# Fincanva — full documentation > Documentation for Fincanva — build, backtest, screen, and follow investment strategies on historical market data. > Language: English (canonical). Translations mirror this text. --- URL: https://fincanva.com/docs/strategies/attaching-a-screener-to-a-strategy # Attaching a screener to a strategy You attach a screener to a strategy from its **Asset selection** card, so the strategy's instruments are chosen by a rule instead of picked by hand. ↗ See this in Fincanva — a strategy's Settings, on the Screening card ## Before you start You need a strategy open in **Asset selection** — either while building one (the **Screener** or **Full setup** strategy type, see [Create a strategy](/docs/strategies/create-a-strategy-and-choose-its-instruments)) or later in [Editing a strategy: the settings cards](/docs/strategies/editing-a-strategy-the-settings-cards#the-settings-cards-one-by-one). Having a screener already saved in your library isn't required — you can also attach a blank one and build it directly on the strategy. If the strategy is public, you can open Asset selection but can't save an attach — make your own copy first, then attach and save on the copy. ## Steps 1. Open the strategy's **Asset selection** card and select **Browse library**, or, in **Pro** mode, select **Attach to In** or **Attach to Out** next to the pool you want to add to. Each opens the **Attach a screener** sheet — "Pick a screener to attach to this strategy." 2. In the sheet, switch between the **My screeners** and **Templates** tabs, or search, to find a screener. Selecting one shows a preview of its filters. 3. Select **Attach screener** to use it, or select **Insert empty screener** to attach one with no filters yet and build it directly on the strategy instead. 4. In **Pro** mode, repeat steps 1–3 for each extra In or Out screener you want — the sheet stays open so you can attach several without reopening it. 5. Save the strategy to keep the attachment — see [Saving, running, and copying a strategy](/docs/strategies/saving-running-and-copying-a-strategy). ## What you should see The attached screener's name and its filter count (for example "3 filters") appear in Asset selection, with **Change** and **Remove** actions next to it. In **Pro** mode, each screener you attached sits in its In or Out group, and you can open it again to edit its filters without detaching it. Fincanva doesn't tell you which screener to attach or whether it's a good fit for your money — see [Is this financial advice?](/docs/investing-theory/is-this-financial-advice#is-this-financial-advice). ## Easy vs Pro: what each mode lets you attach **Easy** and **Pro** are the two attach modes on Asset selection, and they set how many screeners a strategy can use. In **Easy** mode, a strategy uses a single screener — if more than one In screener was attached (for example after switching down from Pro), Easy shows and applies only the first one. In **Pro** mode, you can attach multiple **In** screeners and multiple **Out** screeners to the same strategy, and you can also restrict the universe each screener draws from. Switching Pro down to Easy hides what Easy can't show, and Fincanva asks you to confirm first — see [What happens to my extra In or Out screeners if I switch from Pro to Easy?](#what-happens-to-my-extra-in-or-out-screeners-if-i-switch-from-pro-to-easy) for what is kept and what is dropped. ## What In screeners and Out screeners do An **In** screener narrows the strategy to instruments that match it, and an **Out** screener removes any instrument that matches it — you can only set both in **Pro** mode. Fincanva states the rule for each directly: "Instruments must match an In screener to be considered." and "Instruments matching any Out screener are excluded." With more than one In screener attached, an instrument only needs to match one of them; with more than one Out screener, matching any single one is enough to exclude it. Building and tuning a screener's own filters has its own guide. ## Does editing the saved screener update strategies that already use it? No — attaching a screener copies its filters into the strategy at that moment, so a later edit to the saved screener in your library does not change strategies that already have it attached. Each attached screener becomes its own copy inside the strategy: you can edit that copy's filters directly in Asset selection, and the change only affects this strategy, not your saved screener or any other strategy that used it. Fincanva remembers which library screener an attachment came from, but only to support one manual, one-directional action: from the strategy, you can select **Update source screener** to push that strategy's copy back onto the saved screener in your library, overwriting its filters and universe. Nothing pushes the other way — saving a change to the library screener itself never reaches back into strategies you've already attached it to. ## Common problems ### Why is "Update source screener" unavailable for a screener I attached? You'll see "No source screener tracked — use Save as new instead". Fincanva only offers **Update source screener** when the attached copy still traces back to a screener in your library. An **Insert empty screener** attachment never had a library origin, so it has nothing to update — use **Save as new…** to add it to your library instead. A screener whose library original was later deleted loses the same option, for the same reason. ### What happens to my extra In or Out screeners if I switch from Pro to Easy? They are kept, not deleted. Fincanva asks you to confirm first, in a **Switch to Easy mode** dialog that reads "Easy mode hides these Pro settings. They're kept and restored if you switch back to Pro:" and lists what applies to your strategy — extra In screeners beyond the first (Easy shows only the first), any Out screeners, and your custom max-hold and reinvest-delay timing. Those stop applying in Easy, and switching back to Pro brings them back exactly as you left them. One item on that list is the exception: when you have also picked instruments and your first In screener carries universe filters, the dialog adds "Your screener's universe filters will be dropped — in Easy, your picked instruments are the universe." Those filters are not restored. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/choosing-a-strategy-type # Choosing a strategy type When you create a strategy, Fincanva asks *How do you want to build this strategy?* and offers four types — **Single instrument**, **Multiple instruments**, **Screener**, and **Full setup** — that pre-shape the walk-through so you only fill in the steps your idea needs. Each type describes *what you are building*, not what to invest in: it changes which steps appear and which Asset selection surface you get, never the result the backtest computes. ## How the strategy type shapes what you build The strategy type decides which of the stepper's six steps you walk through. The stepper always ends at **Review**, but the steps before it are trimmed to match the type, so a simple idea skips settings it doesn't need. At creation the picker's subheading says it plainly: "You can change anything later — this just shapes the next few steps." The six stepper steps, in order, are **General**, **Asset selection**, **Risk**, **Allocation**, **Exit rules**, and **Review**. Each type requires a different subset: | Strategy type | Steps in the stepper | |---|---| | Single instrument | Asset selection · Review | | Multiple instruments | General · Asset selection · Allocation · Review | | Screener | General · Asset selection · Allocation · Review | | Full setup | General · Asset selection · Risk · Allocation · Exit rules · Review | Steps that a type leaves out are not lost — every section is either on the type's required rail or offered as an optional add-on you can attach from the Review step, so no section is ever unreachable. ## Which Asset selection surface does each strategy type give you? The strategy type pins the Asset selection surface, and this is the one place where it genuinely limits what a strategy can do rather than just tidying the walk-through. There are three surfaces — a **Basket** you pick by hand, a **Screen** built from rules, and **Compose**, which holds a basket *and* **Include**/**Exclude** screener pools at the same time — and three of the four types offer exactly one of them. | Strategy type | Asset selection surface | Compose, Exclude pool, a second Include screener | |---|---|---| | Single instrument | Basket, one slot that replaces on pick | no | | Multiple instruments | Basket | no | | Screener | Screen | no | | Full setup | Basket, Screen or Compose — you switch between them | yes | Two consequences follow, and both surprise people: - **Compose and the Include/Exclude pools are Full setup only.** A strategy that needs an Exclude pool, or a second Include screener, is a Full setup strategy — no other type has a surface that can show them. - **Max positions stops being a control wherever you pick instruments by hand.** On Single instrument, on Multiple instruments, and on Full setup's Basket surface, the number of positions *is* the number of instruments you picked, so the field is not shown and the count you picked is what runs. Max positions is a control you set only where a screener chooses the holdings — on the Screen surface and inside Compose. ## What is the Single instrument type for? The Single instrument type is for a strategy that trades one instrument, described in its tile as "Trade a single instrument." It is the leanest type: the stepper shows only **Asset selection** and **Review**, so you pick the instrument and go straight to the backtest without allocation or rebalancing choices, because a single holding has nothing to weight against. Its gate is exact — if you select the wrong number of instruments, Asset selection blocks you with "Pick exactly 1 instrument." ## What is the Multiple instruments type for? The Multiple instruments type is for a strategy that holds a basket of instruments you choose yourself, described in its tile as "A basket of instruments you choose." Because there is more than one holding, the stepper adds **General** (naming and rebalance cadence) and **Allocation** (how capital is split across the basket) alongside **Asset selection** and **Review**. Its gate requires at least two holdings — Asset selection blocks you with "Pick 2 or more instruments." ## What is the Screener type for? The Screener type is for a strategy whose holdings are chosen by a screener rather than picked by hand, described in its tile as "Let a screener pick the instruments." Its stepper matches Multiple instruments — **General**, **Asset selection**, **Allocation**, and **Review** — but in Asset selection you define one screener instead of a fixed basket, and that screener decides which instruments the strategy holds each period. Its gate requires at least one screener — Asset selection blocks you with "Add at least 1 screener." Its surface also holds exactly one screen: a second **Include** screener, or any **Exclude** pool, needs **Full setup**. A strategy that carries them is never trimmed to fit — it reads back as Full setup instead. ## What is the Full setup type for? The Full setup type is for building a strategy from scratch with every setting exposed, described in its tile as "Every setting, built from scratch." It is the only type whose stepper shows all six steps — **General**, **Asset selection**, **Risk**, **Allocation**, **Exit rules**, and **Review** — including the Risk conditions and Exit rules the other types leave as optional add-ons, and the only one whose Asset selection offers all three surfaces. If you already know you want every control, pick **Full setup** and then switch to **All at once** — that opens the full [Editing a strategy](/docs/strategies/editing-a-strategy-the-settings-cards) surface, with every card on one page instead of the walk-through. ## Can you change the strategy type later? Yes — the **Strategy type** row in **All at once** switches a strategy to any of the four, and the walk-through's own type picker opens the same four tiles. Adding instruments, attaching a screener, or turning on Risk and Exit rules after the first backtest does not lock you to your original choice, and every section stays reachable whichever type you are on. The picker knows which of the two you are doing. Opened to change an existing strategy's type, it drops the reassurance it shows at creation and warns instead: "Changing the type is not a conversion — the sections the new type has no place for are reset. You'll see exactly what changes before it happens." What changes with the type is the Asset selection surface, so switching to a *narrower* type can cost you part of your selection. Changing the type also moves the stepper's required steps, because each type requires a different subset of the six. The switch confirmation says which way it moved: steps that join the walk carry no review yet, while a switch that takes the unreviewed steps out of the walk can leave nothing to review — "4 steps leave the guided build, and every step it still asks for has already been reviewed." In the stepper the backtest opens only once every required step has been reviewed, so that is what the movement changes; the Backtest on the settings, Analysis and Holdings surfaces is not gated on reviewing steps. Nothing you already reviewed is discarded by the switch: each step keeps its mark, so switching back costs you no progress. ## What happens to your selection when you switch strategy type? Anything the new type's surface cannot hold is removed — but only when you save, and the confirmation tells you how much first. Switching opens a confirmation headed "This removes part of your selection", and the count leads it: "5 selected instruments will be removed — a Screener strategy builds its selection from rules, not from a basket.", or "2 screeners will be removed — this strategy type keeps at most one." Below the count it lists what the new type requires and which configured sections reset to their defaults. The last line is the reassuring one: **"Nothing is removed until you save. Switch back before saving to keep it."** The switch itself changes nothing on disk — the next save is what trims. There is one case where nothing further goes at all. If your setup still needs more than the new type offers, Fincanva does not delete the extras to force the narrowing: it says "Your setup needs more than this type offers, so nothing else is removed — the strategy will keep showing as Full setup." The strategy keeps everything and reads back as the wider type. ## Limits and edge cases The strategy type does not change how a backtest is computed, and no section is ever hidden from **All at once**. What it does restrict is the Asset selection surface: Compose and its Include/Exclude pools exist only on **Full setup**, and Max positions is derived from your basket rather than set by you wherever you pick instruments by hand. For what a strategy is and what it contains, see [What is a strategy?](/docs/strategies/what-is-a-strategy-in-fincanva); for the term itself, see [Strategy type](/docs/getting-started/strategy-type). ## Related To build one step by step, follow [Create a strategy](/docs/strategies/create-a-strategy-and-choose-its-instruments). To change settings on an existing strategy, see [Editing a strategy](/docs/strategies/editing-a-strategy-the-settings-cards). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/choosing-the-instruments-your-strategy-holds # Choosing the instruments your strategy holds The instruments a strategy holds are set in its **Asset selection** — the card where you add specific instruments and lists by hand, scope the strategy by asset class, or leave it open to the whole market. It is one of the settings cards covered in [Editing a strategy: the settings cards](/docs/strategies/editing-a-strategy-the-settings-cards#the-settings-cards-one-by-one), and the step you complete when you first build one in [Create a strategy](/docs/strategies/create-a-strategy-and-choose-its-instruments). ## How you add instruments to a strategy You add instruments in **Asset selection** by searching and adding them one at a time, or by adding a saved list that brings several in at once. The search field reads "Search instruments or lists…"; type a ticker or name, pick a result, and it joins the strategy's selection. A list adds all of its members together, and any already in your selection are skipped. You are not required to name instruments individually. If you pick nothing, the strategy draws from the entire market and you narrow it with filters instead — the card says so directly: "Nothing picked yet, so the strategy draws from the entire market. Search above to narrow it to specific instruments or lists. Filters below screen whatever is in scope at every rebalance." You can also scope the market by asset type using the **Universe** control's **Asset type** field. To have the instruments chosen for you by a rule rather than named by hand, attach a screener instead — that path has its own page, [attach a screener](/docs/strategies/attaching-a-screener-to-a-strategy). ## What "All" and "3 selected" mean on the card The count badge on **Asset selection** shows how many instruments you have named. It reads "All" when you have picked nothing — the strategy is scoped to the whole market — and "3 selected" (or however many) once you have added specific instruments. "All" is therefore a real state, not an empty one: the strategy still has a universe to draw from, just not a hand-picked basket. ## What the "Delisted" and "Not tradable" badges mean An instrument in your selection can carry one of two badges. **"Delisted"** marks an instrument that no longer trades on a live exchange — for example a company that was acquired, went private, or went bankrupt — but whose historical data is still in the catalogue. **"Not tradable"** marks an instrument that exists in the reference data for coverage but is not one you can trade as a live position. Both badges are informational: they tell you why an instrument behaves differently from a currently trading one. ## Why delisted instruments stay in the catalogue Delisted instruments are kept in the data and stay usable, rather than being dropped once they stop trading. That keeps a backtest free of survivorship bias — it can include names that later delisted, instead of testing only the survivors that still exist today. For why leaving them out distorts results, see [which biases Fincanva helps you avoid](/docs/getting-started/the-nine-biases-fincanva-helps-you-avoid#how-does-fincanva-handle-survivorship-bias). ## What the instrument catalogue covers The catalogue spans multiple asset classes, so a strategy can hold instruments across more than one market — and it is the same catalogue behind every strategy, however you select its instruments. What it contains, how it is kept current, and why it keeps names that no longer trade are covered in [what data your backtests run on](/docs/data-methodology/what-data-your-backtests-run-on). ## Limits and edge cases A strategy needs at least one instrument — or, on the screener path, at least one attached screener — before it can be backtested or saved; [Create a strategy](/docs/strategies/create-a-strategy-and-choose-its-instruments) covers the exact gate messages. Leaving **Asset selection** empty is allowed and means "the whole market" rather than "nothing". There is no fixed upper limit on how many instruments a strategy can hold today. On a public strategy you can open the card but not save changes — make your own copy first, as in [Editing a strategy](/docs/strategies/editing-a-strategy-the-settings-cards). ## Related To choose instruments while building, follow [Create a strategy](/docs/strategies/create-a-strategy-and-choose-its-instruments); to change them later, see [Editing a strategy](/docs/strategies/editing-a-strategy-the-settings-cards). To have a rule select instruments for you, see [attach a screener](/docs/strategies/attaching-a-screener-to-a-strategy). For how a run uses the instruments you selected, read [How a backtest works](/docs/backtesting/how-backtesting-works#what-happens-when-you-run-a-backtest); for what a strategy is as a whole, see [What is a strategy?](/docs/strategies/what-is-a-strategy-in-fincanva). Fincanva does not tell you which instruments to hold — see [Is this financial advice?](/docs/investing-theory/is-this-financial-advice#is-this-financial-advice). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/create-a-strategy-and-choose-its-instruments # Create a strategy and choose its instruments You create a strategy from **Single** by picking a [strategy type](/docs/getting-started/strategy-type) and completing a short stepper, then selecting **Backtest**. ↗ See this in Fincanva — Strategies, under New strategy ## Before you start You need to be signed in. You do not need any existing strategies — this creates your first one. ## Steps 1. Open **Single** in the sidebar and select **New strategy**. 2. Answer "How do you want to build this strategy?" by choosing one of the four strategy types: **Single instrument**, **Multiple instruments**, **Screener**, or **Full setup**. Each shapes which stepper steps you see next — see [Choosing a strategy type](/docs/strategies/choosing-a-strategy-type) for what each one is for. To configure every setting on one page instead, pick **Full setup** and switch to **All at once** once the strategy is open. 3. Work through the stepper, in this order: **General** ("Set up your strategy"), **Asset selection** ("Pick assets"), **Risk** ("Set risk conditions"), **Allocation** ("Distribute capital"), **Exit rules** ("Define exit rules"), then **Review** ("Review & backtest"). Your strategy type decides which of these steps appear — **Single instrument** is the leanest (just Asset selection and Review), while **Full setup** shows all six. See [Choosing a strategy type](/docs/strategies/choosing-a-strategy-type) for the per-type breakdown. 4. In **Asset selection**, add the instrument(s) — or, for the **Screener** type, the screener — the strategy will trade. 5. Fill in whichever other steps your strategy type shows: a name and rebalance frequency in General, [risk conditions](/docs/strategies/risk-condition) in the "Set risk conditions" step, weights in Allocation, take-profit/stop-loss conditions in Exit rules. A risk condition switches the strategy between two allocation profiles — Risk-On and Risk-Off — and never pauses, stops or liquidates it, unless the Risk-Off profile you set is itself cash. 6. On **Review & backtest**, check the recap and the "Strategy alerts" panel, then select **Backtest**. ## What you should see The strategy appears in your **Single** library and a backtest starts running on it. Selecting **Backtest** does not take you anywhere: you stay on the final step while the backtest runs — the button in the header reads "Backtesting…", adding the percentage once progress is known — and when the run finishes a **View results** button appears next to **Back** and opens the strategy's **Analysis** section. On **Review & backtest**, the "Strategy alerts" panel lists errors — which block the backtest until fixed — and warnings, which don't. To understand how the pieces you just configured fit together, read [What is a strategy?](/docs/strategies/what-is-a-strategy-in-fincanva). Once the strategy exists, see [Editing a strategy](/docs/strategies/editing-a-strategy-the-settings-cards) for how to change its instruments, allocation, or exit rules later, and [CAGR](/docs/analysis/cagr) for one of the metrics your first backtest will report. ## Common problems ### Why can't I continue past a step? Each strategy type enforces its own instrument or screener count before you can move on, and you'll see one of these messages if a step is missing what it needs: - "Pick exactly 1 instrument." — the **Single instrument** type requires exactly one instrument. - "Pick 2 or more instruments." — the **Multiple instruments** type requires at least two. - "Add at least 1 screener." — the **Screener** strategy type requires at least one screener. Add the missing instrument or screener in **Asset selection**, then continue. ### Why won't the General step accept the name I typed? Because a strategy name has to be at least two characters, and the **General** step will not save one that is shorter. Clear the name or leave a single character and the field shows "Enter a name of at least 2 characters." underneath it, and the step will not let you move on — **Continue** in the stepper, or **Save** when you open **General** from the Review tiles, stays unavailable until you fix it. Type a longer name and both clear. Two characters is what the server requires, so a name this step accepts is one that will save. ### What happens while a strategy is being created? The tiles that create are the four strategy-type tiles and **Combined strategy**. Press one and it shows that it is working while the others stop accepting clicks, so one press creates exactly one thing, however many times you click — **Create new** stays open for the whole request rather than closing on the press. Pressing **Single strategy** creates nothing on the spot: it opens the four strategy-type tiles, and the tile you pick there is what creates. Three things follow from that: - **Closing the dialog does not cancel the create.** Press **Esc**, click the backdrop, or use the close button while it runs and the strategy still exists afterwards — see [What happens when I pick a strategy type from Home?](/docs/getting-started/home-the-page-you-land-on-after-signing-in#what-happens-when-i-pick-a-strategy-type-from-home), which describes what Fincanva does in that moment and how to undo it. - **The name in that toast is the one Fincanva actually saved**, which is not always the one you expected: if you already have an *Untitled strategy*, the new one is saved as *Untitled strategy (1)* and the toast says so. - **The Screener tile creates nothing either, and it appears on one door only.** You reach it from **Create new** in the sidebar; every other route into this dialog offers **Single strategy** and **Combined strategy** alone. Pressing it takes you straight to a new screener with nothing to wait for, and nothing is saved until you save it yourself. The **Combined strategy** tile behaves like the strategy tiles: it saves a real Combined and opens it. It is the one tile that can answer "not yet" instead — with no strategies of your own to combine, pressing it opens a screen inside the Combined flow that reads "A Combined blends your own strategies — you have none yet. Create one to start." and offers a **Create a strategy first** button, which takes you on to the strategy-type tiles; a **Back** control on that step returns you to the Combined screen. Still nothing is created until you actually create and own a strategy. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/editing-a-strategy-the-settings-cards # Editing a strategy: the settings cards You edit an existing strategy in the **All at once** view's **Settings**, opened from the strategy's page in your **Single** library. ↗ See this in Fincanva — a strategy's Settings ## Before you start You need a strategy you've already created — see [Create a strategy](/docs/strategies/create-a-strategy-and-choose-its-instruments). To understand what a strategy's parts are before you change them, read [What is a strategy?](/docs/strategies/what-is-a-strategy-in-fincanva). If the strategy is public, you can open its Settings but can't save changes — make your own copy first, then edit and save the copy. ## Steps 1. Open **Single** in the sidebar and select the strategy you want to change. 2. Open its **Settings**. 3. Change a card — for example, pick a different **Risk** condition, or a new **Allocation** method. The change applies to your working copy right away. 4. Save the strategy. 5. Select **Backtest** to run a new backtest and see the effect of the change. ## What you should see The card you changed shows its new value in **Settings**. After you select **Backtest**, a new run reflects the change — see [How a backtest works](/docs/backtesting/how-backtesting-works#what-happens-when-you-run-a-backtest) for what a run actually computes, including [CAGR](/docs/analysis/cagr). Fincanva doesn't tell you whether a change is good or bad for your money — see [Is this financial advice?](/docs/investing-theory/is-this-financial-advice#is-this-financial-advice). ## The settings cards, one by one A single strategy's Settings is laid out in two columns: **Strategy type**, **Asset selection**, and **Risk** on the left; **Rebalance**, **Allocation**, and **Position exits** on the right. Optional sections you haven't set up yet appear as an add chip rather than a full card. Each one controls a different part of the strategy: | Card | What it controls | |---|---| | **Strategy type** | Which of the four types the strategy is (Single instrument, Multiple instruments, Screener, or Full setup) — see [Choosing a strategy type](/docs/strategies/choosing-a-strategy-type). | | **Asset selection** | The instruments the strategy holds, added directly or attached through screeners. | | **Risk** | Risk conditions that switch the strategy to its Risk-Off allocation when they trigger. The conditions themselves are covered in their own guide. | | **Rebalance** | How often the strategy rebalances, set with the "Rebalance every" control. | | **Allocation** | How capital is distributed across the strategy's instruments. The allocation methods are covered in their own guide. | | **Position exits** | The take-profit and stop-loss rules that close a position. The exit mechanics are covered in their own guide. | ## Common problems ### Why can't I save my changes? Save is disabled on a public strategy. Public strategies can't be edited directly — make your own copy, then edit and save the copy instead of the original. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/how-often-your-strategy-rebalances # How often your strategy rebalances The rebalance frequency is your strategy's master clock: it sets how often the strategy re-checks its instruments and resets their weights. You set it with the **Rebalance every** control, and the month-based settings that ride on it — max hold and reinvest delay — are measured against it. ## How the rebalance frequency works The rebalance frequency is the interval at which the strategy rebuilds its target: it re-reads which [instruments are in scope](/docs/strategies/choosing-the-instruments-your-strategy-holds), re-applies the allocation weighting, and resets each position back to its intended weight. Between two rebalances the positions stay as they are and their weights simply drift with the market — nothing is bought or sold on the strategy's schedule until the next rebalance falls due. Because the strategy rebuilds its target only at these intervals, the frequency is the master clock for that schedule — though not every rule in the strategy runs on it. ## What frequencies can I choose? You choose from a fixed set of intervals in the **Rebalance every** control: **1, 3, 6, 12, 18, or 24 months** (the unit shows as "mo"). One month is the most frequent cadence and 24 months is the slowest. The number you pick is the strategy's base cadence — a 1-month strategy re-checks twelve times a year, a 12-month strategy once a year. There is no weekly or daily setting today. ## How does the frequency shape a backtest? The frequency sets how often, across the tested history, the backtest stops to re-check and rebalance the strategy. A shorter interval means more rebalance points over the same period, so the strategy reacts to the market more often; a longer interval means fewer rebalance points and a strategy that holds each set of weights for longer. It does not change *what* a rebalance does at each point — only how many times it happens over the backtest. See [How a backtest works](/docs/backtesting/how-backtesting-works#what-happens-when-you-run-a-backtest) for what a single backtest computes at each of those points. Fincanva does not tell you which rebalance frequency is best for your money — see [Is this financial advice?](/docs/investing-theory/is-this-financial-advice#is-this-financial-advice). ## How do risk conditions and exits interact with the frequency? The frequency paces some of these rules and not others, so the answer splits three ways. **Risk conditions are not paced by it.** Each condition is measured on the bars of the series it watches, and its **Confirmation delay (weeks)** counts calendar weeks from the flip rather than rebalance periods — see [confirmation delay](/docs/strategies/confirmation-delay#what-does-the-confirmation-delay-change). **Take profit and stop loss are not paced by it either.** Each position's gain or loss is checked on that position's own price bars, so either exit can close a position between two rebalances — see [execution time](/docs/strategies/execution-time#when-does-a-modelled-trade-fill-within-a-bar) for the price such a close books at. **Max hold is paced by it.** It acts at the strategy's scheduled rebalances, which is why its value has to be a whole multiple of the frequency — see [max hold months](/docs/strategies/max-hold-months#when-does-max-hold-actually-close-a-position). Two settings change how a flip lands against the schedule: - **Auto-rebalance** — a risk condition can carry a **Triggers rebalance** toggle (labelled **Auto-rebalance** on its card, with the note "Trigger a rebalance when the condition flips."). With it on, the moment the condition flips — for example into a Risk-Off state — the strategy performs an extra rebalance off its normal schedule, rather than waiting for the next scheduled one. - **Confirmation delay (weeks)** — a risk condition can wait a set number of weeks after it flips before acting, so a brief flip doesn't trigger a reaction. Its hint reads "0 = act immediately." Two exits counted in months — Max hold and Reinvest delay — must be whole multiples of your rebalance frequency. If a value isn't, the app blocks it and tells you it must be a multiple of your chosen frequency in months. An off-schedule rebalance forced by a flip is not one of the scheduled rebalances those settings count: max hold and the Exclude-screener exit do not act on one. Where within a bar a take-profit or stop-loss exit actually fills is covered in [execution time](/docs/strategies/execution-time#when-does-a-modelled-trade-fill-within-a-bar). ## Limits and edge cases The **Rebalance every** control offers only the fixed set of 1, 3, 6, 12, 18, and 24 months — you can't enter an arbitrary number, and there is no sub-monthly option in the app today. Changing the frequency is a settings edit like any other: it takes effect on your working copy, and you re-run a backtest to see its effect — see [Editing a strategy: the settings cards](/docs/strategies/editing-a-strategy-the-settings-cards#the-settings-cards-one-by-one). The same rebalance frequency governs the whole strategy; it is not set per instrument. ## Related To change this setting on an existing strategy, follow [Editing a strategy: the settings cards](/docs/strategies/editing-a-strategy-the-settings-cards). To set it while building a new one, see [Create a strategy](/docs/strategies/create-a-strategy-and-choose-its-instruments). For where this fits among a strategy's parts, read [What is a strategy?](/docs/strategies/what-is-a-strategy-in-fincanva). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/how-risk-off-affects-rebalancing # How Risk-Off affects rebalancing A Risk-Off flip normally acts on your strategy's regular rebalance schedule, but you can make it force an off-schedule rebalance the moment it happens. Two settings on each risk condition — **Auto-rebalance** and **Confirmation delay (weeks)** — decide how a flip is timed against your [rebalance frequency](/docs/strategies/how-often-your-strategy-rebalances). ## How a Risk-Off flip can force an off-schedule rebalance Turning on a condition's **Auto-rebalance** toggle makes the strategy rebalance the instant that condition flips, instead of waiting for the next scheduled rebalance. The toggle carries the note "Trigger a rebalance when the condition flips.", and in the risk list a condition set this way is marked "Triggers rebalance". With Auto-rebalance off, a flip changes which regime is active, but the change only takes effect at the strategy's next scheduled rebalance. The list summarises the trigger logic as "Go Risk-Off when any trigger fires:". ## How the confirmation delay changes when Risk-Off acts The **Confirmation delay (weeks)** makes a condition wait a set number of weeks after it flips before it acts, so a brief flip doesn't set off a reaction (0 to 12 weeks; its hint reads "0 = act immediately."). This governs whether the flip is acted on *yet*; **Auto-rebalance** then governs whether acting means an off-schedule rebalance or a wait for the next scheduled one — see [Risk conditions](/docs/strategies/risk-conditions#what-the-confirmation-delay-and-auto-rebalance-do) for the field itself. ## When Risk-Off acts on your normal rebalance schedule When Auto-rebalance is off, a Risk-Off flip takes effect at the strategy's next scheduled rebalance rather than immediately. Your rebalance frequency is the master clock for this — set in the **Rebalance every** control — and a flip that isn't set to trigger its own rebalance simply rides that clock — see [How often your strategy rebalances](/docs/strategies/how-often-your-strategy-rebalances#how-do-risk-conditions-and-exits-interact-with-the-frequency). ## How you find out your strategy has gone Risk-Off You see the current regime by opening the strategy — the app does not notify you when a strategy flips to Risk-Off. There are no push notifications, alerts, or emails on a flip today. The risk list shows each condition's logic — "Always Risk-On", "Match → Risk-Off", or "Any match → Risk-Off" — so you can see what would trigger a switch. ## Limits and edge cases Auto-rebalance and the confirmation delay are set per condition, not per strategy — each of a strategy's up-to-two risk conditions carries its own **Auto-rebalance** toggle and its own **Confirmation delay (weeks)**. The confirmation delay is capped at 12 weeks. Whether an off-schedule rebalance actually changes your holdings depends on the Risk-Off allocation profile you set — if Risk-Off is configured identically to Risk-On there is nothing to switch to, so the rebalance has no effect. For what the two regimes are and how a condition is built, see [Risk conditions](/docs/strategies/risk-conditions). ## Related For the two regimes and the full condition builder, read [Risk conditions](/docs/strategies/risk-conditions). For the master clock a flip rides when Auto-rebalance is off, see [How often your strategy rebalances](/docs/strategies/how-often-your-strategy-rebalances). To decide whether to use risk management at all, read [When to use risk management](/docs/strategies/when-risk-management-changes-a-strategy). Position-level exits rebalance on their own terms — see [Position exits](/docs/strategies/position-exits). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/invested-capital-and-cash-reserve # Invested capital and cash reserve The invested portion is the share of a combined strategy's capital that the allocation profile puts to work; whatever is left over is held as a cash reserve. You set it as a single percentage, so an invested portion of 75% deploys three-quarters of the capital and keeps one-quarter in cash. ## How the invested portion works The invested portion scales how much capital the allocation profile deploys before the strategies it holds are weighted against each other. At 100% the profile is fully invested; below that, the profile deploys only that share and the remainder stays uninvested as cash. It is set on a combined strategy, one value per allocation profile, and it does not change *which* strategies are held — only *how much* of your capital is at work in them. ## Where you set the invested portion You set it in a combined strategy's **Allocation**, on the allocation profile, using the **Invested portion** control — its helper reads "Share of capital this profile deploys" and its unit is "%". Pick a preset or set a custom value with the slider: | Control value | What it deploys | |---|---| | **Fully invested** | 100% — no cash reserve | | **Mostly invested** | 75% | | **Half invested** | 50% | | **Lightly invested** | 25% | | **Custom** | any value you set with the slider | To reach the Allocation card, open the strategy's settings — see [Editing a strategy: the settings cards](/docs/strategies/editing-a-strategy-the-settings-cards#the-settings-cards-one-by-one). ## What happens to the capital you don't invest Capital above the invested portion is held as a cash reserve — it is not deployed into any strategy. In a backtest what the reserve does depends on your simulation assumptions: with the Costs assumption off — its default — idle cash earns nothing, so the reserve neither gains nor loses on its own; with Costs on it can earn interest. See [interest received and paid](/docs/analysis/interest-received-and-paid) for the rate. Holding more in cash lowers how much of the strategy is exposed to the market, which usually means smaller swings — see [How a backtest works](/docs/backtesting/how-backtesting-works#what-happens-when-you-run-a-backtest) for what a backtest computes. Fincanva doesn't tell you the right amount to hold in cash — see [Is this financial advice?](/docs/investing-theory/is-this-financial-advice#is-this-financial-advice). ## How risk conditions can lower the invested portion A defensive stance holds a smaller invested portion, and therefore more cash, than a fully-invested one. When a combined strategy turns defensive under its Risk conditions — its Risk-Off state — it can hold a lower invested portion, moving capital out of the market and into the cash reserve until conditions ease. How and when that switch happens is set in the **Risk** card, covered under [Editing a strategy: the settings cards](/docs/strategies/editing-a-strategy-the-settings-cards#the-settings-cards-one-by-one). ## Limits and edge cases A new profile starts fully invested at 100%; the invested portion can go below that, and above it up to 300% on any plan that includes a Combined — the range and what investing above 100% means are on [invested portion](/docs/backtesting/invested-portion). Setting it to 0% holds everything in cash and puts nothing to work — the backtest then just tracks an uninvested balance. The invested portion is a combined-strategy control: a single strategy manages how much capital is at work through its own allocation profile, not through this control. ## Related To see where this control sits among the other settings, read [Editing a strategy: the settings cards](/docs/strategies/editing-a-strategy-the-settings-cards#the-settings-cards-one-by-one). For what a strategy and a combined strategy are, see [What is a strategy?](/docs/strategies/what-is-a-strategy-in-fincanva#what-is-a-strategy-in-fincanva). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/position-exits # Position exits Position exits are auto-close rules that act on each individual position rather than on the strategy as a whole, and Fincanva has four of them: **Take profit**, **Stop loss**, **Max hold**, and **Reinvest delay**. Each one is an on/off toggle paired with a value — off means the rule isn't applied. ↗ See this in Fincanva — a strategy's Settings, on the Position exits card ## Before you start You need a strategy open in its settings, either while building one or later in [Editing a strategy: the settings cards](/docs/strategies/editing-a-strategy-the-settings-cards#the-settings-cards-one-by-one). Two of the four exits live on the **Position exits** card ("Auto-close rules applied to each position"); the other two live in the Pro-mode screening settings — see [Where the four exit controls live](#where-the-four-exit-controls-live) below. If the strategy is public, you can open its settings but can't save an edit — make your own copy first. ## Steps Each exit is a toggle with a value, and turning the toggle off is what stops the rule from applying. While you build a strategy, the rules step asks it as a question — "When should positions be exited?". 1. Open the strategy's settings, while building it or later from [the settings cards](/docs/strategies/editing-a-strategy-the-settings-cards#the-settings-cards-one-by-one). 2. For **Take profit** or **Stop loss**, switch its toggle on in the **Position exits** card and enter a percentage. Take profit starts at **150%**, Stop loss at **−30%**. 3. For **Max hold** or **Reinvest delay**, set the **Screening** card to **Pro**, then switch the control on and enter a number of months. Each starts at your rebalance frequency. 4. To stop a rule from applying, switch its toggle off. A rule with its toggle off is simply not evaluated. 5. Save the strategy and run a new **Backtest** to see the effect — see [saving and running a strategy](/docs/strategies/saving-running-and-copying-a-strategy). ## What you should see On the **Position exits** card the status label reflects your choices as "No exits active", "Stop loss active", "Take profit active", or "Both exits active". With Stop loss or Take profit on, the card's footer names the level a position closes at, starting "Positions close at". When no exit rule is active the card shows "No exit rules active — positions only close at the next rebalance." ## Where the four exit controls live The four exits are split across two surfaces in the app, so where you find each one depends on the control. **Take profit** and **Stop loss** are on the **Position exits** card, described there as "Auto-close rules applied to each position". **Max hold** and **Reinvest delay** are Pro-mode settings on the screening surface, not on the Position exits card. All four behave the same way — a toggle plus a value, where turning the toggle off stops the rule from applying — but you reach the first pair and the second pair from different places. ## What does Take profit do? Take profit closes a position once it reaches a target gain, and it lives on the **Position exits** card — the card described there as "Auto-close rules applied to each position". Its value is a positive percentage (suffix "%") and it is **off by default**. When you turn it on it starts at **150%**, and you can set it anywhere from **5% to 1000%**. If you enter a value outside that band, the app blocks it with "Take profit must be between 5% and 1000%." A higher number means the position has to gain more before the rule closes it. ## What does Stop loss do? Stop loss closes a position once it has fallen past a threshold loss, and it sits on the same **Position exits** card, under the title "Stop loss". Its value is a *negative* percentage (suffix "%") because it describes a loss, and it is **off by default**. When you turn it on it starts at **−30%**, and you can set it anywhere from **−100% to −5%**. A value outside that band is blocked with "Stop loss must be between −100% and −5%." A number closer to −100% lets a position fall further before the rule closes it; a number closer to −5% closes it sooner. ## What does Max hold do? Max hold sells a position after you have held it for a set number of months, and it is a **Pro-mode** setting on the screening surface — not on the Position exits card. Its hint reads "Sell a position after holding it this long", its value is in months (suffix "mo"), and it is **off by default**. When you turn it on, the field is seeded with your own rebalance frequency — always a valid multiple, so the value it starts at depends on the strategy. You can set it from **1 to 120 months**, and the value must be a **whole multiple of your rebalance frequency** — see [How the rebalance frequency paces exits](#how-does-the-rebalance-frequency-pace-exits) below. ## What does Reinvest delay do? Reinvest delay keeps an instrument out of the strategy's choices for a set number of months after its position closes, so the strategy cannot buy it straight back — it holds back the instrument, not the freed cash (see [reinvest delay](/docs/strategies/reinvest-delay)). It is also a **Pro-mode** setting on the screening surface. Its hint reads "Wait this long before re-entering an instrument after its position closes", its value is in months (suffix "mo"), and it is **off by default**. Like Max hold, turning it on seeds the field with your own rebalance frequency rather than a fixed number. It ranges from **1 to 120 months** and must be a **whole multiple of your rebalance frequency**. ## How does the rebalance frequency pace exits? It paces two of the four and neither of the other two. **Max hold** and **Reinvest delay** are quantized to whole rebalance periods, which is why each must be a whole multiple of your [rebalance frequency](/docs/strategies/how-often-your-strategy-rebalances#how-do-risk-conditions-and-exits-interact-with-the-frequency). If you enter a number that isn't such a multiple, the app blocks it with a message naming your frequency, such as "Must be a multiple of 3 months". So a strategy that rebalances every 3 months accepts a Max hold of 3, 6, 9, or 12 months, but not 4 or 5. Max hold acts at the strategy's **scheduled** rebalances only: a rebalance forced off schedule by a [risk condition](/docs/strategies/risk-conditions) does not close a position for max hold. **Take profit** and **Stop loss** run on a different clock. Each position's gain or loss is checked on that position's own price bars, so either exit can close a position between two rebalances, on the bar that reached the threshold rather than at the next rebalance — see [execution time](/docs/strategies/execution-time#when-does-a-modelled-trade-fill-within-a-bar) for the price such a close books at. ## What are the limits and validation messages? Every exit control has a fixed range, a value it takes when enabled, and its own validation message, and all four are off until you turn them on: - **Take profit** — 5% to 1000%, starts at 150%. Out of range: "Take profit must be between 5% and 1000%." - **Stop loss** — −100% to −5%, starts at −30%. Out of range: "Stop loss must be between −100% and −5%." - **Max hold** — 1 to 120 months, starts at your rebalance frequency, whole multiple of that frequency. Not a multiple: "Must be a multiple of 3 months" (the number shown is your rebalance frequency). - **Reinvest delay** — 1 to 120 months, starts at your rebalance frequency, whole multiple of that frequency. Same messages as Max hold. With all four off, the card confirms it: "No exit rules active — positions only close at the next rebalance." Fincanva does not tell you which take-profit or stop-loss level is best for your money — see [Is this financial advice?](/docs/investing-theory/is-this-financial-advice#is-this-financial-advice). ## Common problems ### Why does the card say "Stop loss needs attention"? "Enter a value." under an exit means it is switched on with its field empty. "Take profit must be between 5% and 1000%." or "Stop loss must be between −100% and −5%." means its value is outside the range. While either message shows, the status label reads "Stop loss needs attention", "Take profit needs attention", or "Exit rules need attention" when both exits have a problem. To fix it, enter a value inside the range — every range is listed under [What are the limits and validation messages?](#what-are-the-limits-and-validation-messages). ### Why won't Max hold or Reinvest delay accept my number? The field under the control names the reason: - "Enter a value." — the control is switched on with its field empty. - "Enter 1–120 months." — the number is outside the range. - "Enter a whole number." — the number has a decimal part. - "Must be a multiple of 3 months" — the number is not a whole multiple of your rebalance frequency; the figure shown is your own frequency. To fix it, enter a whole number of months from 1 to 120 that is a multiple of your rebalance frequency — see [How does the rebalance frequency pace exits?](#how-does-the-rebalance-frequency-pace-exits). ## Related Position exits act on individual positions; to make the *whole* strategy go defensive instead, see [Risk conditions](/docs/strategies/risk-conditions) and [Set up a risk condition](/docs/strategies/set-up-a-risk-condition). To change any of these controls on an existing strategy, follow [Editing a strategy: the settings cards](/docs/strategies/editing-a-strategy-the-settings-cards#the-settings-cards-one-by-one), then [save and re-run](/docs/strategies/saving-running-and-copying-a-strategy) to see the effect. For where exits fit among a strategy's parts, read [What is a strategy?](/docs/strategies/what-is-a-strategy-in-fincanva). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/risk-conditions # Risk conditions A risk condition watches a market signal and, when it triggers, switches your strategy to its **Risk-Off allocation** — the more defensive mix you defined yourself. When the signal clears, the strategy switches back to its **Risk-On** allocation. A risk condition never pauses or stops a strategy: it keeps running, keeps rebalancing and keeps holding positions, just more defensively. ## How risk conditions switch a strategy between Risk-On and Risk-Off A strategy always holds one of two allocations, and its risk conditions decide which one. [Risk-On](/docs/strategies/risk-on-and-risk-off) is the default — your normal allocation, the strategy exactly as you built it. A triggered [risk condition](/docs/strategies/risk-condition) moves it to Risk-Off, the defensive allocation you defined; when the condition clears, it moves back. There is no third state and no gap between the two: with nothing configured, the **Risk** card states the baseline plainly — "Without a condition, the strategy stays in Risk-On at all times." {/* VISUAL: svg-diagram — two-state machine with Risk-On and Risk-Off as the only states, a "condition triggers" arrow one way and a "condition clears" arrow back, each state labelled with the allocation it runs — tracked in VISUAL_BACKLOG */} The switch is an allocation change and nothing else. The app's risk step puts it in exactly those terms — "Define risk conditions that switch the strategy to its Risk-Off allocation when triggered." — and you build the conditions in the **Risk** card, described as "Automatically de-risk when markets turn". A strategy running Risk-Off is not paused, halted or liquidated; it holds whatever its Risk-Off allocation holds. ## What a single risk condition is made of A risk condition is one watched series, one comparison, and two behavior settings — enough to read as a single sentence: *when SPY is less than its 200-period simple moving average for two weeks, switch to Risk-Off.* The builder, headed "New risk condition", writes every rule out as a sentence like that one, and each part of it is a value you select to change. | Part | The field that sets it | In the example | |---|---|---| | Signal | **Instrument** | SPY | | Reference | a second series, or the numeric thresholds — the **Signal** you choose decides which | SPY again, with **Indicator** "Simple moving average" and **Period** 200 | | Comparison | **Operator** — "is above" or "is below" | is below | | Confirmation | **Confirmation delay (weeks)** | 2 | | Action | the Risk-Off allocation — always | switch to Risk-Off | {/* VISUAL: chart — one price line and its 200-period moving average on the same axis, the crossing point marked, the two-week confirmation window shaded after it, and the switch to Risk-Off marked at the end of that window — tracked in VISUAL_BACKLOG */} That example is a **Double series** condition: what the signal is measured against is another series rather than a number. The other shape you build by hand, **Single series**, measures one transformed series against two thresholds you type. Beyond these two, the **Quantitative regimes** group offers three rules that decide from a model instead of a comparison: [Hidden regimes (Markov)](/docs/strategies/hidden-regimes-markov), [Clustering](/docs/strategies/clustering) and, on a Combined only, [Strategy's own performance](/docs/strategies/strategy-s-own-performance) — [condition types](/docs/strategies/condition-types) covers what each of the five shows. The **Indicator** choices are the same for both hand-built shapes: "Raw price" ([raw price](/docs/strategies/raw-price)), "Simple moving average" ([SMA](/docs/strategies/simple-moving-average-sma)), "Percent change" ([percent change](/docs/strategies/percent-change)) and "Average momentum" ([average momentum](/docs/strategies/average-momentum)). Rather than build from scratch, you can start from a ready-made [risk template](/docs/strategies/risk-templates) and adjust it. ## How the Risk-Off and Risk-On thresholds work A **Single series** risk condition has two thresholds, set independently: a **Risk-Off** one that switches the strategy into Risk-Off, and a **Risk-On** one that switches it back. Because they are two separate numbers rather than one line, the condition gets a distinct entry point and a distinct exit point: set the Risk-Off threshold at 25 and the Risk-On threshold at 20 on a volatility reading, and the strategy only returns to Risk-On once the reading has fallen a clear distance below the level that made it defensive. That gap is what stops a reading hovering around one value from flipping the allocation back and forth — the [whipsaw](/docs/strategies/whipsaw) the two thresholds exist to damp. A **Double series** condition has no numeric thresholds at all: the comparison between the two series is the whole condition. ## What Risk-Off does to your allocation Switching to Risk-Off swaps in the Risk-Off allocation profile — a complete allocation with its own weighting method and its own [invested portion](/docs/backtesting/invested-portion), typically more defensive than the Risk-On one. The two sit side by side in the **Allocation** card: **Risk-On** is the allocation the strategy uses while no condition is firing, and **Risk-Off** the one it swaps to while a condition is. Because the Risk-Off profile can put less capital to work, going defensive shows up as a larger cash reserve, not as a stopped strategy — see [Risk-On and Risk-Off](/docs/strategies/risk-on-and-risk-off) for what changes between the two. Until you configure the defensive side, the app shows "Risk-Off allocation needs to be set". Fincanva does not tell you how defensive to be, or when — see [Is this financial advice?](/docs/investing-theory/is-this-financial-advice#is-this-financial-advice). ## What the confirmation delay and auto-rebalance do Two per-condition settings decide when a flip is acted on and whether it forces a rebalance. **Confirmation delay (weeks)** makes the condition wait before the strategy acts — a whole number from 0 to 12, with the hint "0 = act immediately." — so a move that reverses inside the window never changes the allocation; the trade-off it buys is covered in [confirmation delay](/docs/strategies/confirmation-delay). **Auto-rebalance** ("Trigger a rebalance when the condition flips.") decides whether the switch triggers a rebalance the moment it happens or waits for the next scheduled one — see [auto-rebalance on flip](/docs/strategies/auto-rebalance-on-flip). How the two pace against the strategy's own clock is covered in [How Risk-Off affects rebalancing](/docs/strategies/how-risk-off-affects-rebalancing). ## Limits and edge cases - **At most two risk conditions.** A strategy holds a first and a second condition, and there is no third slot. Removing the first promotes the second into its place. - **The app combines two conditions with Or.** Either one triggering is enough to switch the strategy to Risk-Off; they never both have to fire, so a second condition makes a strategy go defensive more often, not less. The label above the list tracks this — "Always Risk-On" with none configured, "Match → Risk-Off" with one, "Any match → Risk-Off" with two. See [two-condition combination](/docs/strategies/two-condition-combination). - **An identical Risk-Off allocation is a no-op.** If the Risk-Off allocation is configured the same as Risk-On, triggering changes nothing. The app flags it before you backtest with "Risk-Off allocation is the same as Risk-On." and badges the profile "Matches Risk-On". - **The behavior settings are per condition.** Each condition carries its own confirmation delay and its own auto-rebalance setting, so one can act immediately while the other waits out its window. ## Related - [Set up a risk condition](/docs/strategies/set-up-a-risk-condition) — build or edit one, step by step. - [Risk-On and Risk-Off](/docs/strategies/risk-on-and-risk-off) — the two allocation profiles a condition switches between. - [Condition types](/docs/strategies/condition-types) · [Confirmation delay](/docs/strategies/confirmation-delay) · [Auto-rebalance on flip](/docs/strategies/auto-rebalance-on-flip) — the pieces one condition is built from. - [When risk management changes a strategy](/docs/strategies/when-risk-management-changes-a-strategy) — the trade-off you take on by adding one. - [How often your strategy rebalances](/docs/strategies/how-often-your-strategy-rebalances) — the clock a flip rides when Auto-rebalance is off, and does not when it is on. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/saving-running-and-copying-a-strategy # Saving, running, and copying a strategy The strategy workspace header carries one button for both jobs — it shows **Save** while you have unsaved changes and **Backtest** once they're saved — plus a separate copy action that duplicates the strategy or unlocks a Public one for editing. ↗ See this in Fincanva — the header of a strategy's workspace ## Before you start You need a strategy open in its workspace — see [Create a strategy](/docs/strategies/create-a-strategy-and-choose-its-instruments) if you haven't made one yet. If the strategy is Public, you can change its settings locally to see how they'd look, but you can't save those changes to it directly — see "Why can't I save changes to a Public strategy?" below. ## Steps 1. Open the strategy from your library and go to its **Settings**. 2. Change a card — see [Editing a strategy](/docs/strategies/editing-a-strategy-the-settings-cards#the-settings-cards-one-by-one) for what each one controls. The header's primary button switches to **Save** as soon as you have an unsaved change. 3. Select **Save**. Fincanva shows a "Saved" toast when the write succeeds, or "Couldn't save — try again." if it fails — select the button again (it now reads **Retry save**) to retry. 4. Once there's nothing left to save, the same button switches back to **Backtest** — select it to run a new backtest on the strategy's current saved version. While it's running, the button reads "Backtesting…", adding the percentage once progress is known. 5. To duplicate a strategy you own, open its **⋯** menu (top right of the header) and select **Duplicate**. Fincanva names the copy after the original with "(copy)" appended, shows a "Strategy duplicated" toast, and opens the new copy — the original is untouched. The same duplicate action is also available as **Duplicate** from a strategy's row menu in your library list, without opening the strategy first. 6. To get an editable version of a Public strategy, open it and select **Copy to Mine** — on a Public strategy this is the only action shown in the header. Fincanva adds the copy to your own library and shows "Copied to your strategies". ## What you should see After **Save**, the header's primary button reverts to **Backtest** and the strategy's Settings show your change. After a backtest run finishes, see [How a backtest works](/docs/backtesting/how-backtesting-works#what-happens-when-you-run-a-backtest) for what a run actually computes and the states a result can show. A duplicate — whether you made it from the header's **⋯** menu or from your library list — is a fully independent strategy: it starts from the strategy's last saved version, and editing, saving, or deleting the copy never touches the original. As with any backtest result, Fincanva doesn't tell you whether a change is good or bad for your money — see [Is this financial advice?](/docs/investing-theory/is-this-financial-advice#is-this-financial-advice). ## The header actions, one by one | Action | What it does | |---|---| | **Save** | Persists your unsaved changes to the strategy. Shown only while the form is dirty; not available on a Public strategy. | | **Backtest** | Runs a new backtest on the strategy's saved version. Takes Save's place in the header once there's nothing left to save — see [How a backtest works](/docs/backtesting/how-backtesting-works). | | **Duplicate** | Copies a strategy you own, from its last saved version, via the **⋯** menu. | | **Copy to Mine** | Adds an editable copy of a **Public** strategy to your library; on a Public strategy it's the header's only action, and it adds the copy to your library instead of opening it. | | **Duplicate** (library list) | The same action, available from a strategy's row menu in your Single or Combined library list. | ## Common problems ### Why can't I save changes to a Public strategy? Save doesn't appear in the header for a Public strategy — there's nothing to persist to the original. Select **Copy to Mine** to add an editable copy to your own library, then change and save that copy instead. ### Why is Backtest disabled on a Combined strategy? A Combined needs at least two strategies switched on to run. With fewer, Backtest stays disabled — open the Combined's **Settings**, add a strategy on its **Strategies** card with **Add strategy** (or switch a kept-aside one back on), then run it. ### Why was my run refused? Because one of the setup checks below failed, and the message names which one and the step that fixes it. Fincanva asks the same question wherever a run starts — the header's **Backtest**, **Run** in your library list, **Retry backtest** on a failed run, and the re-run on an analysis or holdings page all go through it — so the answer never depends on where you pressed. Often the control is already unavailable and carries the reason before you press it, and the wording is the same as if you had — in your library list too. The checks, and the message each one produces: | What is missing | The message you see | |---|---| | Instruments | "Add at least 1 instrument before running this strategy." — the count is whatever your [strategy type](/docs/getting-started/strategy-type) requires. | | A screener | "Add at least 1 screener before running this strategy." | | A second strategy in a Combined | "Add one more strategy to run this Combined." — the number is however many the Combined is short of two. See [Incomplete Combined](/docs/backtesting/incomplete-combined). | | Enough strategies switched on in a Combined | "Running this needs 2 strategies switched on." — a strategy kept aside on the **Strategies** card does not count until you switch it back on. | | A [blocking alert](/docs/backtesting/strategy-alerts) | The alert's own sentence. Today that is "Risk-Off allocation needs to be set." | | Readable saved settings | "This strategy's saved settings can't be read, so it can't run. Create it again as a new strategy, or contact support." | Each of those arrives with the place that owns the fix appended to it, in the form "Fix it in Strategies." — so a Combined holding a single strategy reads "Add one more strategy to run this Combined. Fix it in Strategies." Today that place is **Asset selection**, **Allocation**, or **Strategies** — the three a refusal can point at. Open it, fix what it names, then run again. The unreadable-settings refusal names no step: the stored strategy is damaged, and no step in the editor can show what it held, so the sentence itself says what to do. The same sentence can answer **Save**: since the editor cannot show those settings, a save that would replace them with nothing is refused rather than allowed to erase them. If Fincanva cannot name the cause it falls back to "This strategy can't run yet; fix the highlighted issue first". ### Can I see previous versions of a strategy? Not today — Fincanva doesn't keep a version history you can browse or restore. If you want to preserve a strategy's current state before making a risky change, select **Duplicate** first: the copy is independent, so the original stays exactly as it was. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/set-up-a-risk-condition # Set up a risk condition You set up a risk condition from a strategy's **Risk** card, using the condition builder to define the market signal that flips the strategy to its Risk-Off allocation. ↗ See this in Fincanva — a strategy's Settings, on the Risk card ## Before you start You need a strategy open in its settings, with the **Risk** card visible — see [Editing a strategy: the settings cards](/docs/strategies/editing-a-strategy-the-settings-cards#the-settings-cards-one-by-one). For what the two regimes are before you configure one, see [Risk conditions](/docs/strategies/risk-conditions). ## Steps 1. Open the strategy's **Risk** card and select **Add a condition** — or **Add second condition** if a first one already exists. Either opens the condition builder — "Configure a market condition that flips this strategy to its Risk-Off allocation." 2. Choose what the rule watches from the **Signal** menu at the top. A ready-made template, grouped under **Volatility**, **Yield curve**, **Inflation** and **S&P 500**, fills the rule in for you; the two blank ones under **Custom** are **Single series** — one instrument's indicator against two thresholds — and **Double series**, which compares two series directly. The **Quantitative regimes** group lists [Hidden regimes (Markov)](/docs/strategies/hidden-regimes-markov), [Clustering](/docs/strategies/clustering) and, on a Combined, [Strategy's own performance](/docs/strategies/strategy-s-own-performance): rules that decide from a model, with their own settings in place of the indicator, operator and thresholds. The template's description appears under the menu, with " (modified)" after it once you change what it set, and the reset button beside the menu puts it back as it ships. 3. Read the rule as a sentence and set its values. The builder writes the rule out — for the **VIX** template, "Go Risk-Off when the value of" the VIX "is above 25. Back to Risk-On when it is below 20." — and every value in it is underlined: select one to open a small panel holding its control and a short explanation. The instrument opens the instrument search; the measure ("value", "200-day moving average") opens the **Indicator** — **Raw price**, **Simple moving average**, **Percent change** or **Average momentum** — with a **Period** field when the indicator reads over a window; each comparison opens its operator; each number opens its field. 4. On a **Single series** rule, set both halves: the **Risk-Off** comparison that switches the strategy into its Risk-Off allocation, and the **Risk-On** comparison that switches it back. A **Double series** rule has one comparison between its two series and no thresholds. 5. Set the last sentence, "When the rule flips, switch immediately without rebalancing.": the first value is the **Confirmation delay (weeks)** — "0 = act immediately.", 0 to 12 weeks — and the second is **Auto-rebalance** — "Trigger a rebalance when the condition flips." — which you turn on if you want a flip to trigger an extra rebalance right away instead of waiting for the next scheduled one. 6. Select **Save condition**, or **Cancel** to close without saving. 7. Optional: repeat from step 1 and select **Add second condition**. Two conditions combine as "Any match → Risk-Off" — either one firing is enough. ## What you should see Your condition appears summarized on the **Risk** card — its instrument, indicator, and thresholds — with edit and remove actions next to it. A saved condition only changes what the strategy actually holds once its **Risk-Off** allocation is also set — see [What Risk-Off does to your allocation](/docs/strategies/risk-conditions#what-risk-off-does-to-your-allocation) and [How Risk-Off affects rebalancing](/docs/strategies/how-risk-off-affects-rebalancing) for how a flip reaches your holdings. Risk-Off profiles commonly hold a lower invested portion — more cash, less market exposure — see [Invested capital and cash reserve](/docs/strategies/invested-capital-and-cash-reserve#how-risk-conditions-can-lower-the-invested-portion). Take profit and stop loss are separate rules on the **Position exits** card, not part of a risk condition — see [Position exits](/docs/strategies/position-exits). Fincanva doesn't tell you which condition, indicator, or thresholds to set — see [Is this financial advice?](/docs/investing-theory/is-this-financial-advice#is-this-financial-advice). ## Common problems ### "Enter a value." A value the rule needs — the **Period** of a moving average or a percent change — was left empty. The value turns red in the sentence and the message stays under it; select the value and fill it in before selecting **Save condition**. An empty instrument reads "choose an instrument" in the sentence, with "Pick an instrument." under it. ### "Confirmation delay must be between 0 and 12 weeks." The **Confirmation delay (weeks)** field only accepts whole numbers from 0 to 12. Enter a value in that range — 0 acts immediately, 12 waits three months of confirmation before the strategy switches. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/starring-strategies-and-screeners # Starring strategies and screeners You mark a strategy or screener as a favourite by selecting its star; the **Favourites** filter then shows you only the items you've starred. ↗ See this in Fincanva — the Favourites filter on Strategies ## Before you start No prerequisites — you can favourite anything you can see, including your own strategies and screeners and any public ones you're browsing. To understand what a strategy is before you start starring them, see [What is a strategy?](/docs/strategies/what-is-a-strategy-in-fincanva). ## Steps 1. Find the strategy or screener — in its explorer sidebar row, in its dashboard table row, or on its own page — and select the star. 2. Selecting an unstarred star adds the item to your favourites; selecting a starred (yellow) star removes it. You can do the same from the row's ⋯ menu, which shows "Add to favourites" or "Remove from favourites" depending on the current state. 3. To see only your starred items, turn on the **Favourites** filter above the strategy or screener list. ## What you should see A favourited item's star stays filled yellow — the same yellow as the **Favourites** filter when it is on — visible even when you're not hovering the row. The one exception is a Live strategy's row in the sidebar library, which shows a green **Live** badge in the star's place. Turning on the **Favourites** filter narrows the list to your starred strategies or screeners only; if you haven't starred anything yet in that list, you see "No favourites yet". ## Why does a live strategy's star lock? Marking a strategy Live automatically adds it to your favourites and keeps it there for as long as the strategy stays live — you can't remove it from favourites while it's live. In the dashboard table and in the strategy page's header, its star locks yellow; in the sidebar library, its row shows a green **Live** badge in the star's place instead, and the sidebar's **Favourites** filter still includes it. Selecting the locked star, or otherwise trying to unfavourite a live strategy, shows "Turn the strategy off first"; turn the strategy off, then unstar it if you want to. Screeners have no Live state, so a screener's star never locks. ## How many favourites can I have? You can favourite up to 200 strategies and up to 200 screeners — the two lists are tracked and capped separately, so favouriting 200 screeners doesn't use up any of your strategy favourites. If a strategy is auto-favourited by going Live while you're already at the 200-strategy cap, it still goes live — it just isn't added to your favourites, rather than blocking the Live toggle. ## Common problems ### Why can't I unstar my live strategy? The strategy is currently Live, and Fincanva keeps a live strategy favourited so you don't lose track of it. Turn the strategy off first, then remove the star. ### Why won't a new favourite save? If you're already at the 200-item cap for that list — strategies or screeners — the app can't add another and shows "Couldn't save favourite". Remove an existing favourite from that list, then try again. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/step-by-step-and-all-at-once # Step by step and All at once **Step by step** and **All at once** are Fincanva's two editing views for one and the same strategy. [Step by step](/docs/getting-started/step-by-step) walks you through the strategy one decision at a time; [All at once](/docs/getting-started/all-at-once) puts its settings cards on a single page you can work through in any order. They are two views of one strategy, not two strategies: neither can set something the other cannot on the settings they share, and the view you used never changes what the strategy does or what its [backtest](/docs/getting-started/backtest) computes. On a saved strategy you move between them with one control on each side. ## How do you switch between Step by step and All at once? You switch with one control on each side, and the switch takes effect immediately: - **Step by step → All at once** — press **All at once** in the walk-through's header. - **All at once → Step by step** — press **Step by step** in the strategy's **Settings** header. Both controls move you between two views of the same open strategy, and both views read and write the same working copy, so nothing you have entered is discarded when you switch. What was unsaved before the switch is still unsaved after it — the switch is not a save. A new strategy always starts in **Step by step**: you pick its [strategy type](/docs/getting-started/strategy-type) in the **Create new** dialog, and the walk-through opens on the first step that type requires. **All at once** becomes reachable once the strategy is saved — from **Settings** on the strategy's page, or with **All at once** when you reopen it in **Step by step**. ## Which view should you use: Step by step or All at once? Use **Step by step** when you would rather be walked past every decision, and **All at once** when you already know which setting you want to change. The two differ in how much of the strategy is on screen at once — nothing else. {/* VISUAL: svg-diagram — one strategy drawn twice side by side: Step by step as a vertical step rail with a single step open, All at once as a grid of settings cards — tracked in VISUAL_BACKLOG */} | | Step by step | All at once | |---|---|---| | **What it shows** | One step at a time, each titled as a task — **Set up your strategy**, **Pick assets**, **Set risk conditions**, **Distribute capital**, **Define exit rules**, **Review & backtest** — with **Back** / **Continue** and a step counter. Only the steps the strategy type requires are on the rail. | The strategy's settings cards together on one page — **Strategy type**, **Rebalance**, **Asset selection**, **Allocation**, **Risk**, **Position exits** — each edited in place, in any order. | | **When to use it** | A first build, or any change where the order of the decisions is itself the help. | Changing settings you can already name, especially two or three unrelated ones: you edit them on one page, save once, and re-run once. | | **Where you land from** | Creating a strategy starts here; the **Step by step** control reopens a saved one in it. | **Settings** on the strategy's page, or **All at once** from inside the walk-through. | The full step rail is described in [Step by step](/docs/getting-started/step-by-step); what each card controls is described in [All at once](/docs/getting-started/all-at-once) and in [Editing a strategy: the settings cards](/docs/strategies/editing-a-strategy-the-settings-cards). ## Limits and edge cases - **A member strategy opened inside a Combined has no Step by step control** — it is edited in **All at once**. The [Combined](/docs/getting-started/combined) itself does have one, and its walk-through acts on the Combined: how often the Combined rebalances, which of your strategies it blends, how capital is split across them, and the recap. See [Which steps does a Combined walk?](/docs/getting-started/step-by-step#which-steps-does-a-combined-walk). - **Neither view shows every setting unconditionally.** A setting that is optional for the strategy type is offered under **Optional add-ons** on the **Review & backtest** step in **Step by step**, and as an **Add** chip in **All at once**; once you set it up it becomes a full step or a full card. - **A strategy that doesn't match its strategy type is gated.** In **Step by step** the gate blocks the step and states the fix: "Pick exactly 1 instrument." on a **Single instrument** strategy, "Pick 2 or more instruments." on **Multiple instruments**, "Add at least 1 screener." on **Screener**. Fix the selection, or take the dialog's **Change strategy type** action. In **All at once** the same requirement appears in the **Strategy type** card's confirmation, which lists what the new type requires before you confirm the switch. - **A Public strategy opens in either view but cannot be saved from it.** Save is disabled, and its tooltip reads: > Public strategies can't be saved. Use "Copy to Mine" to make an editable version. Make your own copy first and edit that — see [Mine / Public](/docs/getting-started/mine-public). ## Related To build a strategy from scratch, follow [Create a strategy](/docs/strategies/create-a-strategy-and-choose-its-instruments). To change one you already have, see [Editing a strategy: the settings cards](/docs/strategies/editing-a-strategy-the-settings-cards). To pick the shape that fits your idea, see [Choosing a strategy type](/docs/strategies/choosing-a-strategy-type). To save and re-run after an edit, see [Saving, running, and copying a strategy](/docs/strategies/saving-running-and-copying-a-strategy). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/what-is-a-strategy-in-fincanva # What is a strategy in Fincanva? A strategy in Fincanva is a saved set of instruments together with rules for how money is allocated across them and when positions change. A strategy is the unit you backtest, save in your library, and follow over time. ## What does a strategy contain? A strategy contains the instruments it trades plus the settings that govern how they're weighted and when they change. Each controls a different part: - **Asset selection** — the instruments the strategy trades, chosen as a basket you pick by hand or by attaching a screener that selects them for you. - **Allocation** — how capital is distributed across those instruments. - **Rebalance every** — how often the weights are refreshed. - **Risk** (optional) — conditions that switch the strategy to its Risk-Off allocation when they trigger. - **Position exits** (optional) — conditions that close a position. Together these settings define exactly what the strategy would have done over any historical period. ## Why build a strategy instead of picking instruments by hand? A strategy is reusable, testable, and modular, which a one-off hand-picked list of instruments is not. Because it is saved as a defined set of rules, you can backtest it over history to see how those same rules would have behaved, re-run it as new data arrives, and reuse it later without rebuilding it. It is also a building block for a combined strategy, covered in the next section. To start one, follow [Create a strategy](/docs/strategies/create-a-strategy-and-choose-its-instruments); to pick the shape that fits your idea, see [Choosing a strategy type](/docs/strategies/choosing-a-strategy-type). ## How is a strategy different from a combined strategy? A strategy holds instruments directly, while a combined strategy holds other strategies as its building blocks. Use a single strategy for one coherent idea; use a combined strategy to blend several strategies into one book. In the app the two are separated in the Strategies navigation under "Single" and "Combined". ## Limits and edge cases A strategy needs at least one instrument before it can be backtested or saved. If it selects instruments through a screener instead of a fixed basket, at least one screener must be attached; [Create a strategy](/docs/strategies/create-a-strategy-and-choose-its-instruments) covers the exact gate messages. There is no fixed upper limit on the number of instruments a strategy can hold today. ## Related To build one, follow [Create a strategy](/docs/strategies/create-a-strategy-and-choose-its-instruments). To choose the right shape, see [Choosing a strategy type](/docs/strategies/choosing-a-strategy-type). For a headline result metric a backtest reports, see [CAGR](/docs/analysis/cagr). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/when-risk-management-changes-a-strategy # When risk management changes a strategy Risk conditions change a strategy's behavior by switching it between two allocation profiles, and the levers you set — Confirmation delay, Auto-rebalance — change how quickly and how often that switch happens. ## How risk conditions change what a strategy holds A strategy with a Risk-Off allocation configured holds two allocation profiles instead of one — Risk-On and Risk-Off, each with its own method and its own invested portion — and runs one or the other depending on whether a risk condition is currently triggered. See [Risk conditions](/docs/strategies/risk-conditions) for what the two regimes are and [Set up a risk condition](/docs/strategies/set-up-a-risk-condition) for how you configure one. Fincanva doesn't tell you when to switch a strategy defensive or which condition to use — see [Is this financial advice?](/docs/investing-theory/is-this-financial-advice#is-this-financial-advice). ## What's the trade-off between reacting fast and whipsaw? A condition that flips easily reacts to a real regime change quickly, but the same sensitivity also makes it flip on brief, temporary moves that reverse soon after — each reversal is a whipsaw, and a flip that reverses switches the strategy's allocation and back again for no lasting benefit. A condition that's harder to trigger avoids most whipsaws but also reacts more slowly to a genuine regime change, staying in the wrong regime longer while it waits for confirmation. ## How does Confirmation delay change that trade-off? **Confirmation delay (weeks)** tunes the fast-reaction-versus-whipsaw trade-off by setting how long a flipped condition must hold before the strategy acts on it, from 0 to 12 weeks — its hint reads "0 = act immediately." At 0, the strategy switches the moment the condition flips, favoring responsiveness. A longer delay requires the flip to persist before it counts, filtering out brief flips at the cost of reacting later to a flip that turns out to be real. ## What's the cash drag when a strategy goes defensive? Cash drag is the market return a defensive strategy gives up because more of its capital sits in cash instead of being invested. Going Risk-Off commonly pairs with a lower invested portion on the Risk-Off allocation profile, so more of the strategy's capital sits in cash and less is exposed to the market — see [Invested capital and cash reserve](/docs/strategies/invested-capital-and-cash-reserve#how-risk-conditions-can-lower-the-invested-portion). Less market exposure means smaller swings in both directions: the strategy is shielded from further declines, but it also captures less of any recovery while it stays defensive. ## What's the trade-off with Auto-rebalance? **Auto-rebalance** (the toggle on a condition, note "Trigger a rebalance when the condition flips.") trades immediacy against staying on schedule: with it on, the regime switch reaches your holdings right away through an off-schedule rebalance; with it off, the switch waits for the next scheduled rebalance. See [How Risk-Off affects rebalancing](/docs/strategies/how-risk-off-affects-rebalancing) for the mechanics. ## Limits and edge cases Configuring the Risk-Off allocation identically to Risk-On makes the condition a no-op — the strategy still flips, but nothing about what it holds actually changes. Fincanva doesn't currently notify you when a condition flips — see [How you find out your strategy has gone Risk-Off](/docs/strategies/how-risk-off-affects-rebalancing#how-you-find-out-your-strategy-has-gone-risk-off). Position exits — take profit and stop loss — are a separate mechanism on their own card and don't interact with risk conditions; see [Position exits](/docs/strategies/position-exits). ## Related For what the two regimes are, read [Risk conditions](/docs/strategies/risk-conditions). To configure one, follow [Set up a risk condition](/docs/strategies/set-up-a-risk-condition). For how a flip reaches your allocation, see [How Risk-Off affects rebalancing](/docs/strategies/how-risk-off-affects-rebalancing). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/allocation-and-allocation-method # Allocation and allocation method Allocation is how a strategy divides the capital available to it among the things it holds, and the allocation method is the rule that decides each share. The method turns a list of candidates into a list of **weights** — one percentage per item — and those weights are what the backtest actually buys. Fincanva runs the same machinery at two levels: a [Combined](/docs/getting-started/combined) allocates across the strategies it holds, and each [strategy](/docs/getting-started/strategy) allocates across its own instruments. **Also seen as:** weighting, position sizing, capital split ## Why does allocation happen at two levels? Because a Combined and a strategy are allocating across different things, so each needs its own rule. The Combined level decides how much of the total capital each member strategy receives; the strategy level then decides how that strategy's slice is split across its own instruments. Which instruments those are comes from the strategy's [universe](/docs/getting-started/universe) — a hand-picked basket, or whatever a screener returns from its [seed universe](/docs/strategies/seed-universe). The two levels are independent layers: Fincanva applies both, one after the other, and never flattens them into a single list of instrument weights. You read a Combined's split across its strategies and each strategy's internal split as two separate answers. A standalone strategy only ever uses the strategy level. ## Which allocation methods can I choose? Every method in the table is available inside a strategy, across its instruments; the ones marked "yes" in the first column are also available to a Combined when it splits capital across its member strategies. | Method (as the app labels it) | Across strategies in a Combined | Across instruments in a strategy | |---|---|---| | [Equal Weights](/docs/strategies/equal-weights) | yes | yes | | [Fixed Allocation](/docs/strategies/fixed-weights) | yes | yes | | [Inverse Volatility](/docs/strategies/inverse-volatility) | yes | yes | | [Ranking-Based](/docs/strategies/ranking-based) | yes | yes | | [Risk Parity](/docs/strategies/risk-parity) | yes | yes | | [MPT (Markowitz)](/docs/strategies/modern-portfolio-theory) | yes | yes | | [Black-Litterman](/docs/strategies/black-litterman) | yes | yes | | [Maximum Diversification](/docs/strategies/maximum-diversification) | yes | yes | | [Minimum MAD](/docs/strategies/minimum-mad) | yes | yes | | [Minimum CVaR](/docs/strategies/minimum-cvar) | yes | yes | | [Scenario CVaR](/docs/strategies/minimum-cvar) | yes | yes | | [CDaR · Conditional drawdown](/docs/strategies/conditional-drawdown-at-risk) | yes | yes | | [EVaR · Entropic VaR](/docs/strategies/entropic-value-at-risk) | yes | yes | | [Robust worst case](/docs/strategies/robust-worst-case) | yes | yes | | [Stochastic programming](/docs/strategies/stochastic-programming) | yes | yes | | [Market Cap](/docs/strategies/market-cap-weighted) | no | yes | | [Min Correlation](/docs/strategies/min-correlation) | no | yes | | [Beta Neutral](/docs/strategies/beta-neutral) | no | yes | | [Mimicking](/docs/strategies/mimicking) | no | yes | | [Floating](/docs/strategies/floating) | no | yes | | [HRP · Hierarchical Risk Parity](/docs/strategies/hierarchical-risk-parity) | no | yes | | [HERC · Equal Risk per Group](/docs/strategies/hierarchical-equal-risk-contribution) | no | yes | | [NCO · Nested Clustered Optimization](/docs/strategies/nested-clustered-optimization) | no | yes | In prose: **Equal Weights, Fixed Allocation, Inverse Volatility, Ranking-Based, Risk Parity, MPT (Markowitz), Black-Litterman, Maximum Diversification, Minimum MAD, Minimum CVaR, Scenario CVaR, CDaR, EVaR, Robust worst case and Stochastic programming** work at both levels. **Market Cap, Min Correlation, Beta Neutral, Mimicking, Floating, HRP, HERC and NCO** work only inside a strategy, across its instruments — they are not offered when a Combined splits capital across its member strategies. Which methods your plan includes is stated on each method's page, and compared across plans in [what each plan includes](/docs/account-security/what-each-plan-includes). Each method page covers its own rule; which of them read history and which do not is set out in [Calculation window](/docs/strategies/calculation-window). How a Combined's split across its member strategies differs from a strategy's split across instruments is covered in [Combined weighting](/docs/strategies/combined-weighting). ## How does the method picker help you find a method? The picker ("Choose allocation method") lists every method at once and lets you narrow the list by what you want the method to do. Its **Filter by goal** chips start on **All**; each other chip keeps only the methods that serve that goal, and a method that serves two goals appears under both. | Goal (as the app labels it) | What the app says it means | Methods | |---|---|---| | **Simple rules** | "Weights set by a rule you can read at a glance." | Equal Weights, Market Cap, Ranking-Based, Fixed Allocation, Floating | | **Balance risk** | "No instrument or group dominates the portfolio's risk." | Risk Parity, Inverse Volatility, HRP, HERC | | **Diversify** | "Makes use of how differently the instruments move." | Min Correlation, Maximum Diversification, HRP, HERC, NCO | | **Limit losses** | "Looks at the worst days and periods, not at the average." | Minimum CVaR, CDaR, EVaR, Scenario CVaR, Robust worst case, Stochastic programming | | **Optimize** | "Looks for the best mix for a risk and return objective." | MPT (Markowitz), Black-Litterman, NCO, Minimum MAD, Stochastic programming | | **Follow a reference** | "Tracks or neutralises an index or an instrument." | Market Cap, Mimicking, Beta Neutral | In prose: the goals group the methods by intent — simple rules, balancing risk, diversifying, limiting losses, optimising, or following a reference — and a Combined's picker shows only the methods available at that level. Two more marks help you choose: - **Speed.** Methods that take noticeably longer to compute say so: Maximum Diversification, Minimum MAD, Minimum CVaR, Scenario CVaR, CDaR, EVaR and Robust worst case are marked "slow to compute", and Stochastic programming "very slow to compute". Every other method carries no mark. - **Plan.** A method your plan does not include stays in the list, tagged with the plan that includes it, rather than being hidden. ## Does a method I am not using still affect my results? No — only the method you have selected executes, and every other method's settings are inert. Each level holds one selected method at a time, and switching to a different method resets the previous method's own parameters: the picker warns "The current method’s specific parameters will be reset." before it applies the change. The one exception is moving between MPT (Markowitz) and [Black-Litterman](/docs/strategies/black-litterman): Black-Litterman is built on MPT and shares its settings, so they are kept and the picker shows no warning. Nothing a non-selected method was configured with reaches the backtest. ## What do all allocation methods have in common? Every method, at either level, shares the same three pieces of vocabulary. - **Weights.** A method's output is one weight per item, as a share of the capital being allocated. Weights are relative: you can enter raw numbers that do not add up to 100, and they are standardized so the allocated capital is fully used. A negative weight means a short position, which only the methods that support it can produce — see [Direction](/docs/strategies/direction-long-only-long-short-short-only). - **Rebalance interaction.** The method recomputes its weights at each [rebalance](/docs/backtesting/rebalance) date, and the strategy trades back to them. Between rebalance dates the weights drift with prices. [Floating](/docs/strategies/floating) is the deliberate exception: it lets weights drift and realigns them on its own schedule. - **Calculation window.** Methods that read history — volatility, correlation, beta, ranking — read it over a window the app calls **In-sample**, in months. Its hint reads: "Historical window used by the active method for volatility, correlation, beta, and similar calculations. Default 12." Equal Weights, Fixed Allocation, Market Cap, and Floating do not use it — see [Calculation window](/docs/strategies/calculation-window). - **Covariance matrix.** Methods built on an estimate of volatilities and correlations — Risk Parity, MPT, Maximum Diversification, and inside a strategy also HRP, HERC and NCO — carry a **Covariance matrix** choice that decides how that matrix is estimated — see [covariance matrix](/docs/strategies/covariance-matrix). Separately from the method, each level carries one dial for *how much* capital is put to work: [**Leverage**](/docs/backtesting/leverage) inside a strategy, and the [invested portion](/docs/backtesting/invested-portion) at the Combined level — see [Invested capital and the cash reserve](/docs/strategies/invested-capital-and-cash-reserve). ## How does Fincanva handle it? - **Equal Weights** is the starting method at both levels, so a new strategy or Combined splits capital evenly until you change it. - The In-sample calculation window defaults to **12 months**, and Leverage defaults to **1.00** — no leverage. - Each level holds an allocation profile per risk regime: **Risk-On**, used while no risk condition is firing, and **Risk-Off**, used while one is. A strategy with no [risk condition](/docs/strategies/risk-conditions) configured has only the one profile, and the app says so: "No Risk conditions configured — this allocation runs at all times." - Risk-On and Risk-Off each pick their own method, so a strategy can allocate one way normally and another way defensively. - With a single instrument there is nothing to divide: "With one instrument and no Risk-Off split, 100% of capital goes to that instrument." ## What does it look like in practice? A strategy holds four instruments — A, B, C, and D. Under **Equal Weights** the method returns 25% each, and the backtest buys a quarter of the strategy's capital in each. You switch the same strategy to **Fixed Allocation** and enter 40, 30, 20, 10; the method now returns 40% / 30% / 20% / 10%, so A gets four times what D gets. Same instruments, same dates, same rebalance cadence — only the allocation method changed, and the results differ because the capital was split differently. Now put that strategy into a Combined alongside two others and leave the Combined on Equal Weights. The Combined gives each of its three member strategies one third of the total capital; inside its third, our strategy still splits 40 / 30 / 20 / 10. Instrument A therefore ends up with 40% of one third — about 13.3% of the Combined's capital. That is the two levels, applied in order. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/auto-rebalance-on-flip # Auto-rebalance on flip Auto-rebalance on flip is the per-condition toggle that makes a strategy [rebalance](/docs/backtesting/rebalance) the moment a [risk condition](/docs/strategies/risk-condition) flips, instead of waiting for its next scheduled rebalance date. The control is labelled **Auto-rebalance** and carries the note "Trigger a rebalance when the condition flips."; a condition set this way is marked "Triggers rebalance" in the risk list. It decides *when* a switch reaches your holdings — never *what* it switches to. **Also seen as:** Auto-rebalance, Triggers rebalance, off-schedule rebalance ## What does Auto-rebalance change about a flip? It changes whether the flip is executed immediately or at the next scheduled rebalance. With **Auto-rebalance** on, the flip forces a rebalance the moment it happens, so the incoming allocation profile is applied off-schedule. With it off, the flip is recorded but the holdings do not change until the strategy's next scheduled rebalance, set by **Rebalance every** — until then the strategy keeps holding the outgoing profile's mix. The destination is identical in both cases: the strategy still ends up in the profile the condition asked for. Two settings therefore pace a flip in sequence. The [confirmation delay](/docs/strategies/confirmation-delay) decides whether the flip counts *yet*; Auto-rebalance then decides whether counting means an off-schedule rebalance or a wait for the scheduled one. ## How does Fincanva handle it? - Auto-rebalance is set per condition, not per strategy: each of a strategy's up-to-two risk conditions carries its own toggle. - Every built-in [risk template](/docs/strategies/risk-templates) arrives with Auto-rebalance off, so a flip rides the normal schedule unless you turn it on. - A rebalance forced this way is extra to the schedule — the **Next rebalance** date shown for a strategy is the scheduled one, and a risk-triggered rebalance can happen in between it and the previous one. - If the Risk-Off profile is configured identically to Risk-On, a forced rebalance has nothing to switch to and changes nothing. - Rebalancing off-schedule means trading off-schedule, so it carries the same costs the [simulation assumptions](/docs/backtesting/simulation-assumptions) apply to any other rebalance. ## What does it look like in practice? A strategy rebalances every 6 months. Its last rebalance was 1 March, so the next scheduled one is 1 September. On 10 May — four months into the cycle — its risk condition flips, with the **Confirmation delay (weeks)** at 0. With **Auto-rebalance** on, the strategy rebalances on 10 May: the incoming allocation profile is applied that day and the holdings change mid-cycle. With **Auto-rebalance** off, the flip is recorded on 10 May but nothing trades; the strategy carries the outgoing profile's holdings for nearly four more months and only switches on 1 September. Same condition, same thresholds, same destination — a four-month difference in when your holdings reflect it. Shorten the cadence to **Rebalance every** 1 month and the gap narrows to weeks, which is why the toggle matters most on long cadences. **Learn more:** [How Risk-Off affects rebalancing](/docs/strategies/how-risk-off-affects-rebalancing#how-a-risk-off-flip-can-force-an-off-schedule-rebalance) Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/average-momentum # Average momentum Average momentum is a smoothed trend reading: the average of an instrument's percent price change over 1 month, 3 months, 6 months and 12 months, in percent. It converts recent price history into a single signed number standing for how strongly, and in which direction, an instrument has been trending, so a rule can act on the trend rather than on the raw price level. Fincanva makes it available in two places — as one of the **Indicator** options on a [risk condition's](/docs/strategies/risk-condition) series, and as the ranking metric of the [Ranking-Based](/docs/strategies/ranking-based) [allocation method](/docs/strategies/allocation-and-allocation-method) — where it plays the same role in both. **Also seen as:** momentum, trend strength ## Where does average momentum appear in Fincanva? Average momentum appears on two different controls, and does the same job on both. | Where | Control | What it drives | |---|---|---| | Risk condition | "Average momentum", one of the four **Indicator** options on a series | the reading the condition's Risk-On and Risk-Off thresholds are compared against | | Ranking-Based allocation | "Average Momentum", one of the ranking metrics | the order instruments are ranked in — the app's own hint reads "Instruments are ranked by their average momentum — highest first." | The other **Indicator** options on a risk condition are "Raw price", [Simple moving average](/docs/strategies/simple-moving-average-sma), and [Percent change](/docs/strategies/percent-change). ## How is average momentum calculated? Average momentum is the plain average of four percent-change readings taken over four fixed spans — 1 month, 3 months, 6 months and 12 months — so one number carries the short-term and the year-long trend at the same time. $$ \text{average momentum} = \frac{c_{1} + c_{3} + c_{6} + c_{12}}{4} $$ where: $c_N$ is the [percent change](/docs/strategies/percent-change) of the instrument's adjusted closing price over the last $N$ months — its latest adjusted close measured against its adjusted close $N$ months earlier, expressed in percent. *Adjusted* means the price series is already corrected for [dividends and splits](/docs/analysis/dividends-and-splits), so a payout or a share split does not read as a price move. All four spans carry the same weight, which is what the "average" in the name refers to: no single horizon can dominate the reading. In words: measure how far the price has moved over the past month, the past three months, the past six months and the past year, then take the average of those four percentages. That is also why average momentum asks for no **Period** — the four spans are fixed, not chosen by you — and why it is smoother than a single percent change: three of the four spans are long, so one sharp month moves the average by only a quarter of its own size. ## Why does an instrument have no momentum reading at first? Because one of the four spans reaches back further than its history goes. If any one of the 1-, 3-, 6- or 12-month readings cannot be computed, that day is skipped entirely — average momentum produces no value rather than averaging the three spans that do exist. In practice that means the first year: nothing is ranked or compared on average momentum until the instrument has a full 12 months of prices behind it, because the 12-month span is the last of the four to become available. Once the history is long enough, a missing day inside it does not skip anything — a span that lands on a date with no bar reads the most recent bar before it, so holidays and suspensions are covered rather than blanking the reading. ## How do you read a high or low average momentum? A higher average momentum reading means a stronger recent uptrend in the series, and a lower one means a weaker trend or an outright downtrend. The reading is signed, so it can sit above or below zero: a positive number describes a series that is above where it stood across the four spans on average, a negative number one that is below, and a reading near zero a series with no clear direction either way. Fincanva's own preset copy reads it that way — the shipped TIPS [risk template](/docs/strategies/risk-templates) flips a strategy to Risk-Off "Risk-Off when momentum turns sharply negative", and the Ranking-Based hint ranks the highest readings first. Because three of the four spans are long, average momentum reacts to a turn later than a raw price move does. That is the usual trade-off of any smoothed trend measure: fewer reactions to one-off moves, and a later reaction to a real turn. This page describes how a reading is interpreted, not what to do about it. ## What does it look like in practice? An instrument closes today at 110 (adjusted). A month ago it closed at 105, three months ago at 100, six months ago at 95 and twelve months ago at 88. The four percent changes are +4.76%, +10.00%, +15.79% and +25.00%, so average momentum is (4.76 + 10.00 + 15.79 + 25.00) ÷ 4 = **+13.89%**. Now suppose the last month reversed hard and today's close is 96 instead. The four readings become −8.57%, −4.00%, +1.05% and +9.09%, and average momentum is **−0.61%** — barely negative, even though the instrument now sits 8.6% below where it stood a month ago, because two of the longer spans are still positive and each span carries a quarter of the weight. That damping is the point of averaging four horizons, and it is why the reading turns later than the price does. ## How does Fincanva handle it? - Average momentum takes no window input. When you pick it as a risk condition's **Indicator**, the **Period** field that Simple moving average and Percent change require is not shown, and any value already entered is cleared — the indicator carries its own four fixed spans rather than one you choose. - As a risk-condition indicator it only transforms the series being watched; the switch between the [Risk-On and Risk-Off](/docs/strategies/risk-on-and-risk-off) allocation is decided by that condition's [thresholds](/docs/strategies/condition-types). - As a Ranking-Based metric it decides the ranking order only. How many instruments that ranking ends up holding is capped separately by [max positions](/docs/strategies/max-positions). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/beta-neutral # Beta Neutral Beta Neutral is an [allocation method](/docs/strategies/allocation-and-allocation-method) that holds a long book and a short book at the same time, sized so that the strategy's overall [beta](/docs/analysis/beta) — its sensitivity to the benchmark it is measured against — lands on a target you set. A target of 0.00 means market-neutral: the long side's market sensitivity and the short side's cancel out, so the strategy's outcome depends on how its longs perform *relative to* its shorts rather than on the market's direction. **Also seen as:** market-neutral, beta-hedged book, beta hedging, long/short market-neutral ## How does a target beta of zero work? A portfolio's beta is the weighted sum of its holdings' betas, where a short position carries a negative weight. Setting a target beta means choosing weights whose weighted sum equals that target. $$ \beta_p = \sum_i w_i \beta_i $$ where: $\beta_p$ is the strategy's overall beta, $w_i$ is the weight of position *i* (positive for a long, negative for a short), and $\beta_i$ is that instrument's own beta against the chosen benchmark. Neutrality is the case $\beta_p = 0$. The part that surprises people is that **equal long and short exposure does not give a beta of zero.** Neutrality depends on the betas, not on the money: shorting the same amount you are long only cancels out if both sides have the same average beta. When the two sides have different betas, the two books have to be different sizes. ## What is beta measured against? Beta is measured against the **Benchmark instrument** you pick inside the method, not against a fixed market index. The app states it directly: "The portfolio's beta is computed against this instrument." Change that instrument and every beta in the calculation changes with it, along with what "neutral" means for the strategy. Selecting a benchmark instrument is required — with none chosen, the app shows the empty state "Select a benchmark instrument", with the note "Required for Beta Neutral". ## Which settings does Beta Neutral have? | Control | What you set | |---|---| | **Benchmark instrument** | the instrument beta is measured against (required) | | **Target beta** | the beta the finished strategy should have, from −2 to 2. "0.00 = market-neutral. Positive = net long exposure; negative = net short exposure." | | [**Adjusted beta**](/docs/analysis/adjusted-beta) | a switch, on by default, that pulls each beta estimate part of the way toward 1.0 before the books are sized. Turn it off and the method works from the raw fitted betas instead | | **Position side** | **Both**, **Long-only**, or **Short-only**. "Long-only and Short-only relax the neutral constraint to a single-sided book." | | **Positions** | how many positions the strategy holds at a time, from 2 to 100 — "Total long + short positions held at any time." | | **Ranking direction** | **Standard** or **Contrarian**. "Standard goes long the top-ranked instruments and short the bottom. Contrarian inverts." | | **Ranking metric** | the signal instruments are ranked by, chosen from Price Change, Average Momentum, Volatility, Sharpe Ratio, or P/E Ratio | | **Ranking window** | how far back the ranking metric reads, in months — "distinct from the Calculation window above, which controls the beta-estimation window" | The **Position side** control also appears elsewhere in the app under the shorter labels **Long**, **Both**, and **Short** — the same three choices, differently named. The ranking controls read the same five metrics [Ranking-Based](/docs/strategies/ranking-based) documents, and that page covers each one. **What Adjusted beta actually changes:** with the switch on, an instrument whose fitted beta is extreme is not taken at face value — it is pulled toward 1.0 before the books are sized, on the reasoning that an extreme estimate is usually part noise. A raw 1.8 is treated as something nearer 1.5; a raw 0.2 as something nearer 0.5. The effect on the allocation is that the two books come out closer in size than the raw estimates alone would make them, because the gap between the long side's average beta and the short side's has narrowed. Turn the switch off and the raw estimates are used as fitted, spread and all. [Adjusted beta](/docs/analysis/adjusted-beta) covers the adjustment itself, including its coefficients. ## Where can you use Beta Neutral? Beta Neutral is a **single-strategy method only**. It is offered inside a strategy and not inside a [Combined](/docs/getting-started/strategy-in-a-combined), because a Combined splits capital across whole strategies rather than building a long-and-short book of instruments. ## How does Fincanva handle it? - **Beta Neutral is included from the Advanced plan**; Free and Starter do not offer it. See [what each plan includes](/docs/account-security/what-each-plan-includes). - **Target beta** defaults to **0.00** (market-neutral) and accepts anything from −2 to 2. - **Position side** defaults to **Long-only**; **Positions** defaults to **10**; **Ranking direction** defaults to **Standard**. - **Ranking metric** defaults to **Price Change**, and the **Ranking window** to **12 months**. - Two separate windows are in play: the [calculation window](/docs/strategies/calculation-window) (**In-sample**) feeds the beta estimates, while the **Ranking window** feeds the ranking signal. Both default to 12 months and can be set independently. - There is no default benchmark instrument: you must choose one before the strategy will run. - The books are rebuilt at every [rebalance](/docs/backtesting/rebalance), because both the rankings and the beta estimates are re-read from the window ending at that date. ## What does it look like in practice? A strategy is set to hold 4 positions with a target beta of 0.00. Its two highest-ranked instruments have betas of 1.4 and 1.2, an average of **1.30**; its two lowest-ranked have betas of 0.5 and 0.4, an average of **0.65**. Equal books would not be neutral: 50% long at beta 1.30 and 50% short at beta 0.65 leaves a beta of (0.5 × 1.30) − (0.5 × 0.65) = **+0.325**, still meaningfully exposed to the market. Because the long side's average beta is twice the short side's, the short book has to be twice the size of the long book: - long book = one third of the exposure: (1/3) × 1.30 = 0.433 - short book = two thirds of the exposure: (2/3) × 0.65 = 0.433 - net beta = 0.433 − 0.433 = **0.00** The same arithmetic run with a target of +0.5 rather than 0.00 leaves a deliberate slice of market exposure in place, which is what a positive target beta means. ## What does a beta-neutral strategy still risk? Neutralising beta removes sensitivity to the chosen benchmark; it does not remove risk. The strategy still carries whatever is left after the market factor is stripped out — the relative performance of its longs against its shorts, the residual return [alpha](/docs/analysis/alpha) names — and shorting brings its own costs, since a short position accrues a borrowing charge whenever cost assumptions are switched on — see [Interest-rate markups](/docs/backtesting/interest-rate-markups). Beta is also an estimate from a historical window, so a strategy that was neutral on the estimation window will not be exactly neutral going forward. Fincanva describes how this method works; it does not recommend it or any target beta. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/black-litterman # Black-Litterman Black-Litterman is an allocation method built on Markowitz's [Modern Portfolio Theory](/docs/strategies/modern-portfolio-theory): it runs the same mean-variance optimisation, but replaces the expected returns — the plain historical averages, which are noisy and swing the weights around — with a steadier estimate that starts from an equilibrium and tilts it toward "views". In Fincanva the views are each instrument's momentum, computed for you at every rebalance, so you enter no forecast of your own. **Also seen as:** Black-Litterman model, BL, Bayesian mean-variance, momentum views The method picker lists it as **"Black-Litterman"**, right after MPT (Markowitz), and describes it as "Markowitz with corrected expected returns: a stable equilibrium tilted by momentum views". It is an [allocation method](/docs/strategies/allocation-and-allocation-method) offered both inside a single strategy and inside a [Combined](/docs/getting-started/strategy-in-a-combined). ## How does Black-Litterman correct the expected returns? Black-Litterman blends two estimates of each instrument's expected return — an equilibrium, which is stable, and a set of views — weighting each by how much it is trusted. In its textbook form the blended ("posterior") expected returns are: $$ \mu_{BL} = \left[(\tau\Sigma)^{-1} + P^{\top}\Omega^{-1}P\right]^{-1}\left[(\tau\Sigma)^{-1}\Pi + P^{\top}\Omega^{-1}Q\right] $$ where: $\Pi$ is the vector of equilibrium returns, $Q$ the returns the views expect, $P$ says which instruments each view is about, $\Omega$ is the uncertainty of the views, $\Sigma$ is the [covariance matrix](/docs/strategies/covariance-matrix) of the instruments and $\tau$ scales the uncertainty of the equilibrium. In words: the result is a weighted average of the equilibrium and the views, where the more certain a source is, the more it pulls the estimate toward itself. The optimiser then works on $\mu_{BL}$ exactly as MPT works on the historical averages. The app describes the method's momentum views as "Starts from a stable equilibrium and tilts it toward the instruments with momentum. The views are computed for you: you don't enter any forecast." The equilibrium it starts from is built from the instruments' risk, not from their market capitalisation. ## Which optimization targets can Black-Litterman aim at? Black-Litterman offers two of MPT's three targets: **Optimal** (the default) and **Max return**. The app describes them as "Optimal = best risk-adjusted return. Max return = highest expected return regardless of risk." **Min volatility** is not offered, because the lowest-risk portfolio is chosen from the covariance matrix alone and does not use expected returns — the one input Black-Litterman changes. On Min volatility it would make (almost) no difference, so the target stays with [MPT (Markowitz)](/docs/strategies/modern-portfolio-theory). ## What are the momentum views, and which settings control them? The views are each instrument's recent momentum measured against the others, recomputed at every [rebalance](/docs/backtesting/rebalance) from the data available on that date, so a backtest never uses information from after the date it is simulating. The **Momentum views** section of the method has two settings: - **Momentum months** — how far back momentum is measured; from 1 to 24, 12 by default. - **View confidence** — "Higher = momentum weighs more against the equilibrium." From 0.1 to 10, 1 by default. Momentum can reverse sharply, and a Black-Litterman tilt reverses with it: a higher view confidence makes the weights follow recent winners more closely, for better and for worse. ## How does Fincanva handle it? - **Black-Litterman is included wherever MPT is**: it has no plan level of its own, so any plan that includes MPT (Markowitz) includes it, at the strategy level and inside a Combined alike. See [what each plan includes](/docs/account-security/what-each-plan-includes). - **Optimization target** defaults to **Optimal**; **Max return** is the other choice. - **Momentum months** defaults to 12 and **View confidence** to 1. - **Every other setting is MPT's own** and behaves as described on [Modern Portfolio Theory](/docs/strategies/modern-portfolio-theory): position direction (strategy level only), weight limits, force diversification, the **Covariance matrix** choice and the **Resampled** option, with the plan levels stated there. With Resampled on, the Black-Litterman estimate is computed once and every resample reuses it. - **Moving between MPT (Markowitz) and Black-Litterman keeps your settings.** Choosing Black-Litterman on an MPT strategy keeps every MPT setting and moves a **Min volatility** target to **Optimal**; choosing MPT (Markowitz) again keeps them too and drops the momentum views. - **A strategy saved before Black-Litterman became its own method keeps running exactly as saved.** If it had the Black-Litterman switch on with the **Min volatility** target, it is now shown as MPT (Markowitz), because that combination uses (almost) no expected returns; the first time you edit its MPT settings, it is saved without the switch. - The [calculation window](/docs/strategies/calculation-window) (**In-sample**) supplies the risk and momentum inputs, and weights are recomputed at every rebalance, so a Black-Litterman weighting moves over the life of a backtest. ## What does it look like in practice? Take one instrument whose equilibrium return is 6% and whose momentum view says 12%. In the textbook blend, if the equilibrium and the view are trusted equally, the expected return used is halfway between them: (6% + 12%) / 2 = **9%**. If the view is trusted twice as much as the equilibrium, it counts twice: (6% + 2 × 12%) / 3 = **10%**. Plain MPT would have used the historical average of the window directly — which, after a strong run, can be far above either number and pile the portfolio into that one instrument. Black-Litterman's estimate moves toward momentum only as far as its confidence allows, which is why its weights change more gradually. The numbers here illustrate the textbook blend; they are not the exact figures Fincanva computes for a given confidence setting. Choosing the momentum months or the view confidence that made a past backtest look best is [overfitting](/docs/investing-theory/overfitting), and searching many combinations for that best one is [data snooping](/docs/investing-theory/data-snooping-bias). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/calculation-window # Calculation window The calculation window is how many months of past data an [allocation method](/docs/strategies/allocation-and-allocation-method) reads when it computes weights — the lookback that feeds its volatility, correlation, beta and ranking calculations at each [rebalance](/docs/backtesting/rebalance). It is a single number of months, set per allocation profile, and it bounds everything the method can see: history older than the window has no influence on the weights produced. In the strategy editor the field is labelled **In-sample**. **Also seen as:** In-sample, lookback, lookback window, in-sample period, estimation window ## What does the calculation window change? The calculation window changes the weights a method produces without changing the method itself, because it changes the span of history the method measures over. The app's own note reads: "Historical window used by the active method for volatility, correlation, beta, and similar calculations. Default 12." A short window makes the weights react quickly to recent conditions and shift noticeably from one rebalance to the next; a long window averages across more market regimes and produces steadier weights that respond slowly. Neither is more correct than the other — they answer different questions about the same instruments. The window is measured backwards from each rebalance date *inside* the backtest, not from today, so a method using a 12-month window at a rebalance in March 2015 reads 2014–2015 data, not recent data. ## Which allocation methods read the calculation window? | Reads the window | Ignores the window | |---|---| | Inverse Volatility · Risk Parity · [MPT (Markowitz)](/docs/strategies/modern-portfolio-theory) · [Min Correlation](/docs/strategies/min-correlation) · Mimicking · Beta Neutral · [Maximum Diversification](/docs/strategies/maximum-diversification) · [HRP](/docs/strategies/hierarchical-risk-parity) · [HERC](/docs/strategies/hierarchical-equal-risk-contribution) · [NCO](/docs/strategies/nested-clustered-optimization) · [Minimum MAD](/docs/strategies/minimum-mad) · [Minimum CVaR and Scenario CVaR](/docs/strategies/minimum-cvar) · [CDaR](/docs/strategies/conditional-drawdown-at-risk) · [EVaR](/docs/strategies/entropic-value-at-risk) · [Robust worst case](/docs/strategies/robust-worst-case) · [Stochastic programming](/docs/strategies/stochastic-programming) | [Equal Weights](/docs/strategies/equal-weights) · [Fixed Allocation](/docs/strategies/fixed-weights) · Floating · [Market Cap](/docs/strategies/market-cap-weighted) | [Ranking-Based](/docs/strategies/ranking-based) is the conditional case: it reads the window when its ranking metric is Price Change, Volatility or Sharpe Ratio, and ignores it for Average Momentum and P/E Ratio. When the active method does not read the window, the **In-sample** field is not displayed at all — there is nothing for it to set. ## How does Fincanva handle it? - The default is **12 months**. The field takes whole months with a minimum of 1 and no fixed ceiling; the unit shown beside it is "mo". - The window belongs to the allocation profile, so a strategy that has a Risk-Off allocation can read one window in Risk-On and a different one in Risk-Off. - [Beta Neutral](/docs/strategies/beta-neutral) carries a second, separate window — its **Ranking calculation window** — for the metric it ranks on, while the profile's calculation window controls its beta estimation. The app spells the split out: "How far back the ranking metric reads — distinct from the Calculation window above, which controls the beta-estimation window." - Changing the window changes a strategy's inputs, so the backtest has to be run again before the results reflect it. ## What does it look like in practice? A strategy holds five ETFs and uses [Inverse Volatility](/docs/strategies/inverse-volatility), which gives each holding a weight inversely proportional to its risk. With the calculation window at 6 months, the weights are set from the last six months of returns: an ETF that was turbulent through that half-year but calm before it measures as high-risk and receives a small weight. Change the window to 24 and that same turbulent half-year is averaged against eighteen quieter months, so its measured [volatility](/docs/analysis/volatility) falls and its weight rises. Same method, same five ETFs, same rebalance date — a different allocation, purely because the method was shown a different span of history. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/clustering # Clustering Clustering is a quantitative risk rule that sorts days into groups according to how one series has moved over a recent window — how much and in which direction — and switches the strategy to its Risk-Off allocation on every day that falls in the most volatile group. It gives no probability: each day either is in the turbulent group or is not. It is one of the three rules in the **Quantitative regimes** group of the risk condition builder, where the app describes it as "Groups days by how the market has moved recently. It decides yes or no, with no probability: if the day falls in the turbulent group, you move to Risk-Off." **Also seen as:** k-means clustering, regime clustering, k-means regimes ## How does a clustering rule decide which days are turbulent? A clustering rule describes each day by a small set of numbers measured over the observation window, then lets a k-means algorithm find the groups those days naturally form. Each day belongs to the group whose centre it sits closest to: $$ c(t) = \arg\min_{k}\; \lVert x_t - \mu_k \rVert \qquad\qquad \text{Risk-Off when}\quad c(t) = k_{\text{turbulent}} $$ where $x_t$ describes how much and in which direction the series moved over the window ending on day $t$, $\mu_k$ is the centre of group $k$, $c(t)$ is the group day $t$ is assigned to, and $k_{\text{turbulent}}$ is the group with the highest volatility. In words: the strategy runs Risk-Off on exactly the days that look most like the most volatile stretch of the series' history. ## How is clustering different from Hidden regimes (Markov)? Both rules learn regimes from one series, and they answer differently. [Hidden regimes (Markov)](/docs/strategies/hidden-regimes-markov) gives a probability and lets you set how sure it must be; Clustering gives a yes or no, so there is no threshold to set. Clustering also has no notion of how long a regime tends to last — each day is judged on its own window — so on a series that swings in and out of volatility it can switch more often, and the [confirmation delay](/docs/strategies/confirmation-delay) matters more. ## How does Fincanva handle it? - **The series** is any instrument you pick by selecting the instrument in the rule's sentence; a new rule starts on the S&P 500. There is no indicator, operator or pair of thresholds to set, unlike a Single series or Double series condition — see [condition types](/docs/strategies/condition-types). - **Observation window (trading days)** runs from 10 to 63, default 21; the app's note: "How many days to look at to describe each day. 21 ≈ 1 month." - **Number of regimes** is 2 or 3, default 2 ("How many groups of days the model looks for."). Whichever you pick, **only the most volatile group is Risk-Off**; with 3, the middle group stays Risk-On. - **The rule uses only history available on each day.** The groups are recalibrated as the backtest moves forward, and a day is never assigned using data from after it. - **It stays Risk-On until it has enough history to learn from**, and it stays Risk-On when the groups it finds are too alike in volatility to tell apart. - **One decision, no hysteresis.** The [confirmation delay](/docs/strategies/confirmation-delay) is the brake against [whipsaw](/docs/strategies/whipsaw); the app's hint on that field reads "This rule has a single threshold: the delay is your brake against switching too often. 0 = immediate." **Auto-rebalance** works as it does on any condition. - **Clustering is included from the Advanced plan**, at the strategy level and inside a Combined alike; Free and Starter do not offer it. See [what each plan includes](/docs/account-security/what-each-plan-includes). - In the list of risk conditions a saved rule shows "Clustering" with its series, "turbulent group" as its comparison, and its regime count and window, such as "2 regimes" and "21-day window". ## What does it look like in practice? You add a Clustering rule on a broad equity index with the default 21-day window and 2 regimes. Most days of the index's history sit in a calm group — small daily moves, drifting up — and a minority sit in a turbulent group of large moves, mostly down. For months each new day lands in the calm group and the strategy stays Risk-On. A sell-off starts: over three weeks the 21-day window fills with large down days, and on the day its description moves closer to the turbulent group's centre than to the calm one's, the rule asks for Risk-Off. When the window has rolled past the sell-off and new days land back in the calm group, it asks for Risk-On again. With a 10-day window the same sell-off would register sooner, and brief shocks would register too; with 63 days it would register later and hold longer. The figures are illustrative, not a suggested setting. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/combined-weighting # Combined weighting Combined weighting is how a Combined splits its capital across the strategies inside it — a layer of allocation that sits above, and is independent of, how each of those strategies weights its own instruments. The editor titles it **Combined allocation** and describes it as "How capital is split across strategies". **Also seen as:** Combined allocation, strategy-level allocation, multi-strategy weighting ## What are the two independent weighting layers? A Combined applies two allocation layers and never merges them into one. The Combined layer decides what share of capital each member strategy receives. Inside each member strategy, that strategy's own [allocation method](/docs/strategies/allocation-and-allocation-method) then decides how its share is spread across instruments. The layers do not interact: a member strategy keeps exactly the same internal weighting whether the Combined hands it 10% of capital or 40%, and changing a member's internal method leaves the Combined's split untouched. ## Which weighting schemes can a Combined use? A Combined can use every [allocation method](/docs/strategies/allocation-and-allocation-method) that the method table marks for a Combined: Equal Weights, Fixed Allocation, [Ranking-Based](/docs/strategies/ranking-based), [Inverse Volatility](/docs/strategies/inverse-volatility), [Risk Parity](/docs/strategies/risk-parity), [MPT (Markowitz)](/docs/strategies/modern-portfolio-theory), [Maximum Diversification](/docs/strategies/maximum-diversification), [Minimum MAD](/docs/strategies/minimum-mad), [Minimum CVaR and Scenario CVaR](/docs/strategies/minimum-cvar), [Conditional Drawdown at Risk](/docs/strategies/conditional-drawdown-at-risk), [Entropic Value at Risk](/docs/strategies/entropic-value-at-risk), [Robust worst case](/docs/strategies/robust-worst-case) and [Stochastic programming](/docs/strategies/stochastic-programming). The methods that exist only inside a single strategy are not offered at this level: [Floating](/docs/strategies/floating), [Market Cap](/docs/strategies/market-cap-weighted), [Min Correlation](/docs/strategies/min-correlation), [Mimicking](/docs/strategies/mimicking) and [Beta Neutral](/docs/strategies/beta-neutral), which weight instruments rather than strategies, and the three group-based methods — [Hierarchical Risk Parity](/docs/strategies/hierarchical-risk-parity), [Hierarchical Equal Risk Contribution](/docs/strategies/hierarchical-equal-risk-contribution) and [Nested Clustered Optimization](/docs/strategies/nested-clustered-optimization). Two of them produce the schemes people usually mean by "combined weighting": - [**Fixed Allocation**](/docs/strategies/fixed-weights) — you set a weight per strategy in the Strategies table and it stays there, whatever the strategies do. - **Ranking-Based** — the member strategies are ranked each period and paid by rank position, with fixed exceptions you nominate. This is the scheme that introduces strategy roles. ## What are strategy roles, static weight and rank weight? When a Combined uses Ranking-Based, every member strategy takes one of two roles, set per strategy in the Strategies table: - **static** — **Rotate** is off. The strategy is held every period at the fixed **Static weight** you gave it, regardless of how it ranks. - **rotating** — **Rotate** is on. The strategy joins the ranking pool, and its weight comes from where it ranks that period rather than from a fixed number. The editor summarises the split under the heading **Strategy roles** as "`{rotating}` rotating · `{staticCount}` static", with the note "Rotate and static weights are configured per strategy". The rotating strategies share one **Rotation weights** curve — a relative weight per rank position, labelled Rank 1, Rank 2 and so on, described as "Relative weight given to each rotating rank, top to bottom — any number from 0 to 999, decimals allowed." There is exactly one slot per rotating strategy: switch Rotate on for one more strategy and a slot is added, switch it off and a slot is removed. The weight a rotating strategy actually receives — its rank weight — is whichever slot matches its rank in that period, so the slots stay put while the strategies move between them. ## How does Fincanva handle it? - The Combined's default method is [**Equal Weights**](/docs/strategies/equal-weights): capital split evenly across the member strategies. - Under Ranking-Based, the Combined's ranking metric defaults to **Price Change**, and four metrics are offered — Price Change, Average Momentum, Volatility and Sharpe Ratio. **P/E Ratio is not available at this level**; it exists only inside a single strategy. - A newly added strategy starts **static** with a weight of 1, so a fresh Ranking-Based Combined has no rotating strategies and no rotation weights until you switch Rotate on. - Rotation weights are relative, exactly like the rank-tier weights inside a single strategy — they are normalised to 100% before capital is assigned. A newly opened slot starts at 1. - Every weight you type across a Combined — a Fixed Allocation weight, a Static weight or a rotation weight — accepts any number from 0 to 999, decimals included. A negative is not accepted: a Combined cannot be short one of its own strategies. - Switching Rotate on and back off keeps the Static weight you typed: while a strategy rotates its static weight is simply not used — nor checked against the 0 to 999 range, so a value you cannot see never stops a save — and it returns unchanged when rotation stops. - If the Combined's weights invest nothing — every Fixed Allocation weight at 0 or, under Ranking-Based, every static weight of a strategy that does not rotate and every rotation weight at 0 — the allocation invests nothing. It still saves, and the totals line reads "Invests nothing" in place of a number. The yellow "invests nothing" warning is raised the same way for the Combined's own selected allocation as for a single strategy's, and it clears as soon as any member strategy in use gets a non-zero weight. - Weighting belongs to the allocation profile, so a Combined that has a Risk-Off allocation can weight its strategies one way in Risk-On and another way in Risk-Off. - How the two layers are combined into the final positions is part of the engine and is not published; what is documented is that both layers apply and neither overrides the other. ## What does it look like in practice? A Combined holds three strategies — A, B and C — and rebalances monthly. Under **Equal Weights**, each receives a third of capital every period. Under **Fixed Allocation**, you type 50, 30 and 20, and those shares hold whatever the three strategies do. Under **Ranking-Based**, you mark A as static with a **Static weight** of 20 and switch **Rotate** on for B and C. That leaves two rotation slots: you give Rank 1 a weight of 60 and Rank 2 a weight of 20. The raw total is 100, so A is held at 20% every period, whichever of B and C ranks higher on the chosen metric takes 60%, and the other takes 20%. Next month the ranking flips: B and C swap slots, their weights swap with them, and A's 20% does not move. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/condition-types # Condition types Condition types are the shapes a [risk condition](/docs/strategies/risk-condition) can take, chosen from the builder's **Signal** menu. Two are built from a comparison you write, under **Custom**: "Single series" watches one instrument and compares its indicator against two thresholds you type, and "Double series" pits two instruments against each other with an **Operator** — the type decides whether the right-hand side of the comparison is a number or a second series. Three more, under **Quantitative regimes**, decide from a model instead of a comparison: [Hidden regimes (Markov)](/docs/strategies/hidden-regimes-markov), [Clustering](/docs/strategies/clustering) and, on a Combined only, [Strategy's own performance](/docs/strategies/strategy-s-own-performance). **Also seen as:** dual thresholds, hysteresis band, Double series ## What condition types are there? There are five, in two groups: the two **Custom** shapes differ only in what the watched series is measured against, and the three **Quantitative regimes** rules replace the comparison with a model whose settings are on each rule's own page. | Condition type | Group | What it is measured against | Values its sentence holds | |---|---|---|---| | **Single series** | Custom | two numbers you type | the instrument, its **Indicator** (with a **Period** where needed), then a **Risk-Off** comparison and a **Risk-On** comparison, each an operator and a number | | **Double series** | Custom | a second series | **Series 1**, an **Operator**, and a **Comparison series** — each series with its own instrument, Indicator and Period | | **[Hidden regimes (Markov)](/docs/strategies/hidden-regimes-markov)** | Quantitative regimes | a probability threshold on the turbulent state | **Instrument**, **Number of states**, **Probability threshold** | | **[Clustering](/docs/strategies/clustering)** | Quantitative regimes | membership of the most volatile group of days | **Instrument**, **Observation window (trading days)**, **Number of regimes** | | **[Strategy's own performance](/docs/strategies/strategy-s-own-performance)** | Quantitative regimes, Combined only | the Combined's own volatility, drawdown or trend | **Metric**, a window where the metric uses one, and a threshold | A **Double series** condition has no numeric thresholds at all: the comparison between the two series *is* the condition. Switching between the two Custom types swaps those fields in and out and keeps everything else you had set; switching to Hidden regimes (Markov) or Clustering keeps the instrument, the **Confirmation delay (weeks)** and **Auto-rebalance**, and drops the indicator, which those rules do not use. ## How does each condition type compare? The two Custom types run one comparison per reading of the watched series; the three quantitative rules each state their own test on their own page. $$ \text{Single series:}\quad s_t \;\square\; \theta \qquad\qquad \text{Double series:}\quad s^{(1)}_t \;\square\; s^{(2)}_t $$ where: $s_t$ is the value the chosen **Indicator** produces from the watched series at time $t$; $\square$ is the **Operator** — "is above" or "is below"; $\theta$ is a threshold you type, meaning $\theta_{\text{off}}$ in the Risk-Off comparison and $\theta_{\text{on}}$ in the Risk-On comparison; and $s^{(1)}_t$, $s^{(2)}_t$ are the two series' indicator readings, each configured independently. ## Why does a Single series condition have two thresholds instead of one? Because one line would make the strategy flip every time the series wobbled across it. With a single threshold, a series hovering right at that level crosses it repeatedly, and each crossing would swap the whole allocation profile — a lot of turnover for no lasting change in conditions, which is [whipsaw](/docs/strategies/whipsaw). Two thresholds separate the point where Risk-Off is requested from the point where Risk-On is requested, leaving a band between them where neither test is satisfied and nothing is asked for. That asymmetry is the point: because the return threshold sits on the far side of the entry threshold, the series has to travel a real distance back before the strategy is asked to return to Risk-On, rather than merely re-crossing the same line. Engineers call this **hysteresis** — the state depends on which threshold was crossed last, not on a single value. Fincanva exposes both thresholds and both operators; how the engine resolves a reading that sits inside the band is internal. The [confirmation delay](/docs/strategies/confirmation-delay) works on the same problem from the other direction: it adds patience in time, where the two thresholds add distance in value. ## What do Indicator and Period set? The **Indicator** sets how the series is transformed before the comparison, and the **Period** field under it sets how many periods that transformation covers. The four options are [Raw price](/docs/strategies/raw-price), [Simple moving average](/docs/strategies/simple-moving-average-sma), [Percent change](/docs/strategies/percent-change), and [Average momentum](/docs/strategies/average-momentum). In a **Double series** condition each side has its own Indicator, which is how a series is compared with a transformed version of itself. ## How does Fincanva handle it? - Thresholds accept values from −1000 to 1000; outside that the app reports "Risk threshold must be between -1000 and 1000." - A threshold is read in the same units as the indicator produces — an index level for a raw index, a percentage for a percent change, percentage points for a yield spread. - The **Operator** offers "is above" and "is below". Some built-in [risk templates](/docs/strategies/risk-templates) arrive with a crossing comparison instead, which the rule's sentence reads as "crosses above" or "crosses below" and the template's own description states — the S&P 500 one reads "Risk-Off when the S&P 500 crosses below its 200-day simple moving average." A crossing comparison reads the moment one series crosses the other, not simply sitting above or below it. - Fincanva does not publish each indicator's formula or its shipped default window — those are engine internals. - Fincanva does not suggest a threshold value, a series to watch, or a condition type to pick. See [Is this financial advice?](/docs/investing-theory/is-this-financial-advice#is-this-financial-advice). ## What does it look like in practice? Take a Single series condition on a market index you choose, with the **Indicator** set to "Percent change" and a **Period** of 6, so the condition reads the index's percent change over six months — the sentence says "6-month change". In the Risk-Off comparison you set the operator to "is below" and the value to −5%; in the Risk-On comparison, "is above" and 2%. Risk-Off is now requested when the six-period change drops below −5%, and Risk-On is requested only once it has climbed back above +2%. A reading of −1% satisfies neither test, so an index that fell 6% and then recovered to −1% is not yet asked back into Risk-On — it has to clear +2% first. Had you set both thresholds to 0 instead, an index oscillating around flat would ask for a switch at every crossing. The −5 and +2 here are illustrative numbers that show the asymmetry; they are not a suggested setting. **Learn more:** [Risk conditions](/docs/strategies/risk-conditions#how-the-risk-off-and-risk-on-thresholds-work) Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/conditional-drawdown-at-risk # Conditional Drawdown at Risk Conditional Drawdown at Risk (CDaR) is an [allocation method](/docs/strategies/allocation-and-allocation-method) that chooses the weights whose worst stretches below a previous peak are, on average, as shallow as possible. Instead of looking at single bad days, it follows the portfolio's path through the whole window, measures how far below its running high it sits on each day, and minimises the average of the deepest of those under-water readings. The method picker labels it **"CDaR · Conditional drawdown"** and describes it as "Reduces the longest and deepest stretches below the peak". **Also seen as:** CDaR, conditional drawdown, drawdown optimisation ## What does Conditional Drawdown at Risk minimise? It minimises the average of the worst share of [drawdowns](/docs/analysis/max-drawdown) along the path — the same idea as [Minimum CVaR](/docs/strategies/minimum-cvar), applied to under-water depth instead of daily loss: $$ \text{CDaR}_\alpha = \text{average of the worst } \alpha \text{ of } D_t, \qquad D_t = \max_{s \le t} V_s - V_t $$ where: $V_t$ is the portfolio's value on day $t$, $D_t$ is how far it sits below its highest value so far, and $\alpha$ is the **Tail share**. In words: every day the portfolio spends under water contributes its depth, and the method pushes down the average of the deepest 5%. Because a drawdown persists until the portfolio recovers, a mix that heals slowly racks up many deep readings, and one that bounces back within days racks up few — which is the difference variance cannot see. ## How does Fincanva handle it? - Conditional Drawdown at Risk is offered at **both levels**: across the instruments of a strategy, and across the strategies of a [Combined](/docs/getting-started/strategy-in-a-combined). - Its one setting is the **Tail share**, from 1% to 25% and 5% by default: the share of the path's days whose drawdown depth is averaged. - It reads the [calculation window](/docs/strategies/calculation-window) (**In-sample**, 12 months by default) and does not read the **Covariance matrix** choice. - When the window times the tail share comes to less than one day, the average becomes the single deepest day, and the app shows the same "Too little data for this tail share" warning as Minimum CVaR, offering to lengthen the in-sample period or switch to [Entropic Value at Risk](/docs/strategies/entropic-value-at-risk). - The drawdown path is measured on log returns, so its depths sit a hair away from the drawdowns of the compounded equity curve shown in the results. - The picker marks it "slow to compute": each [rebalance](/docs/backtesting/rebalance) solves an optimisation over the whole path. ## Which plan includes Conditional Drawdown at Risk? It depends on your plan, at each level where the method is offered. **Inside a strategy** Included from Ultimate upwards. See [what each plan includes](/docs/account-security/what-each-plan-includes). **Inside a Combined** Included from Ultimate upwards. See [what each plan includes](/docs/account-security/what-each-plan-includes). ## What does it look like in practice? Two mixes have the same volatility over a 12-month window of about 252 days, and both suffer the same −10% drop at some point. - **Mix A** recovers its peak within a week. Across the year it spends about 20 days under water, and only a handful of them deeper than −5%. - **Mix B** takes three months to recover. It spends about 70 days under water, dozens of them deeper than −5%. At a 5% tail share the method averages the deepest 252 × 5% ≈ 13 under-water readings. For A they include its short dip and some shallow ones; for B all 13 come from its long slump. B's average is far deeper, so Conditional Drawdown at Risk prefers A — while a variance-based method, seeing equal volatility, would call the two equal. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/confirmation-delay # Confirmation delay Confirmation delay is the number of weeks a [risk condition](/docs/strategies/risk-condition) waits after it flips before the strategy acts on it, so a brief move that reverses inside the window never changes the allocation. The field is labelled **Confirmation delay (weeks)** and its hint reads "0 = act immediately." The risk list shows a configured delay as "2-week delay", and the compact view as "confirm 2w". It buys patience: the longer the delay, the more short-lived signals are filtered out, and the later a genuine change is acted on. **Also seen as:** weeks delay ## What does the confirmation delay change? It changes *when* a flip is acted on, never *what* the flip does. A condition with a delay of 0 asks for the switch as soon as its comparison is satisfied; a condition with a delay of 2 requires the flip to stand for two weeks before the strategy acts. Once the delay has elapsed, the strategy switches to the profile the condition asked for, exactly as it would have at 0 — the destination is the same, only the timing moved. Whether "acting" then means an off-schedule rebalance or a wait for the next scheduled one is decided separately, by [Auto-rebalance on flip](/docs/strategies/auto-rebalance-on-flip). The delay also cuts both ways. It filters out the brief moves you did not want to react to, and it delays the lasting moves you did — it is the time-domain answer to [whipsaw](/docs/strategies/whipsaw), a trade-off covered in [When risk management changes a strategy](/docs/strategies/when-risk-management-changes-a-strategy#whats-the-trade-off-between-reacting-fast-and-whipsaw). ## How does Fincanva handle it? - The delay is a whole number of weeks from 0 to 12. Outside that range the app reports "Confirmation delay must be between 0 and 12 weeks." - 0 means act immediately, and every built-in [risk template](/docs/strategies/risk-templates) arrives with the delay at 0 — if you want patience you add it yourself. - The delay is set per condition, not per strategy: each of a strategy's up-to-two conditions carries its own value. - There is one delay per condition, covering the condition itself — not a separate delay for going Risk-Off and another for coming back. - The delay is counted in weeks regardless of the strategy's rebalance cadence, which is set in months by **Rebalance every**. ## What does it look like in practice? A condition watches an index and its **Confirmation delay (weeks)** is set to 2. On a Monday the index dips past the **Risk-Off** threshold; by Wednesday it has recovered above it. The two weeks never elapsed, so the strategy stayed in Risk-On the whole time and the condition generated no trade at all — the dip is invisible in the results. Now set that same condition's delay to 0. The Monday dip is enough to ask for Risk-Off, and Wednesday's recovery is enough to ask for Risk-On again, so a two-day wobble produces two switches of the allocation profile and the turnover that comes with them. The cost of the delay shows up in the other case: had the index kept falling instead of recovering, the 2-week setting would have put the strategy into Risk-Off two weeks later than the 0 setting would. **Learn more:** [How Risk-Off affects rebalancing](/docs/strategies/how-risk-off-affects-rebalancing#how-the-confirmation-delay-changes-when-risk-off-acts) Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/contracts # Contracts Contracts is the quantity of an instrument a position holds — its number of units, shares, or contracts — and **Max contracts** is the largest quantity that position held at any point in its life. It is a count of how much is held, not the money value of the holding. **Also seen as:** units, shares, quantity. ## What do Contracts and Max contracts measure? Contracts is a count of how much of one instrument is held: a position of 10 shares holds 10 contracts, regardless of the price. Max contracts is the peak of that count over the position's life — if a position was built up to 15 shares and later trimmed to 8, its Max contracts is 15: $$ \text{Max contracts} = \max_t q_t $$ where $q_t$ is the quantity held at time $t$. ## How does Fincanva handle it? - Contracts appears per trade in the **Trade history** table (Italian "Contratti"); Max contracts appears per position in the **Positions** table (Italian "Contratti max"). - The value is a count of units, shares, or contracts — distinct from the position's money value in the "Gross" and "Net" columns. - Distinct from **Max positions**, which caps how many different instruments are held at once, not the quantity of any single one. ## What does it look like in practice? A position opens with 10 shares. A later rebalance adds 5, taking it to 15, and a partial exit then sells 7, leaving 8. Its Contracts change trade by trade — 10, then 15, then 8 — while Max contracts records the high-water mark of 15, the most it ever held. *A quantity records what a simulation held on historical data, never a real order, and it is not a position size to take in any instrument.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/covariance-matrix # Covariance matrix The covariance matrix holds how much each instrument moves (its volatility) and how much each pair moves together (their correlation), and it is what methods such as [Risk Parity](/docs/strategies/risk-parity) and [MPT](/docs/strategies/modern-portfolio-theory) are built on. An [allocation method](/docs/strategies/allocation-and-allocation-method) estimates it from past returns, and the **Covariance matrix** setting chooses how: the app offers eight estimators, the classic **Sample** estimate and seven that correct it, either to reduce estimation noise or to react faster to changing markets. The control is labelled **Covariance matrix**, with the hint "The covariance matrix (volatilities and correlations) the method estimates from history." **Also seen as:** covariance estimator, covariance estimation, risk estimation, shrinkage estimator ## Why does the sample covariance matrix need correcting? The sample covariance matrix needs correcting because it is noisy when there are many instruments and not much history. With 30 instruments, the covariance matrix holds 465 separate numbers — 30 volatilities and 435 correlations — and a 12-month window gives about 252 days to estimate them from. Some correlations then come out unusually low by pure chance, and an optimiser will lean hard on exactly those. A corrected estimate pulls such accidents back toward something more plausible, which makes the weights steadier from one rebalance to the next. The price is a small, deliberate bias. ## Which estimators can you choose? The list names each one and says what it does, in the app's own words: | Estimator | What it does | |---|---| | **Sample** | "The classic estimate, with no corrections." | | **Ledoit-Wolf · identity** | "Reduces noise more firmly, treating every instrument the same way." | | **Ledoit-Wolf · constant correlation** (Recommended) | "Reduces noise by pulling correlations toward their average." | | **Exponentially weighted moving average (EWMA)** | "Gives more weight to recent days: reacts sooner when volatility changes." | | **Manual shrinkage** | "You choose how much to correct, from 0 to 1." | | **Marchenko-Pastur** | "Separates the signal from the noise and keeps only the signal." | | **Nonlinear Ledoit-Wolf** | "A tailored correction for each part of the estimate." | | **Regime-conditional (HMM)** | "Uses crisis correlations when the market is in crisis." | In prose: the first five are the basic estimators, and the last three sit in the list's **Advanced** group. - **Ledoit-Wolf** estimators blend the sample estimate with a simple target, and work out from the data how much to blend. The *identity* target treats every instrument alike; the *constant correlation* target keeps each instrument's own volatility and pulls every pairwise correlation toward the average one, which usually suits a basket of similar instruments such as stocks. It suits a deliberately mixed basket — stocks, bonds and gold together — less well, because there two very different levels of correlation are real. - **EWMA** weighs recent days more heavily, so the estimate follows a change in volatility within weeks instead of averaging it away over the whole window. It also reacts to noise, which can raise trading. - **Manual shrinkage** is the constant-correlation blend with the amount set by you rather than by the data. - **Marchenko-Pastur** uses random-matrix theory to tell which parts of the correlation structure are indistinguishable from noise, flattens those, and keeps the rest — such as the market-wide and sector-wide co-movement. It can discard weak structure that was real. - **Nonlinear Ledoit-Wolf** corrects each part of the estimate by its own amount rather than by one blend for everything. It helps most with large baskets and short windows, and adds almost nothing when history is long compared with the number of instruments. - **Regime-conditional (HMM)** estimates one covariance from calm periods and one from turbulent periods, and leans on the turbulent one when the market looks turbulent today, so the method sees crisis-level correlations while a crisis lasts. ## How do shrinkage and EWMA work? Shrinkage blends two estimates: $$ \hat{\Sigma} = \delta \, F + (1 - \delta) \, S $$ where: $S$ is the sample covariance, $F$ is the target (for constant correlation: every instrument keeps its own volatility, every pair gets the average correlation), and $\delta$ is the blend between 0 and 1. Ledoit-Wolf works $\delta$ out from the data; **Manual shrinkage** lets you set it as **Shrinkage intensity** — "0 = no correction, 1 = all correlations equal." EWMA updates each variance with a **Decay factor** $\lambda$: $$ \sigma^2_t = \lambda \, \sigma^2_{t-1} + (1 - \lambda) \, r^2_{t-1} $$ where: $\sigma^2_t$ is today's variance estimate, $r_{t-1}$ yesterday's return, and $\lambda$ how much of the old estimate survives each day — "The closer to 1, the more distant data counts." At the default 0.94 the estimate's memory is about 1 ÷ (1 − 0.94) ≈ 17 trading days. ## Which methods use the covariance matrix? Only the methods that are built on a covariance matrix show the **Covariance matrix** control; every other method ignores it. - **Inside a strategy:** [Risk Parity](/docs/strategies/risk-parity), [MPT (Markowitz)](/docs/strategies/modern-portfolio-theory), [Hierarchical Risk Parity](/docs/strategies/hierarchical-risk-parity), [Hierarchical Equal Risk Contribution](/docs/strategies/hierarchical-equal-risk-contribution), [Nested Clustered Optimization](/docs/strategies/nested-clustered-optimization) and [Maximum Diversification](/docs/strategies/maximum-diversification). - **Inside a Combined:** Risk Parity, MPT (Markowitz) and Maximum Diversification. The tail-focused methods — [Minimum CVaR](/docs/strategies/minimum-cvar), [Minimum MAD](/docs/strategies/minimum-mad), [Conditional Drawdown at Risk](/docs/strategies/conditional-drawdown-at-risk), [Entropic Value at Risk](/docs/strategies/entropic-value-at-risk), [Robust worst case](/docs/strategies/robust-worst-case) and [Stochastic programming](/docs/strategies/stochastic-programming) — work on the returns themselves and never show it. In MPT the choice affects the risk side only: expected returns are left to MPT itself — the plain averages of the window, or the Black-Litterman estimate when that option is on. ## How does Fincanva handle it? - **A method you choose now starts on Ledoit-Wolf · constant correlation**, the estimator the list marks **Recommended**. A strategy saved before this choice existed keeps **Sample**, so its results do not change by themselves. - The Risk-On and Risk-Off profiles each keep their own estimator. - **An instrument whose price stayed flat for the whole window has no measured risk, and most estimates leave it that way.** With Sample, Ledoit-Wolf · constant correlation, EWMA, Manual shrinkage, Marchenko-Pastur or Regime-conditional (HMM), such an instrument stops the backtest when the method is [Hierarchical Risk Parity](/docs/strategies/hierarchical-risk-parity), [Hierarchical Equal Risk Contribution](/docs/strategies/hierarchical-equal-risk-contribution), [Nested Clustered Optimization](/docs/strategies/nested-clustered-optimization) or [Maximum Diversification](/docs/strategies/maximum-diversification). Ledoit-Wolf · identity and Nonlinear Ledoit-Wolf give it a small positive risk instead, so the backtest runs — Nonlinear Ledoit-Wolf only once the window holds about 30 trading days, below which it behaves as Sample. - The estimate is taken over the [calculation window](/docs/strategies/calculation-window) (**In-sample**), so the window and the estimator work together. - **Decay factor** (EWMA only) accepts 0.90 to 0.99 and starts at 0.94. - **Shrinkage intensity** (Manual shrinkage only) is required and accepts 0 to 1. - **Two advanced estimators need enough history, and quietly fall back to Sample without it.** Regime-conditional (HMM) needs about 126 trading days — an in-sample period of at least 6 months — and also falls back when calm and turbulent periods cannot be told apart. Nonlinear Ledoit-Wolf needs about 30 trading days, so at least 2 months. When the window is too short the app warns: "With this history the estimate has no effect", with an action to lengthen the in-sample period. ## Which plan includes the advanced estimators? - **The five basic estimators come with the method.** Any plan that includes a method which reads the covariance matrix includes Sample, both Ledoit-Wolf estimators, EWMA and Manual shrinkage with it — see each method's page for the plan that includes it. - **Marchenko-Pastur, Nonlinear Ledoit-Wolf and Regime-conditional (HMM) start at Ultimate.** On Free, Starter and Advanced they stay in the list, tagged with the plan that includes them; choosing one opens a dialog naming that plan and leaves the current estimator in place. Ultimate and Professional allow them. See [what each plan includes](/docs/account-security/what-each-plan-includes). ## What does it look like in practice? A strategy holds 25 stocks on a 12-month window. Most pairs show a correlation around 0.5, but the sample estimate puts one pair at 0.05 — very likely an accident of this particular year. - **Sample** keeps the 0.05, and MPT leans on that pair as if it were a near-perfect diversifier. - **Manual shrinkage at 0.4** moves it to 0.6 × 0.05 + 0.4 × 0.5 = **0.23**: still below the crowd, but no longer an outlier worth betting the portfolio on. Every other pair moves toward 0.5 in the same proportion, and each stock's own volatility is left as measured. - **Ledoit-Wolf · constant correlation** does the same blend but picks the amount from the data — more when the estimate is noisier, for example with more stocks or a shorter window. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/direction-long-only-long-short-short-only # Direction: Long-only, Long + Short, Short-only Direction is whether an [allocation method](/docs/strategies/allocation-and-allocation-method) may hold only long positions, both long and short positions, or only short positions. A **long** position is an instrument the strategy owns: it gains when the price rises. A **short** position is the mirror image: the strategy sells an instrument it does not own and gains when the price falls. Fincanva names the three settings **Long-only**, **Long + Short**, and **Short-only**, and expresses a short position as a negative weight in the allocation. **Also seen as:** Position direction, Position side, long/short, shorting *Fincanva describes how these settings behave; it never recommends holding short positions or tells you which direction to run.* ## What does going short mean? Going short means selling an instrument the strategy does not own, with the obligation to buy it back later. The instrument is borrowed, sold at today's price, and repurchased at whatever the price is when the position closes; the difference between the two prices is the result. A short position therefore gains when the price falls and loses when the price rises — the reverse of owning the instrument. Two consequences matter, and both are mechanical facts rather than opinions: - **The loss on a short position has no fixed ceiling.** A long position's worst case is bounded: the instrument can fall to zero and no further, so you can lose what you put in. A price can rise without any upper limit, so the amount a short position can lose is not capped in principle. This is why short exposure is never a default: a method goes short only when you choose a direction that allows it, or type a negative weight yourself. - **Shorting has a carrying cost.** Borrowing an instrument to sell it is charged at a rate above the reference rate — modelled in Fincanva as the short-rate markup, see [Interest-rate markups](/docs/backtesting/interest-rate-markups). That cost only enters the numbers when costs are switched on in the simulation assumptions; with costs off, the backtest shorts for free, which real markets do not. ## Which allocation methods offer a direction setting? Direction is a per-method setting, not one switch for the whole strategy — three allocation methods show a direction control, and each names it in its own words. | Method | Control | Choices | |---|---|---| | [MPT (Markowitz)](/docs/strategies/modern-portfolio-theory) | "Position direction" | "Long-only", "Long + Short" | | [Beta Neutral](/docs/strategies/beta-neutral) | "Position side" | "Both", "Long-only", "Short-only" | | [Inverse Volatility](/docs/strategies/inverse-volatility) | "Direction" | "Long-only", "Long + Short" | For **MPT (Markowitz)** the app states the rule exactly: "Long-only requires every weight ≥ 0. Long + Short allows negative weights (short positions)." For **Beta Neutral**, which is built around a long leg and a short leg, choosing a single side changes what the method is doing — the hint reads: "Long-only and Short-only relax the neutral constraint to a single-sided book." **Inverse Volatility** shows the same "Long-only" / "Long + Short" pair, but whether that choice reaches the backtest is not confirmed today: the evidence on the engine side conflicts, so Fincanva does not publish an effect for it yet. [Fixed Weights](/docs/strategies/fixed-weights) has no direction control, but inside a strategy it accepts weights from −999 to 999, and a negative weight you type is a short position in that instrument. [Ranking-Based](/docs/strategies/ranking-based) works the same way for its decile weights: inside a strategy each one accepts −999 to 999, and a negative decile is held short. Every other method allocates long only. The **Position side** control on Beta Neutral also appears elsewhere in the app under the shorter labels **Long**, **Both**, and **Short** — the same three choices, differently named. ## Does direction apply inside a Combined? No — direction lives inside a strategy, among its instruments. When a [Combined](/docs/getting-started/combined) splits capital across its member strategies, none of the six methods available at that level offers a direction control, and the split across member strategies is always positive: a Combined cannot be "short" one of its own strategies. If short exposure exists at all, it was created by a method inside one of those strategies. ## How does Fincanva handle it? - **Long-only** is the default for Beta Neutral, whose "Position side" starts on "Long-only". - **MPT (Markowitz) starts on "Long + Short"** at the strategy level, so shorting is allowed unless you switch it to "Long-only". At the Combined level MPT has no direction control and is positive-only by construction. - When MPT allows shorts, an instrument's weight may range from −1 to 1; restricted to "Long-only" the range is 0 to 1. - A negative weight is how a short position is expressed — its size is the weight's magnitude, its direction the sign. - Every weight you type inside a strategy — a Fixed Weights weight or a Ranking-Based decile weight — accepts −999 to 999 with decimals, so a negative number is a short; every weight you type across a Combined's member strategies accepts 0 to 999 only. - Short-position financing costs are modelled only when costs are switched on. ## What does it look like in practice? A strategy holds two instruments, A and B, and runs a method set to "Long + Short". The method returns a weight of +0.60 for A and −0.40 for B: 60% of the allocated capital is long A, and the equivalent of 40% is short B. Over the next period A rises 10% and B falls 10%. The long leg contributes 0.60 × (+10%) = +6%. The short leg gains when B falls, so it contributes (−0.40) × (−10%) = +4%. The strategy is up about 10% before costs. Now run the same period with B rising 10% instead. The short leg contributes (−0.40) × (+10%) = −4%, so it loses exactly what it would have gained. And if B had risen 50%, the short leg would have cost 20% — the loss scales with the price move, with no point at which it stops. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/entropic-value-at-risk # Entropic Value at Risk Entropic Value at Risk (EVaR) is an [allocation method](/docs/strategies/allocation-and-allocation-method) that minimises a measure of tail loss built from **every** day in the window, with each day weighted more heavily the worse its loss. It sits above [CVaR](/docs/strategies/minimum-cvar) at the same tail share — always at least as prudent — and, unlike CVaR, it does not collapse onto a single worst day when the window is short. The method picker labels it **"EVaR · Entropic VaR"** and describes it as "More prudent than CVaR, stable even with little history". **Also seen as:** EVaR, entropic VaR ## What is Entropic Value at Risk? EVaR is the tightest upper bound on the tail loss that can be built from the whole distribution of returns rather than from its worst days alone: $$ \text{EVaR}_\alpha(L) = \inf_{z > 0} \; z \,\ln\!\left( \frac{\mathbb{E}\left[e^{L/z}\right]}{\alpha} \right) $$ where: $L$ is the portfolio's daily loss, $\alpha$ is the **Tail share**, $\mathbb{E}[e^{L/z}]$ averages every day's loss after an exponential weighting that grows steeply with the size of the loss, and $z$ is the scale that makes the bound tightest. In words: large losses dominate the average without the ordinary days being thrown away, so the answer depends smoothly on the weights and never on one single observation. ## How is EVaR different from Minimum CVaR? Two differences, and both come from EVaR using every day. - **It is more prudent.** At the same tail share, a portfolio's EVaR is never below its CVaR, so the weights that minimise it come out more conservative. That is the purpose, not a side effect. - **It has no small-sample cliff.** [Minimum CVaR](/docs/strategies/minimum-cvar) averages the worst tail-share of days; when the window times the tail share falls below one day, it becomes a single-worst-day rule, and the app warns you. EVaR has no such limit, which is why that warning offers "Switch to EVaR" as one of its two fixes. ## How does Fincanva handle it? - Entropic Value at Risk is offered at **both levels**: across the instruments of a strategy, and across the strategies of a [Combined](/docs/getting-started/strategy-in-a-combined). - Its one setting is the **Tail share**, from 1% to 25% and 5% by default — the same control as Minimum CVaR. - It reads the [calculation window](/docs/strategies/calculation-window) (**In-sample**, 12 months by default) and does not read the **Covariance matrix** choice. - No low-data warning is ever shown for it, whatever the window and tail share. - Weights are never negative. - The picker marks it "slow to compute": each [rebalance](/docs/backtesting/rebalance) solves an optimisation over every day of the window. ## Which plan includes Entropic Value at Risk? It depends on your plan, at each level where the method is offered. **Inside a strategy** Included from Ultimate upwards. See [what each plan includes](/docs/account-security/what-each-plan-includes). **Inside a Combined** Included from Ultimate upwards. See [what each plan includes](/docs/account-security/what-each-plan-includes). ## What does it look like in practice? A strategy uses a 1-month in-sample window, about 21 trading days, with a 4% tail share. - **Minimum CVaR** would average the worst 21 × 4% = 0.84 days — less than one — so it can only look at the single worst day, and the app shows "Too little data for this tail share". - **Entropic Value at Risk** uses all 21 days, each weighted by how bad it was. The worst day still counts most, but the second- and third-worst days move the answer too, so a small change in the data does not flip the weights. Lengthen the window to 12 months, about 252 days, and both methods have enough data; EVaR then still reads a little more deeply into the tail than CVaR at the same 4%. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/equal-weights # Equal Weights Equal Weights is the [allocation method](/docs/strategies/allocation-and-allocation-method) that gives every item the same share of the capital being allocated. With N items, each receives 1/N — four instruments get 25% each, ten get 10% each. It has no parameters to set and reads no history, which makes it the simplest method in Fincanva and the starting method for every new strategy and Combined. The app describes it as: "Every instrument receives an equal weight." **Also seen as:** equal weighting, equally weighted, 1/N *Fincanva describes how this method behaves; it never recommends an allocation method or tells you which split to run.* ## How is an Equal Weights allocation calculated? Each item's weight is one divided by the number of items. $$ w_i = \frac{1}{N} $$ where $w_i$ is the weight given to item $i$ and $N$ is the number of items being allocated across — instruments, when a strategy allocates; member strategies, when a Combined allocates. Every weight is identical, and the weights add up to the whole capital being allocated. ## What counts as a good value? There is nothing to tune, so the question becomes what an equal split *does*: it spreads capital without any view on which item is more attractive, so no single holding dominates by construction. That evenness cuts both ways — a small, volatile holding carries the same capital as a large, stable one, so an equally weighted strategy can be more exposed to its smallest holdings than a size-based method would be. Read it alongside a risk measure such as [volatility](/docs/analysis/volatility) or [max drawdown](/docs/analysis/max-drawdown). ## How does Fincanva handle it? - Equal Weights is the method a new strategy and a new Combined start on, at both levels. - It has no parameters at all: the method's card carries no settings, because 1/N leaves nothing to choose. - It does not use the In-sample [calculation window](/docs/strategies/calculation-window), because it reads no price or fundamental history. - Weights are recomputed at every [rebalance](/docs/backtesting/rebalance) date, so holdings that drifted apart between rebalances are brought back to an even split. - It is available both across a strategy's instruments and across a [Combined's member strategies](/docs/getting-started/strategy-in-a-combined). ## What does it look like in practice? A strategy holds four instruments: AAPL, MSFT, JNJ, and KO. Under Equal Weights, N = 4, so each weight is 1 ÷ 4 = 0.25 — 25% each. On \$100,000 of strategy capital that is \$25,000 per instrument, regardless of company size, price, or past performance. Three months later AAPL has doubled and KO is flat, so the actual weights have drifted to roughly 40% / 20% / 20% / 20%. At the next rebalance date Equal Weights recomputes 1/4 again, and the strategy sells part of AAPL and tops up the rest to return to 25% each. A [Combined](/docs/getting-started/combined) holding three strategies works the same way: N = 3, so each strategy receives one third of the Combined's capital. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/execution-time # Execution time Execution time is the point within a trading bar at which a modelled trade fills — at the **Open**, **IntraBar**, or **Close** — which sets the price the simulation uses for that trade. A trading bar is one period's price range (its open, high, low, and close), and where in that range a fill lands changes the price recorded. **Also seen as:** fill time ## When does a modelled trade fill within a bar? A backtest records, for every trade, whether it filled at the bar's Open, somewhere IntraBar, or at the Close, because that choice fixes which price the trade books at. Rebalance-driven trades are modelled to fill at the **Open of the first trading day after the rebalance date**, if the needed exchanges are open — so most fills carry an Open execution time. Because the calculation uses the close but execution is assumed at the next open, the booked price can differ from the level that triggered the trade. ## How does Fincanva handle it? - Recorded per trade in the "Execution time" column of the **Trade history** table (Italian "Orario esecuzione"), next to the "Actual execution price". - Rebalance trades are modelled to fill at the Open of the first trading day after the rebalance date. - [Stop-loss](/docs/strategies/stop-loss) and [take-profit](/docs/strategies/take-profit) exits do not wait for the next Open: they fill on the bar that reached the threshold, IntraBar at that level — or at the Open when the bar opens already past it, which is the case where the booked price overshoots the threshold. - Open, IntraBar, and Close each map to a different bar price, so the execution time and the execution price move together. ## What does it look like in practice? The same trade fills very differently depending on its execution time. Take a stock whose bar runs from an Open of 100 to a Close of 104. Filled at the Open, the trade books at 100; filled at the Close, it books at 104. The execution time is what decides which of the two prices the backtest records as the Actual execution price for that trade. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/exit-reason # Exit reason Exit reason is the recorded cause of a position being closed — take profit, stop loss, max hold, a rebalance, an Exclude screener, bankruptcy, or the instrument's price history ending — shown in the "Reason" column of a backtest's trade history. There are seven reasons in all, and every closing trade carries exactly one, so you can tell why each position left the strategy. It is a record of what the simulation did, not a setting: [take profit](/docs/strategies/take-profit), [stop loss](/docs/strategies/stop-loss) and [max hold](/docs/strategies/max-hold-months) are the controls that decide *when* a position closes, while the exit reason tells you afterwards *which* of them closed it. **Also seen as:** close reason ## What are the exit reasons a backtest records? Each closing trade is tagged with the reason it happened, drawn from a fixed set of seven causes: - **Take profit** — the position reached its take-profit gain. - **Stop loss** — the position reached its stop-loss threshold. - **Max hold** — the position reached its maximum holding period (a time-based exit), acted on at a scheduled rebalance. - **Rebalance** — the position was closed as part of a normal rebalance, when the strategy reweighted and no longer held it (this used to be called a "rotation"). - **Exclude screener** — at a scheduled rebalance the instrument matched one of the strategy's [Exclude screeners](/docs/getting-started/screener-attach), so it was dropped. - **Price history ended** — the instrument's own price history ran out while the position was open, because it stopped trading. It is a property of that instrument, not of the backtest: a position still open on an instrument that is still trading when the backtest ends is not closed for this reason. - **Bankruptcy** — a [bankruptcy rule](/docs/backtesting/bankruptcy-rules) closed the position: the run, or the strategy inside a Combined, fell below 10% of its reference capital and everything it held was closed. The reasons do not share one clock. **Take profit** and **Stop loss** are checked on the position's own price bars, so either can close a position between two rebalances — see [execution time](/docs/strategies/execution-time#when-does-a-modelled-trade-fill-within-a-bar) for the price such a close books at. **Max hold** and **Exclude screener** act only at the strategy's scheduled rebalances, so a rebalance forced off schedule by a [risk condition](/docs/strategies/risk-condition) never produces either of them. ## How does Fincanva handle it? - Shown in the "Reason" column of the **Trade history** table (Italian "Motivo"). - Recorded per closing trade — one position can open and close more than once, and each close carries its own reason. - The reason is a record of what the simulation did; it is not a setting you edit. ## What does it look like in practice? Across one backtest, five positions close for five different reasons: a stock up +20% shows **Take profit**; one that fell to its stop level shows **Stop loss**; one dropped at a scheduled reweight shows **Rebalance**; one held to its month cap shows **Max hold**; and one whose company was taken private mid-test, so its prices stop, shows **Price history ended**. Reading the Reason column tells you at a glance which rule ended each position. *An exit reason records what a simulation did on historical data, not what a position will do, and no reason in the column is a suggestion to close or hold anything.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/fixed-weights # Fixed Weights Fixed Weights is the [allocation method](/docs/strategies/allocation-and-allocation-method) where you decide each share yourself instead of letting a rule compute it. You type one number per item, and those numbers are **relative**: they do not have to add up to 100, because Fincanva normalizes them to 100% before the backtest uses them. The app labels this method **Fixed Allocation** and describes it as: "Set a weight for each instrument manually." **Also seen as:** Fixed Allocation, manual weights, custom weights ## What happens if my weights do not add up to 100? Nothing breaks — the weights are rescaled so they do. Fincanva reads your numbers as proportions, divides each one by their total, and uses the result as the actual share of capital. The total is the sum of the weights' sizes, ignoring their sign, so a negative weight counts towards it the same way a positive one does. The app shows both figures while you type, as "Raw total 110 · normalized to 100%", so you can see the raw sum you entered and know it will be converted. The practical consequence is that only the *ratios* between your numbers matter. Entering 50, 30, 20 and entering 5, 3, 2 produce exactly the same allocation. Entering 40, 40, 40 is the same as Equal Weights across three items. ## Where do the weights apply? To whatever the level is allocating across. Inside a strategy you set one weight per instrument; inside a [Combined](/docs/getting-started/combined) you set one weight per member strategy. Fixed Weights is one of the six methods available at both levels, and the normalization works identically in both. Because the weights are attached to specific items, they follow your selection: add an instrument and it starts at the default weight, remove one and its weight leaves with it — the remaining numbers are then renormalized over the smaller set. ## Can a Fixed Weights weight be negative? Yes, inside a strategy: each instrument's weight can be anywhere from −999 to 999, decimals included, and a negative weight is a short position in that instrument. Its size is the weight's magnitude and its direction is the sign — the same convention the [Direction](/docs/strategies/direction-long-only-long-short-short-only) page describes for every method that can go short. There is no separate switch: typing a negative number is the choice. Negative weights normalize like any other. The total they are divided by is the sum of the sizes, so entering 50 for one instrument and −50 for another gives a raw total of 100 and an allocation of 50% long and 50% short. Inside a [Combined](/docs/getting-started/combined) the weights across member strategies stay between 0 and 999: a Combined cannot be short one of its own strategies. ## What happens if every weight is zero? A Fixed Weights allocation whose weights are all zero invests nothing: there is no total to normalize over, so no capital goes to any item. Fincanva lets you save it, because an all-cash allocation can be deliberate, but the app says so. The totals line reads "Raw total 0 · invests nothing" instead of "normalized to 100%", and inside a strategy a yellow warning appears — "This allocation invests nothing: every weight is zero, so no capital goes anywhere." — which you can accept like any other warning. **Clear all** produces exactly this state: it sets every weight to 0 rather than removing the weights. ## How does Fincanva handle it? - Every item starts at a weight of **1**, so an untouched Fixed Weights allocation is an even split — the same result as Equal Weights. - Weights accept decimals and are read as proportions, never as literal percentages. Inside a strategy each weight can range from −999 to 999; inside a Combined, from 0 to 999. A number outside that range is not changed for you — the field shows "Enter a weight between -999 and 999." (or 0 and 999) until you correct it. - The method reads no history, so it does not use the In-sample [calculation window](/docs/strategies/calculation-window). - The weights you set are targets, reapplied at each [rebalance](/docs/backtesting/rebalance) date: between rebalances the actual mix drifts with prices, then snaps back to your numbers. - Two shortcuts sit right above the weights they change — in the Instruments table inside a strategy, in the Strategies table inside a Combined: **Equal** sets every weight to 1, and **Clear all** sets every weight to 0. When a strategy splits into Risk-On and Risk-Off, each regime's weight column has its own pair, and it changes only that regime's weights. - Inside a strategy with picked instruments, the list of weights always matches the list of instruments: exactly one weight each. Adding an instrument gives it a weight of 1; removing one removes its weight. ## What does it look like in practice? A strategy holds three instruments and you enter 50, 30, 20. The raw total is 100, so the weights are used as they stand: 50% / 30% / 20%. On \$100,000 that is \$50,000, \$30,000, and \$20,000. Now change the middle number to 40, so you have entered 50, 40, 20. The raw total is 110, and the app reads "Raw total 110 · normalized to 100%". Each weight is divided by 110: 50 ÷ 110 = 45.5%, 40 ÷ 110 = 36.4%, 20 ÷ 110 = 18.2%. The first instrument's share fell from 50% to 45.5% even though you never touched its number — because the other numbers grew, and every share is measured against the total. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/floating # Floating Floating is an [allocation method](/docs/strategies/allocation-and-allocation-method) that lets a strategy's existing weights drift with the market instead of resetting them at every [rebalance](/docs/backtesting/rebalance), and realigns the whole strategy back to a base method only every so many months. The app's own one-liner is "Weights drift between rebalances and realign periodically". **Also seen as:** drift-and-realign weighting, let-winners-run weighting ## How does Floating differ from a normal rebalance? A normal rebalance snaps every holding back to its target weight on each scheduled date; Floating leaves the existing holdings where the market has moved them. Existing holdings are not reset between realignments — so a holding that has run keeps the larger share it earned rather than being trimmed back each period, and the relative weights between the existing holdings are preserved. A position the strategy opens between realignments is the other half of the rule: a **new** position is sized by the base method — the **Realignment method** you picked — while the existing holdings keep their drifted relative weights. Only a realignment resets everything: at that point every holding is put back on the base method's weights and the drift starts again from there. ## How is the Floating frequency counted? The Floating frequency is counted in **calendar months** since the last realignment — not in number of rebalances. Elapsed months are checked at the strategy's scheduled rebalance dates, so the rebalance that first falls on or after the frequency you set is the one that also realigns the strategy. With a frequency of 6, a monthly-rebalancing strategy realigns roughly twice a year and drifts freely in between; the other rebalances still happen, they simply do not reset the existing weights. Be aware that the field's own in-app hint and the unit suffix shown on its input currently describe the count differently, tying the unit to the strategy's rebalance cadence rather than to calendar months, so the two do not agree in the product today. ## How does Fincanva handle it? - **Floating is included from the Starter plan**; the Free plan does not offer it. See [what each plan includes](/docs/account-security/what-each-plan-includes). - **Realignment method** defaults to [**Equal Weights**](/docs/strategies/equal-weights); the alternative is [**Inverse Volatility**](/docs/strategies/inverse-volatility). The app's note reads "When realigning, redistribute equally across instruments OR weight by inverse volatility (less volatile instruments get more)." - **Frequency** defaults to **25** and accepts whole numbers from 1 to 25. - Floating is available inside a single strategy only. A Combined does not offer it when it splits capital across its member strategies. - The [calculation window](/docs/strategies/calculation-window) does not apply to Floating — the field is not shown for this method, because the drift itself reads no history. - Floating changes what a rebalance does to existing weights; it does not change how often rebalances happen. The rebalance cadence stays whatever the strategy's own **Rebalance every** setting says. ## What does it look like in practice? A strategy holds four instruments at 25% each, with Equal Weights as the realignment method and a Frequency of 12. Over the following year one holding doubles while the other three are flat. Its share drifts from 25% to about 40% (50 out of a total of 125) and the other three fall to roughly 20% each — the winner is left to run, where a monthly rebalance would have trimmed it back to 25% every month. Twelve calendar months after the last realignment, the next scheduled rebalance realigns the strategy: all four holdings go back to 25%, the accumulated drift is given up, and the cycle restarts. Set the Frequency to 25 instead and the same strategy drifts for over two years before anything is reset. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/hidden-regimes-markov # Hidden regimes (Markov) Hidden regimes (Markov) is a quantitative risk rule: a model learns from one series' returns when the market has been calm and when it has been turbulent, gives each day a probability of being in the turbulent state, and switches the strategy to its Risk-Off allocation while that probability is at or above a threshold you choose. It is one of the three rules in the **Quantitative regimes** group of the risk condition builder, where the app describes it as "A model learns on its own when the market is calm and when it is turbulent. It gives a probability: you choose the threshold." **Also seen as:** hidden Markov model, HMM, Markov regime switching, regime-switching model ## What is a hidden-regime model? A hidden-regime model assumes the market moves between a small number of states that you never observe directly — calm and turbulent — each with its own typical behaviour, and that it tends to stay in one state for a while before moving to another. The states are "hidden" because only the returns are visible; the model infers from them how likely each state is on a given day. Moving between states follows a Markov chain: tomorrow's state depends only on today's, which is where the name comes from. The rule asks for Risk-Off on day $t$ when $$ \Pr\left(S_t = \text{turbulent} \mid r_1, \dots, r_t\right) \;\ge\; q $$ where $S_t$ is the hidden state on day $t$, $r_1, \dots, r_t$ are the series' returns up to and including that day, and $q$ is the **Probability threshold**. In words: once the model judges the turbulent state at least $q$ likely, given everything seen so far, the strategy runs Risk-Off. ## What do the number of states and the probability threshold change? **Number of states** sets how many regimes the model looks for: 2 (the app labels it "2 · calm / turbulent") or 3. With 3 states the model also finds a middle regime, and only the most turbulent state counts towards Risk-Off — the app's note reads "With 3 states, only the most turbulent one counts." **Probability threshold** sets how sure the model must be. The app puts the trade-off in one line: "Risk-Off when the turbulent state is at least this likely. Higher: fewer false alarms, but it reacts later." A lower threshold switches earlier and more often; a higher one waits for stronger evidence and switches less. ## How does Fincanva handle it? - **The series** is any instrument you pick by selecting the instrument in the rule's sentence; a new rule starts on the S&P 500. The app's hint: "The model reads the returns of this series." There is no indicator, operator or pair of thresholds to set, unlike a Single series or Double series condition — see [condition types](/docs/strategies/condition-types). - **Number of states** is 2 or 3, default 2. **Probability threshold** runs from 50% to 95%, default 70%. - **The model uses only history available on each day.** It is recalibrated as the backtest moves forward, and a day's probability never draws on data from after that day. - **It stays Risk-On until it has enough history to learn from**, and it stays Risk-On when the history shows no clearly distinct calm and turbulent states. - **One threshold means no built-in hysteresis.** A Single series condition has separate thresholds to leave and re-enter Risk-On; this rule has one, so the [confirmation delay](/docs/strategies/confirmation-delay) is what damps [whipsaw](/docs/strategies/whipsaw). The app's hint on that field: "This rule has a single threshold: the delay is your brake against switching too often. 0 = immediate." **Auto-rebalance** works as it does on any condition. - **Hidden regimes (Markov) is included from the Advanced plan**, at the strategy level and inside a Combined alike; Free and Starter do not offer it. See [what each plan includes](/docs/account-security/what-each-plan-includes). - In the list of risk conditions a saved rule shows its short name, "Hidden regimes", with its series, its threshold as a comparison such as "≥ 70%", and its state count, such as "2 states". ## What does it look like in practice? You add a Hidden regimes (Markov) rule on the S&P 500 with 2 states, a probability threshold of 70% and a confirmation delay of 1 week. Through a quiet stretch the model puts the turbulent state at 10%–30%, so the strategy stays Risk-On. Returns then turn large and erratic, and the probability climbs to 55%, then 74%. At 74% the rule asks for Risk-Off; one week later, the reading still above 70%, the strategy switches to its Risk-Off allocation. A threshold of 90% on the same history would have waited longer, and might never have switched if the probability peaked at 85%. A threshold of 55% would have switched a step earlier — and would also have fired on more short bursts that faded. The numbers here are illustrative, not a suggested setting. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/hierarchical-equal-risk-contribution # Hierarchical Equal Risk Contribution Hierarchical Equal Risk Contribution is an [allocation method](/docs/strategies/allocation-and-allocation-method) that arranges the instruments into a family tree by how alike they move, then splits the capital along the tree's actual branches so that the two sides of every split contribute the same amount of risk. It is a close relative of [Hierarchical Risk Parity](/docs/strategies/hierarchical-risk-parity): the tree is built the same way, but the capital follows the groups the tree really found instead of cutting an ordered list in half. The method picker labels it **"HERC · Equal Risk per Group"** and describes it as "Like HRP, but follows the real groups and gives each the same risk". **Also seen as:** HERC, equal risk per group ## How does it differ from Hierarchical Risk Parity? Two things change, and both follow the groups more faithfully. - **Where the cut falls.** Hierarchical Risk Parity halves a list, so a cut can land in the middle of a real group. Hierarchical Equal Risk Contribution cuts where the tree branches: if 30 instruments split naturally into 22 cyclical stocks and 8 defensive ones, the first split is 22 against 8, not 15 against 15. - **How each split is shared.** Each side gets a share that makes the two sides' risk contributions equal, which for two sides means sharing in inverse proportion to their volatility: $$ w_{\text{left}} = \frac{1/\sigma_{\text{left}}}{1/\sigma_{\text{left}} + 1/\sigma_{\text{right}}} \qquad w_{\text{right}} = 1 - w_{\text{left}} $$ where: $\sigma_{\text{left}}$ and $\sigma_{\text{right}}$ are the [volatilities](/docs/analysis/volatility) of the two branches, and $w$ is each branch's share of the capital above it. Because $w \times \sigma$ comes out the same on both sides, each branch supplies an equal slice of the risk — the [Risk Parity](/docs/strategies/risk-parity) idea applied one split at a time. In universes where the instruments are only loosely correlated, the two methods give similar weights; the difference grows when strong groups exist. ## How does Fincanva handle it? - Hierarchical Equal Risk Contribution is offered **inside a single strategy only**, across its instruments; a Combined does not offer it. - It has no settings of its own. It reads the [calculation window](/docs/strategies/calculation-window) (**In-sample**, 12 months by default) and the **Covariance matrix** choice — see [covariance matrix](/docs/strategies/covariance-matrix). - Weights are never negative. - With most covariance estimators — including the recommended Ledoit-Wolf · constant correlation — every instrument must have moved in price at some point inside the window: an instrument whose price stayed flat for the whole window, such as a suspended listing, stops the backtest rather than receiving a weight. Two estimators are the exception; [covariance matrix](/docs/strategies/covariance-matrix) names them. - Weights are recomputed at every [rebalance](/docs/backtesting/rebalance) from the window ending on that date. ## Which plan includes Hierarchical Equal Risk Contribution? Included from Advanced upwards. See [what each plan includes](/docs/account-security/what-each-plan-includes). ## What does it look like in practice? Take the same four instruments as on the [Hierarchical Risk Parity](/docs/strategies/hierarchical-risk-parity) page: an equity pair with 20% volatility and a bond pair with 10%, each pair made of two funds of equal risk. - **First split, equities against bonds:** the equity branch receives (1 ÷ 0.20) ÷ (1 ÷ 0.20 + 1 ÷ 0.10) = 5 ÷ 15 = **33.3%**, and the bond branch **66.7%**. Check: 33.3% × 20% = 66.7% × 10% ≈ 6.7% — equal risk on both sides. - **Second split, inside each pair:** two funds of equal risk share their branch evenly, so each equity fund gets 16.7% and each bond fund 33.3%. The result is 16.7% / 16.7% / 33.3% / 33.3%. Hierarchical Risk Parity, splitting by variance instead of volatility, gave the same tree 10% / 10% / 40% / 40% — a heavier tilt toward the calmer branch. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/hierarchical-risk-parity # Hierarchical Risk Parity Hierarchical Risk Parity is an [allocation method](/docs/strategies/allocation-and-allocation-method) that first arranges the instruments into a family tree by how alike they move, lines them up so that relatives sit side by side, and then splits the capital by cutting that line in half again and again: at every cut, the two halves share capital in inverse proportion to their risk, so the calmer half receives more. Instruments that behave alike end up sharing one budget instead of each claiming its own, which diversifies the portfolio across groups rather than across names. The method picker labels it **"HRP · Hierarchical Risk Parity"** and describes it as "Groups similar instruments and splits the risk between the groups". **Also seen as:** HRP, hierarchical clustering allocation ## How does Hierarchical Risk Parity build the tree? The tree comes from correlation: two instruments whose returns move closely together sit on neighbouring branches, and groups of such instruments join into larger branches the less alike they are. Six utility stocks that rise and fall together form one branch; a bond fund that moves on its own sits far from them. The instruments are then reordered so that relatives are side by side, and the capital is split by halving that ordered list — first into two halves, then each half into two, and so on down to single instruments. The cut falls at the middle of the list, not necessarily where one group ends and the next begins; following the groups exactly is what [Hierarchical Equal Risk Contribution](/docs/strategies/hierarchical-equal-risk-contribution) does differently. At each split the capital is divided between the two halves in inverse proportion to their variance: $$ w_{\text{left}} = \frac{\sigma^2_{\text{right}}}{\sigma^2_{\text{left}} + \sigma^2_{\text{right}}} \qquad w_{\text{right}} = 1 - w_{\text{left}} $$ where: $\sigma^2_{\text{left}}$ and $\sigma^2_{\text{right}}$ are the variances (the squared [volatility](/docs/analysis/volatility)) of the two halves, and $w$ is the share of that branch's capital each half receives. In words: the riskier half gets the smaller share, and the split repeats inside each half until every instrument has its weight. ## Why use Hierarchical Risk Parity instead of MPT? Because it never has to invert the covariance matrix, which is where [MPT](/docs/strategies/modern-portfolio-theory) turns small estimation errors into extreme weights. With many instruments and a short history, MPT can load most of the capital onto the one instrument whose past correlation happened to look low; Hierarchical Risk Parity cannot, because it only ever compares two halves at a time. The trade-off is that its splits follow a rule rather than an optimisation, so it does not claim to find the best risk-and-return mix. ## How does Fincanva handle it? - Hierarchical Risk Parity is offered **inside a single strategy only**, across its instruments; a Combined does not offer it when it splits capital across strategies. - It has no settings of its own. It reads the [calculation window](/docs/strategies/calculation-window) (**In-sample**, 12 months by default) and the **Covariance matrix** choice, which decides how volatilities and correlations are estimated — see [covariance matrix](/docs/strategies/covariance-matrix). - Weights are never negative: every instrument receives a share of the capital, and none is held short. - With most covariance estimators — including the recommended Ledoit-Wolf · constant correlation — every instrument must have moved in price at some point inside the window: an instrument whose price stayed flat for the whole window, such as a suspended listing, stops the backtest rather than receiving a weight. Two estimators are the exception; [covariance matrix](/docs/strategies/covariance-matrix) names them. - Weights are recomputed at every [rebalance](/docs/backtesting/rebalance) from the window ending on that date. ## Which plan includes Hierarchical Risk Parity? Included from Advanced upwards. See [what each plan includes](/docs/account-security/what-each-plan-includes). ## What does it look like in practice? A strategy holds four instruments that fall into two pairs: two equity funds that move together, and two bond funds that move together. The equity pair, held as a pair, has a volatility of 20% (variance 0.04); the bond pair has 10% (variance 0.01). - **First split, equities against bonds:** the equity side receives 0.01 ÷ (0.04 + 0.01) = **20%** of the capital and the bond side **80%**. - **Second split, inside each pair:** the same rule shares each pair's slice between its two members by their own variances. With two equity funds of equal risk, each gets 10%; with two bond funds of equal risk, each gets 40%. The result is 10% / 10% / 40% / 40%. Compare [Equal Weights](/docs/strategies/equal-weights), which gives each 25% and so lets the equity pair supply most of the risk, and [Hierarchical Equal Risk Contribution](/docs/strategies/hierarchical-equal-risk-contribution), which splits the same tree by volatility rather than variance. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/inverse-volatility # Inverse Volatility Inverse Volatility is an [allocation method](/docs/strategies/allocation-and-allocation-method) that weights each instrument in inverse proportion to that instrument's own risk: the calmer the instrument, the larger its weight, and the more volatile the instrument, the smaller its weight. It looks at each instrument on its own — it does not consider how the instruments move together, which is what [Min Correlation](/docs/strategies/min-correlation) and [Risk Parity](/docs/strategies/risk-parity) do. **Also seen as:** inverse-variance weighting, volatility-weighted allocation, inverse-volatility weighting, 1/σ weighting ## How does Inverse Volatility set weights? Inverse Volatility gives every instrument a raw score of one divided by its risk, then rescales those scores so the weights add up to 100%. $$ w_i = \frac{1 / \sigma_i}{\sum_{j} 1 / \sigma_j} $$ where: $w_i$ is the weight of instrument *i*, $\sigma_i$ is instrument *i*'s risk over the historical window, and the sum in the denominator runs over every instrument in the strategy, so the weights always total 100%. ## Which risk measure does Inverse Volatility use? The **Risk measure** control decides what "risk" means for this method, and the app describes the two options exactly like this: "Annualized volatility = how much the price fluctuates · Max drawdown = its worst historical loss". | Risk measure | What it reads | Effect on weights | |---|---|---| | **Annualized volatility** (default) | each instrument's [annualised standard deviation of returns](/docs/analysis/volatility) | instruments whose price fluctuates less get more weight | | **Max drawdown** | each instrument's largest [peak-to-trough decline](/docs/analysis/max-drawdown) | instruments whose worst historical fall was smaller get more weight | Both measures are read over the [calculation window](/docs/strategies/calculation-window) — the field labelled **In-sample** in the strategy editor — which sets how many months of history the risk figures cover. What changes when you switch between them is covered in [risk measure selection](/docs/strategies/risk-measure-selection). ## Where can you use Inverse Volatility? Inverse Volatility is available at both levels. Inside a single strategy it weights the [instruments](/docs/getting-started/instrument) the strategy holds; inside a [Combined](/docs/getting-started/strategy-in-a-combined) it splits capital across the strategies the Combined contains. A **[Direction](/docs/strategies/direction-long-only-long-short-short-only)** control (Long-only or Long + Short) appears only at the strategy level — a Combined's split across its member strategies is always positive. ## How does Fincanva handle it? - **Inverse Volatility is included from the Starter plan**, at the strategy level and inside a Combined alike; the Free plan does not offer it in either place. See [what each plan includes](/docs/account-security/what-each-plan-includes). - **Risk measure** defaults to **Annualized volatility**; **Max drawdown** is the alternative. - The calculation window (**In-sample**) defaults to **12 months** and accepts any whole number of months from 1 upward. - Weights are recomputed at every [rebalance](/docs/backtesting/rebalance), from the risk figures measured over the window ending at that date — so they change over the life of a backtest rather than staying fixed. - Inverse Volatility has no weight floor or ceiling: a very calm instrument can end up with a large share, and adding a highly volatile instrument barely moves the totals. ## What does it look like in practice? A strategy holds two instruments. Over the window, instrument A has an annualised volatility of 10% and instrument B of 30%. The raw scores are 1 ÷ 0.10 = 10 for A and 1 ÷ 0.30 = 3.33 for B, which total 13.33. Rescaling gives A a weight of 10 ÷ 13.33 = 75% and B a weight of 3.33 ÷ 13.33 = 25%. The calmer instrument ends up with three times the weight of the volatile one, purely because its volatility is three times smaller. ## How is Inverse Volatility different from Risk Parity? Inverse Volatility reads each instrument's risk in isolation, while [Risk Parity](/docs/strategies/risk-parity) equalises how much risk each instrument contributes to the finished portfolio, which depends on correlations as well as individual volatilities. The two coincide only in the special case where every instrument is uncorrelated with every other; as soon as some instruments move together, they produce different weights. Fincanva describes how these methods work; it does not recommend one. See [Is this financial advice?](/docs/investing-theory/is-this-financial-advice). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/market-cap-weighted # Market Cap Weighted Market Cap Weighted is the [allocation method](/docs/strategies/allocation-and-allocation-method) that sizes each instrument in proportion to its market capitalization — the total market value of a company's shares. A company worth ten times more than another receives ten times the weight, so the largest holdings dominate the allocation and the smallest barely register. It is the weighting convention most broad market indices use. The app labels it **Market Cap** and describes it as: "Instruments are weighted by market capitalization." **Also seen as:** Market Cap, cap weighted, capitalization weighting *Fincanva describes how this method behaves; it never recommends an allocation method or tells you which weighting to run.* ## How is a market-cap weight calculated? Each instrument's weight is its own market capitalization divided by the total market capitalization of all the instruments being allocated across. $$ w_i = \frac{\text{cap}_i}{\sum_{j=1}^{N} \text{cap}_j} $$ where the numerator is instrument $i$'s own market capitalization, the denominator is the sum of the capitalizations of all $N$ instruments in the allocation, and $w_i$ is the resulting weight. Because the weights are shares of a total, they always add up to the whole capital being allocated. ## What counts as a good value? There is nothing to configure, so what matters is the shape of the result: cap weighting concentrates capital in the largest holdings. A handful of very large companies can absorb most of the allocation while the rest of the list receives a fraction of a percent each, which means the strategy's outcome is driven mostly by those few names. That is a property of the method, not a fault — but it is why a cap-weighted allocation and an [equally weighted](/docs/strategies/equal-weights) one over the same instruments can behave very differently. Read the result alongside a concentration check, such as how much of the capital the top few weights hold. ## How does Fincanva handle it? - **Market Cap Weighted is included from the Starter plan**; the Free plan does not offer it. See [what each plan includes](/docs/account-security/what-each-plan-includes). - Market Cap Weighted has no parameters: the weights follow each instrument's market capitalization, so there is nothing to set. - It is available **only inside a strategy**, across its instruments. A [Combined](/docs/getting-started/combined) does not offer it when it splits capital across its member strategies. - It does not use the In-sample [calculation window](/docs/strategies/calculation-window): it reads current capitalizations rather than a window of history. - Weights are recomputed at each [rebalance](/docs/backtesting/rebalance) date, so as companies grow or shrink relative to each other their shares move with them. ## What does it look like in practice? A strategy holds two stocks. One has a market capitalization of \$500 billion; the other, \$50 billion — a 10:1 ratio. The total is \$550 billion, so the weights are 500 ÷ 550 = 90.9% and 50 ÷ 550 = 9.1%. On \$100,000 of strategy capital that is about \$90,900 in the large company and \$9,100 in the small one. Compare that with [Equal Weights](/docs/strategies/equal-weights) over the same two stocks, which would put \$50,000 in each. If the small company then doubles while the large one is flat, the equally weighted version gains roughly 50% and the cap-weighted version roughly 9% — the same two instruments, the same period, a different allocation method. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/max-hold-months # Max hold months Max hold months is a time-based exit that closes a position once the number of months you set has passed since it was opened — counted in **calendar months**, and acted on only at the strategy's **scheduled rebalances**, never on the position's month anniversary. It is a cap on how long any single position may stay in a strategy, regardless of whether the position is up or down. In the app the control is labelled **Max hold**, with the helper "Sell a position after holding it this long". **Also seen as:** Max hold, maximum holding period, hold cap. ## When does max hold actually close a position? Max hold closes a position at the first **scheduled** rebalance of the strategy at which the months you set have passed — never partway through a period, and never on a rebalance a [risk condition](/docs/strategies/risk-condition) forced off schedule. Two rules decide which rebalance that is: - **Months are calendar months.** The count is the number of calendar months between the month the position was opened and the month of the rebalance; the day of the month plays no part. A position opened in January has been held five months at any rebalance in June, whether June's rebalance falls on the 3rd or the 28th. - **Only scheduled rebalances act on it.** The check runs at the strategy's scheduled rebalance dates, and nowhere else. The practical consequence is that max hold is not an exact stopwatch: the position leaves at the scheduled rebalance in the month its time runs out, which can be a few days before or after the same calendar day N months on. Because the exit lands on a scheduled rebalance date, the value you enter has to line up with the rebalance clock: it must be a whole multiple of the strategy's rebalance interval, and the app blocks anything else with "Must be a multiple of `{rebalanceEvery}` months". That whole-multiples rule belongs to the rebalance cadence itself and is described in full under [rebalance](/docs/backtesting/rebalance). ## How does Fincanva handle it? - Off by default. When you switch it on, the value starts at the strategy's own rebalance interval — always a valid multiple — and you raise it from there. - Entered in months (the field's suffix reads "mo"), up to a maximum of 120 months; the field itself will not take a value outside that range. - The value must stay a whole multiple of the rebalance interval, so changing the cadence can leave a value you already set invalid — see [rebalance](/docs/backtesting/rebalance). - A position closed by this rule is recorded with the exit reason **Max hold** — see [exit reason](/docs/strategies/exit-reason) for the full list of causes a backtest records. - Max hold is one of the per-position exits, alongside [take profit](/docs/strategies/take-profit) and [stop loss](/docs/strategies/stop-loss). It looks only at elapsed time; it does not look at the position's gain or loss. - Only the strategy's scheduled rebalances act on it. Take profit and stop loss run on the position's own price bars and can close it between two rebalances; max hold cannot, and a rebalance forced off schedule by a risk condition does not close a position for max hold. ## What does it look like in practice? A strategy rebalances every month and has max hold set to **5** months. A position opened on the 12 January rebalance is 5 whole months old on 12 June, which is also a rebalance date, so it is closed there and its trade history shows the reason **Max hold**. Nothing happens at the February through May rebalances — the clock has not run out yet — and nothing happens between rebalances either. The calendar-month count shows up when the rebalance dates do not fall on the same day each month. Suppose the position opened at a rebalance on 28 January and June's scheduled rebalance falls on 3 June. January to June is five calendar months, so the position closes on 3 June — a few days short of five full months, because the day of the month is not counted. Had a [risk condition](/docs/strategies/risk-condition) forced an off-schedule rebalance on 28 June, it would not have closed the position there: an off-schedule rebalance does not act on max hold. Now raise the cadence to every 3 months: 5 is no longer a whole multiple of 3, so the app refuses it with "Must be a multiple of 3 months", and the nearest valid settings are 3 or 6 months. *Fincanva does not recommend a holding period, or whether to cap one at all.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/max-positions # Max positions Max positions caps how many instruments a strategy may hold at the same time, so a selection that qualifies twenty candidates still holds only as many as the cap allows. In the app the control is labelled **Max positions**, with the helper "Cap how many instruments are held at once". It is a concentration control rather than an exit rule: it decides the width of the portfolio at every rebalance, not when an individual position leaves. **Also seen as:** position cap, maximum positions, holdings limit. ## What happens when more instruments qualify than the cap allows? The cap is applied at each rebalance, and when the selection produces more candidates than the cap allows, the strategy's ranking — the ordering its [allocation method](/docs/strategies/allocation-and-allocation-method) works from — decides which of them are kept — the rest are simply not bought. A screener still reports every instrument it [matches](/docs/screeners/matches), and the cap then trims that set down to the number the strategy is allowed to hold. Max positions is not the only limit on that path, though: a [max-symbols cap](/docs/screeners/max-symbols-cap) can trim the match set to its most liquid names before the ranking ever sees it. So the cap changes what the strategy owns, not what its screener found. Two knock-on effects follow from that. A lower cap makes the strategy more concentrated and puts more weight on the ranking — explicit when the method is [Ranking-Based](/docs/strategies/ranking-based) — because a smaller number of survivors is decided by a finer cut of the same ordering. A higher cap spreads the same capital over more instruments and leans less on the ranking, because more of the qualifying set survives. Both are mechanical consequences of where the cut falls — neither is a recommendation. ## Is max positions a control when I pick the instruments myself? No — and this is the one place the cap is not something you set. When the selection is manual, Fincanva sets max positions to the number of instruments you picked, so the cap can never be the reason one of your own choices goes unheld. That covers a **Single instrument** strategy (one), a **Multiple instruments** strategy, and the **Basket** mode of a Full setup strategy. The field is not shown on those surfaces, because there is nothing left to decide: you already answered "how many?" by choosing them. It remains a real control everywhere the selection is by rule — the **Screen** mode, and **Compose**, where it sits with the other selection rules. Those are the modes where the number of qualifying instruments is not known in advance, which is exactly when a cap has something to do. ## How high can max positions go? As high as the lower of two ceilings: the 50 the field itself accepts, and what your plan allows. The field's own maximum is 50 on every account, and the plan allows 5 on Free, 10 on Starter, 25 on Advanced and 50 on Ultimate and Professional — so a Free account tops out at 5, a Starter one at 10, an Advanced one at 25, and Ultimate and Professional both top out at 50. The engine imposes no user-facing maximum of its own; both ceilings are Fincanva's, and the app resolves your plan's before it accepts the value, so the number the field lets you save is a statement about your own account. A strategy already holding more than its plan allows is not edited or deleted — it reads Set aside until the value comes down or the plan covers it, which is [plan compliance](/docs/backtesting/plan-compliance). ## How does Fincanva handle it? - **The highest cap your plan allows is 5 on Free, 10 on Starter, 25 on Advanced, and 50 on Ultimate and Professional.** The value in force is the lower of that and the 50 the field itself accepts, which is why Ultimate and Professional both show the same 50 here and no upgrade between them raises it further. See [what each plan includes](/docs/account-security/what-each-plan-includes). - Always on. Unlike the other per-position controls, max positions has no on/off switch — a strategy always carries a cap, which keeps its results bounded and comparable. - The value is a whole number of instruments, entered directly in the field — except on a manual selection, where Fincanva sets it to the number of instruments picked and shows no field. - The cap is per strategy. Inside a Combined, each member strategy carries its own cap, so the Combined can hold more instruments in total than any one of its members. - The cap is applied at each rebalance, so it constrains the target portfolio the strategy is aiming at, not just its first buy-in. - It is independent of the time-based controls: [max hold](/docs/strategies/max-hold-months) decides how long a position may stay, and [reinvest delay](/docs/strategies/reinvest-delay) how long a closed instrument stays out before it can be bought again, while max positions decides only how many slots there are. ## What does it look like in practice? A strategy's screener matches 14 instruments and max positions is set to **10**. At the rebalance the strategy ranks all 14, keeps the top 10, and holds those; the remaining 4 are matched but not bought, and they appear nowhere in the strategy's holdings. The eleventh-ranked instrument is the first one left out — it qualified on every filter and was excluded purely by the cap. Raise the cap to 14 and all of them are held, each at a smaller share of the same capital. Lower it to 5 and only the top five survive, so the strategy becomes markedly more concentrated and small changes in the ranking now change half its portfolio. *Fincanva does not recommend how many positions to hold — a wider or narrower cap is a mechanical consequence of where the cut falls, not a suggestion. See [Is this financial advice?](/docs/investing-theory/is-this-financial-advice#is-this-financial-advice).* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/maximum-diversification # Maximum Diversification Maximum Diversification is an [allocation method](/docs/strategies/allocation-and-allocation-method) that chooses the weights with the highest **diversification ratio**: the weighted average of the instruments' own volatilities divided by the volatility of the portfolio they form. The higher that ratio, the more the mix gains from its instruments not moving together, so the method leans toward the instruments that move most differently from the rest. The method picker labels it **"Maximum Diversification"** and describes it as "Favours the instruments that move most differently from the rest". **Also seen as:** most diversified portfolio, MDP ## What is the diversification ratio? The diversification ratio compares what the portfolio's risk would be if its instruments moved in perfect lockstep with what it actually is: $$ DR(w) = \frac{\sum_i w_i \, \sigma_i}{\sigma_p(w)} $$ where: $w_i$ is instrument *i*'s weight, $\sigma_i$ its own [volatility](/docs/analysis/volatility), and $\sigma_p(w)$ the volatility of the whole portfolio at those weights. The numerator is the risk of a mix with no diversification benefit at all; the denominator is the risk you really carry. A ratio of 1 means the instruments move together completely; the further above 1, the more diversification the mix is harvesting. It is a third answer next to two others: [MPT](/docs/strategies/modern-portfolio-theory) aims at the best risk-and-return trade-off, and [Risk Parity](/docs/strategies/risk-parity) equalises each instrument's share of the risk. Maximum Diversification asks only how much of the parts' risk disappears in the whole. ## How is it different from Min Correlation? Both reward instruments that move differently, but they aim at different targets: [Min Correlation](/docs/strategies/min-correlation) aims at the lowest overall correlation of the portfolio, while Maximum Diversification aims at the highest diversification ratio, in which each instrument's volatility sits directly. That makes it sensitive to how volatility is measured, which is why it also reads the **Covariance matrix** choice. ## How does Fincanva handle it? - Maximum Diversification is offered at **both levels**: across the instruments of a strategy, and across the strategies of a [Combined](/docs/getting-started/strategy-in-a-combined). - It has no settings of its own. It reads the [calculation window](/docs/strategies/calculation-window) (**In-sample**, 12 months by default) and the **Covariance matrix** choice — see [covariance matrix](/docs/strategies/covariance-matrix). - Weights are never negative. - With most covariance estimators — including the recommended Ledoit-Wolf · constant correlation — every instrument must have moved in price at some point inside the window: an instrument whose price stayed flat for the whole window, such as a suspended listing, stops the backtest rather than receiving a weight. Two estimators are the exception; [covariance matrix](/docs/strategies/covariance-matrix) names them. - The picker marks it "slow to compute": it solves an optimisation at every [rebalance](/docs/backtesting/rebalance). ## Which plan includes Maximum Diversification? It depends on your plan, at each level where the method is offered. **Inside a strategy** Included from Ultimate upwards. See [what each plan includes](/docs/account-security/what-each-plan-includes). **Inside a Combined** Included from Ultimate upwards. See [what each plan includes](/docs/account-security/what-each-plan-includes). ## What does it look like in practice? Three instruments all have 20% volatility. Two of them are near-twins, with a correlation of 0.9; the third moves independently of both. - **At Equal Weights (33.3% each)** the portfolio's volatility is 20% × √(0.533) ≈ 14.6%, so the diversification ratio is 20% ÷ 14.6% ≈ **1.37**. - **Maximum Diversification** instead holds about **25.6% / 25.6% / 48.7%**: the independent instrument gets nearly half, and the twins share the rest almost as if they were one instrument. The portfolio's volatility falls to about 14.0%, and the ratio rises to about **1.43**. The method did not look at returns at all — only at how much risk the mix sheds by combining instruments that do not move together. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/mimicking # Mimicking Mimicking is an [allocation method](/docs/strategies/allocation-and-allocation-method) that weights a strategy's own instruments so that the strategy's returns follow one chosen reference instrument as closely as possible — index replication built from your holding list rather than the index's. You pick the reference; the method works out the weights. **Also seen as:** index replication, index tracking, partial replication, tracking-portfolio weighting ## What does Mimicking actually track? Mimicking targets the reference instrument's **returns**, not its published list of constituents. As the app puts it, "The strategy's weights are computed so its returns track this instrument as closely as possible." The strategy therefore does not need to hold what the reference holds: it holds the instruments already in its own [universe](/docs/getting-started/universe), weighted so that the basket's return path stays as near the reference's path as those instruments allow. That is what makes it useful for replicating a broad index with ten or twenty holdings instead of hundreds. ## Why is the copy never exact? Replicating something with fewer holdings than it has always leaves a residual gap, because the strategy can only be assembled from the instruments in its universe. The gap tends to be wider when the universe is small, when its instruments behave differently from the reference's own components, and in periods when the reference's return is driven by parts of the market the strategy cannot hold at all. A wider universe generally follows the reference more closely; a shorter holding list is simpler and cheaper to trade but follows less tightly. That trade-off — closeness against holding count — is the whole decision Mimicking puts in front of you. Note that Fincanva's [tracking error](/docs/analysis/tracking-error) metric measures a different pair: a member strategy against its parent Combined, not a strategy against its Mimicking reference. It is not a readout of how well a Mimicking strategy is following its reference. ## How does Fincanva handle it? - **Mimicking is included from the Advanced plan**; Free and Starter do not offer it. See [what each plan includes](/docs/account-security/what-each-plan-includes). - Mimicking is available inside a single strategy only. A Combined does not offer it when it splits capital across its member strategies. - A **Reference instrument** is required — until one is chosen the app shows "Select a reference instrument" with the note "Required for Mimicking". - The reference is any single instrument in Fincanva's coverage, searched by ticker or name. It is commonly an index or an index ETF, but the picker is not restricted to indices. - Mimicking reads the [calculation window](/docs/strategies/calculation-window): the weights are fitted over that many months of history, and recomputed at each [rebalance](/docs/backtesting/rebalance) as new history arrives. - How the weights are computed is part of the engine and is not published. What the method promises to the user is the objective — follow the reference's returns as closely as this universe permits. ## What does it look like in practice? A strategy's universe holds ten large US stocks, and its reference instrument is a broad US index ETF. Mimicking sets those ten weights so the basket's return path stays as near the ETF's as ten names allow; it does not attempt to copy the index's hundreds of constituents. Through a stretch where the index is carried by sectors none of the ten stocks belong to, the basket lags the reference noticeably. Through a stretch where the ten move with the market, it follows closely. Swap the reference for a small-cap index and the same ten large-cap stocks track it far less well — not because the method changed, but because the instruments available cannot reproduce that reference's behaviour. *How closely a Mimicking strategy followed its reference on historical data is not how closely it will follow it ahead, and neither the method nor any reference instrument is a recommendation.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/min-correlation # Min Correlation Min Correlation is an [allocation method](/docs/strategies/allocation-and-allocation-method) that sets weights so the instruments in a strategy move together as little as possible: instruments whose returns are closely tied to the rest of the strategy get less weight, and instruments that behave differently from the rest get more. Where [Inverse Volatility](/docs/strategies/inverse-volatility) looks at each instrument on its own, Min Correlation looks at the relationships between them. **Also seen as:** minimum-correlation algorithm, MCA, minimum correlation weighting ## Why does low correlation matter? A portfolio's volatility depends on how its holdings move relative to each other, not only on how volatile each one is. Two instruments with identical individual volatility give a *less* volatile combination the less correlated they are — that is the whole mechanism behind diversification, and it is the correlation term in the [mean-variance volatility formula](/docs/strategies/modern-portfolio-theory#what-is-the-efficient-frontier). Concretely, for two instruments held at equal weight and with the same volatility σ, the combination's volatility is σ × √((1 + ρ) ÷ 2), where ρ is their correlation. At ρ = 1 the pair is no calmer than one instrument alone; the lower ρ falls, the more the pair's volatility drops below σ. ## Which settings does Min Correlation have? One — **Correlation matrix**, which chooses how the correlations the method weighs on are estimated. The weights themselves fall out of those correlations, so there is nothing else to set. The other input the method reads is the [calculation window](/docs/strategies/calculation-window) — the field labelled **In-sample** in the strategy editor — and that window is where the correlations are measured. ## Which correlation estimate does Min Correlation use? Min Correlation uses the **Sample** estimate unless you choose another under **Correlation matrix**, with the hint "How the method measures how closely the instruments move together." Pressing **Change** opens six choices, each described in the app's own words: | Choice | What it does | |---|---| | **Sample** (default) | "The historical estimate, computed on prices." | | **Pearson on returns** | "The classic correlation, computed on daily returns instead of prices." | | **Spearman (rank-based)** | "Compares the order of returns, not their size: extreme days weigh less." | | **Kendall (rank-based)** | "Counts how often two instruments rise and fall together: the most robust to extreme days." | | **Exponentially weighted moving average (EWMA)** | "Gives more weight to recent days: reacts sooner when correlations change." | | **Marchenko-Pastur** | "Separates the signal from the noise and keeps only the signal." | In prose: **Sample** correlates prices, the historical convention; the other five all work on daily returns. Correlating price levels picks up shared long-run trends as well as day-to-day co-movement, while correlating daily returns measures the day-to-day co-movement alone. - **Pearson on returns** is the textbook correlation coefficient, applied to daily returns. - **Spearman** and **Kendall** are rank correlations: they compare the order of returns rather than their size, so a handful of extreme days moves them less than it moves Pearson. - **EWMA** weighs recent days more heavily, so the estimate follows a change in correlations sooner instead of averaging it away over the whole window. It has no decay setting of its own here. - **Marchenko-Pastur** uses random-matrix theory to tell which parts of the correlation structure are indistinguishable from noise, and keeps the rest — the same idea as the Marchenko-Pastur option under [Covariance matrix](/docs/strategies/covariance-matrix), applied to the correlations Min Correlation weighs on. It sits in the list's **Advanced** group. None of the six choices has a setting of its own. ## Where can you use Min Correlation? Min Correlation is a **single-strategy method only**. It is offered inside a strategy and not inside a [Combined](/docs/getting-started/strategy-in-a-combined), so you cannot use it to split capital across the strategies a Combined contains. ## How does Fincanva handle it? - **Min Correlation is included from the Starter plan**; the Free plan does not offer it. See [what each plan includes](/docs/account-security/what-each-plan-includes). - **Correlation matrix starts on Sample**, for a method you choose now and for a strategy saved before the setting existed alike — so an existing strategy keeps running exactly as before. When the choice differs from Sample, a chip under the method names it: "Correlation: Pearson", "Correlation: Spearman", "Correlation: Kendall", "Correlation: EWMA" or "Correlation: Marchenko-Pastur". - **Marchenko-Pastur is included from the Ultimate plan**, the same step as the advanced [covariance matrix](/docs/strategies/covariance-matrix) estimators; the other five choices come with Min Correlation itself. On a lower plan Marchenko-Pastur stays in the list with the plan mark, and choosing it opens the plan dialog instead of switching. See [what each plan includes](/docs/account-security/what-each-plan-includes). - **The Correlation matrix setting is not the Combined's correlation matrix.** It changes only how Min Correlation estimates correlations inside a single strategy; the [correlation matrix](/docs/analysis/correlation-matrix) on a Combined's **Correlations** page is a separate analysis and is unaffected by it. - The calculation window (**In-sample**) defaults to **12 months** and accepts any whole number of months from 1 upward. Correlations are measured over that window. - Correlations are re-measured and weights recomputed at every [rebalance](/docs/backtesting/rebalance), so a min-correlation weighting shifts over the life of a backtest — and it can shift sharply, because correlations between the same instruments change over time — a [rolling correlation](/docs/analysis/rolling-correlation) is how that movement is read. - The method needs at least two instruments to have anything to correlate: with a single [instrument](/docs/getting-started/instrument) there are no relationships to minimise. ## What does it look like in practice? A strategy holds three instruments, each with 15% volatility. Their pairwise correlations over the window are: A with B, 0.85; A with C, 0.20; B with C, 0.35. Held at equal weight, a pair's volatility is 15% × √((1 + ρ) ÷ 2): | Pair | Correlation | Volatility of the equal-weight pair | |---|---|---| | A + B | 0.85 | 15% × √0.925 = **14.4%** | | B + C | 0.35 | 15% × √0.675 = **12.3%** | | A + C | 0.20 | 15% × √0.600 = **11.6%** | Every one of these pairs is built from instruments with exactly the same 15% volatility, yet the calmest pair is nearly three percentage points calmer than the most correlated one. Nothing about the individual instruments explains that difference — only the correlations do, and picking on that difference is what Min Correlation is for. Fincanva reports the same pair-by-pair reading for the strategies a Combined holds in its [correlation matrix](/docs/analysis/correlation-matrix). ## How is Min Correlation different from Risk Parity? Both methods take correlations into account, but they aim at different things. [Risk Parity](/docs/strategies/risk-parity) targets the *split* of risk — every instrument should supply an equal share of the portfolio's total risk. Min Correlation targets the *co-movement* itself, favouring the instruments that behave least like the rest of the strategy. A highly correlated instrument can still receive a substantial risk-parity weight; under Min Correlation it is the very thing being weighted down. Fincanva describes how these methods work; it does not recommend one. See [Is this financial advice?](/docs/investing-theory/is-this-financial-advice). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/minimum-cvar # Minimum CVaR Minimum CVaR is an [allocation method](/docs/strategies/allocation-and-allocation-method) that chooses the weights whose **average loss on the worst days** is as small as possible. It looks only at the bad tail of the returns — the worst 5% of days by default — and ignores how the portfolio behaves on ordinary or good days, so it tells apart two instruments that variance would treat as equally risky when one of them has rare, deep falls. The method picker labels it **"Minimum CVaR"** and describes it as "Reduces the average loss on the worst days". Its variant **Scenario CVaR** applies the same objective to generated possible futures instead of past days. **Also seen as:** mean-CVaR optimisation, minimum expected shortfall, CVaR minimisation ## What does Minimum CVaR minimise? It minimises the conditional value at risk (CVaR, also called expected shortfall): the average loss across the worst share of outcomes, where that share is the **Tail share** you set. $$ \text{CVaR}_\alpha = \mathbb{E}\left[\,L \mid L \ge \text{VaR}_\alpha\,\right] $$ where: $L$ is the portfolio's loss on one day, $\alpha$ is the tail share, and $\text{VaR}_\alpha$ is the loss that only the worst $\alpha$ of days reach. In words: line up every day of the [calculation window](/docs/strategies/calculation-window) from worst to best, keep the worst 5%, and average them — that average is what the method pushes down. Variance counts a +3% day and a −3% day as the same amount of risk. CVaR only ever counts losses, which is why two instruments with the same [volatility](/docs/analysis/volatility) can come out very differently. ## What is the tail share? The **Tail share** is the one setting Minimum CVaR has: "The worst share of days or scenarios over which the method measures the average loss." It runs from 1% to 25% and starts at 5%. A small share looks at the few most extreme days only, which makes the estimate noisy; a larger share averages over more days and is steadier, but looks less deep into the tail. ## What happens when the window is too short for the tail share? When the in-sample window times the tail share comes to less than one day, the average of the worst days becomes the single worst day, and the method quietly turns into a worst-day minimiser. The app warns before you run, with the message "Too little data for this tail share" and the arithmetic behind it — for a 1-month window at 4%: about 21 days × 4% = less than one day. The warning offers two fixes: lengthen the in-sample period, or switch to [Entropic Value at Risk](/docs/strategies/entropic-value-at-risk), which has no such limit because every day contributes to it ("Switch to EVaR"). ## What is Scenario CVaR? Scenario CVaR minimises the same average loss, but over **generated possible futures** instead of the days in the window. At each [rebalance](/docs/backtesting/rebalance) it builds a set of scenarios, each one a possible next period assembled from real days of the window, and minimises the average loss of the worst share of those scenarios. The picker describes it as "Generates possible futures and reduces the worst losses across them". Two things change as a result. The loss it looks at is the loss over a whole next period rather than a single day, and the scenarios can combine days that never followed each other in history — two instruments that never fell on the same day can still fall in the same scenario. The limit is the other side of the same coin: a kind of market the window never contained cannot appear in any scenario. Two settings describe the scenarios, under **Advanced settings**: - **Number of scenarios** — "How many possible futures are generated at each rebalance." From 100 to 2,000; 500 by default. - **Horizon of each scenario** — "How many trading days each generated future covers." From 5 to 63 days; 21 by default, about one month. Because Scenario CVaR measures its tail over the scenarios rather than over the window's days, a short window does not trigger the low-data warning for it. The same check runs against the number of scenarios instead, and within the ranges the app accepts — at least 100 scenarios, a tail share of at least 1% — its tail always keeps at least one scenario. ## What does the robustness radius do? The **Robustness radius** makes Scenario CVaR also guard against scenario sets slightly different from the one it generated: "Also protects against scenarios slightly different from the generated ones. The higher it is, the more evenly the weights spread." It is off by default; switched on, it runs from 0.001 to 0.1 and starts at 0.01. In theory terms it is distributionally robust optimisation: the method assumes an adversary may shift the scenarios a small distance — the radius — before the loss is measured, and minimises the worst loss that could result. The effect you see is that concentration is penalised, so a larger radius spreads the weights more evenly. From a radius of about 0.02 upward the weights become almost equal and every other setting stops mattering; with joint-crash scenarios also on, the app says so: "At this radius the weights become almost equal", with an action to reduce the radius to 0.01. ## What are joint-crash scenarios? **Joint-crash scenarios** change how Scenario CVaR generates its futures: instead of reusing whole days from the window, each instrument keeps its own history of daily moves while the link between instruments is drawn so that they tend to crash together more often than the window alone shows — a Student-t copula, in textbook terms. The app puts the trade-off plainly: "t copula: instruments tend to crash together. It is a different way to generate scenarios, not necessarily a better one." What it gives up is the way calm and stormy days cluster in real history. Switched on, it adds **Tail heaviness**, from 3 to 30 and 5 by default: "Lower = more extreme joint crashes." ## How does Fincanva handle it? - Minimum CVaR and Scenario CVaR are offered at **both levels**: across the instruments of a strategy, and across the strategies of a [Combined](/docs/getting-started/strategy-in-a-combined). - Both read the [calculation window](/docs/strategies/calculation-window) (**In-sample**, 12 months by default). Neither reads the **Covariance matrix** choice: they work on the returns themselves, not on a volatility-and-correlation estimate. - The **Tail share** starts at 5% and accepts 1% to 25%; a value outside that range shows an error on the field, and the backtest does not run until it is corrected. - Both are marked "slow to compute" in the picker: each rebalance solves an optimisation over every day or scenario. ## Which plan includes Minimum CVaR and Scenario CVaR? Both depend on your plan, at each level where they are offered. The robustness radius and joint-crash scenarios come with Scenario CVaR itself. **Minimum CVaR inside a strategy** Included from Ultimate upwards. See [what each plan includes](/docs/account-security/what-each-plan-includes). **Minimum CVaR inside a Combined** Included from Ultimate upwards. See [what each plan includes](/docs/account-security/what-each-plan-includes). **Scenario CVaR inside a strategy** Included from Ultimate upwards. See [what each plan includes](/docs/account-security/what-each-plan-includes). **Scenario CVaR inside a Combined** Included from Ultimate upwards. See [what each plan includes](/docs/account-security/what-each-plan-includes). ## What does it look like in practice? Two instruments both have 15% annual volatility over a 12-month window of about 252 days. Instrument A moves in even steps every day, about ±0.95% on a typical day. Instrument B is calmer most days, about ±0.57%, but had four days of −6% — and those four days alone supply almost two-thirds of its variance, which is how its annual volatility still comes out at 15%. - At a 5% tail share the method averages the worst 252 × 5% ≈ 12–13 days. - A's worst 5% of days average about −1.95%. B's worst 5% are its four −6% days plus its eight or nine worst ordinary days, about −1.25% each, and average about −2.8%. - Variance sees two equally risky instruments; Minimum CVaR sees one with about 40% more tail loss, and leans toward A — holding some B only where B's bad days fall on days when A did well, which lowers the mix's own tail. Shrink the window to 1 month (about 21 days) at the same 5% and 21 × 5% ≈ 1.05 day remains — right at the edge. At 4% it drops below one day, and the app shows the low-data warning described above. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/minimum-mad # Minimum MAD Minimum MAD is an [allocation method](/docs/strategies/allocation-and-allocation-method) that chooses the weights whose daily returns stray the least, on average, from their own mean. It is the robust cousin of minimising variance: variance squares every deviation, so one extreme day can outweigh months of ordinary ones, while the mean absolute deviation (MAD) counts each deviation once, at its size. The method picker labels it **"Minimum MAD"** and describes it as "Reduces the average deviation of returns: one unusual day weighs little". **Also seen as:** mean absolute deviation optimisation, MAD ## What is the mean absolute deviation? The mean absolute deviation is the average distance between each day's portfolio return and the portfolio's average return over the window: $$ \text{MAD} = \frac{1}{T} \sum_{t=1}^{T} \left| r_{p,t} - \bar{r}_p \right| $$ where: $T$ is the number of days in the [calculation window](/docs/strategies/calculation-window), $r_{p,t}$ is the portfolio's return on day $t$, and $\bar{r}_p$ is its average daily return. In words: how far, on a typical day, the portfolio lands from where it usually lands — counting a day twice as far away as twice as bad, not four times as bad. ## When does Minimum MAD differ from minimising variance? When returns have outliers. If returns were normally distributed, minimising MAD and minimising variance would lead to the same weights; the two part ways when some days are far more extreme than the rest. So a large gap between Minimum MAD's weights and the Min volatility weights of [MPT](/docs/strategies/modern-portfolio-theory) on the same instruments is itself a sign that their history has fat tails. What Minimum MAD does not offer is an efficient-frontier picture or a target to choose: it has one objective and no settings. ## How does Fincanva handle it? - Minimum MAD is offered at **both levels**: across the instruments of a strategy, and across the strategies of a [Combined](/docs/getting-started/strategy-in-a-combined). - It has no settings of its own. It reads the [calculation window](/docs/strategies/calculation-window) (**In-sample**, 12 months by default) and works on the daily returns themselves, so it does not read the **Covariance matrix** choice. - The picker marks it "slow to compute": each [rebalance](/docs/backtesting/rebalance) solves an optimisation over every day of the window. ## Which plan includes Minimum MAD? It depends on your plan, at each level where the method is offered. **Inside a strategy** Included from Ultimate upwards. See [what each plan includes](/docs/account-security/what-each-plan-includes). **Inside a Combined** Included from Ultimate upwards. See [what each plan includes](/docs/account-security/what-each-plan-includes). ## What does it look like in practice? A window holds 250 days on which an instrument moves 1% away from its average, and one day on which a data glitch or a one-off event puts it 20% away. - **In variance**, each ordinary day adds 0.01² = 0.0001 and the one extreme day adds 0.20² = 0.04 — as much as 400 ordinary days. That single day outweighs the rest of the window put together. - **In MAD**, each ordinary day adds 0.01 and the extreme day adds 0.20 — as much as 20 ordinary days. It counts, but it does not decide. An optimiser minimising variance would reorganise the whole portfolio around that one day; Minimum MAD treats it as one bad day among many. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/modern-portfolio-theory # Modern Portfolio Theory Modern Portfolio Theory is Harry Markowitz's mean-variance framework for combining instruments: for any level of risk you are willing to carry, there is a mix of instruments whose expected return is as high as it can be, and equivalently, for any expected return there is a mix whose risk is as low as it can be. Its central insight is that a portfolio's risk is not the average of its parts' risks — because instruments do not move in lockstep, a mix can be less volatile than the individual instruments inside it. **Also seen as:** MPT, Markowitz, mean-variance optimisation The method picker labels it **"MPT (Markowitz)"** and describes it as "Modern portfolio theory: optimize on a risk/return objective". It is an [allocation method](/docs/strategies/allocation-and-allocation-method) offered both inside a single strategy and inside a [Combined](/docs/getting-started/strategy-in-a-combined), and it has one optional variant, **Resampled**, that changes how its inputs are treated. [Black-Litterman](/docs/strategies/black-litterman) is built on MPT and appears in the picker as a method of its own. ## What is the efficient frontier? The efficient frontier is the set of portfolios that are not beaten on both counts at once — for each of them, you cannot raise expected return without also raising risk, and you cannot lower risk without also lowering expected return. Every other combination sits below the frontier and is dominated by one on it. For a two-instrument portfolio, the expected return is the weighted average of the two expected returns, but the volatility is not: $$ E(R_p) = w_A E(R_A) + w_B E(R_B) $$ $$ \sigma_p = \sqrt{w_A^2 \sigma_A^2 + w_B^2 \sigma_B^2 + 2 w_A w_B \rho_{AB} \sigma_A \sigma_B} $$ where: $w_A$ and $w_B$ are the two weights (adding to 1), $E(R)$ is an expected return, $\sigma$ is a [volatility](/docs/analysis/volatility), and $\rho_{AB}$ is the correlation between the two instruments' returns. The correlation term is what makes the frontier curve: the lower $\rho_{AB}$ is, the more the mix's volatility falls below the weighted average of the two individual volatilities. ## Which optimization target can you choose? The **Optimization target** control picks which point on the frontier the method aims at. The app describes the three options exactly like this: "Optimal = best risk-adjusted return. Min volatility = lowest portfolio risk. Max return = highest expected return regardless of risk." | Target | Aims at | |---|---| | **Optimal** (default) | the best return per unit of risk — the [Sharpe-ratio](/docs/analysis/sharpe-ratio) sense of "best" | | **Min volatility** | the lowest-risk point on the frontier | | **Max return** | the highest expected return, with no regard for the risk that comes with it | ## What do the MPT constraint toggles do? Three controls narrow which portfolios the optimisation is allowed to pick from. They change the answer by changing the admissible set — a tighter constraint can only move the result away from the unconstrained frontier point, or make the problem impossible to satisfy at all. | Control | Effect | |---|---| | **[Position direction](/docs/strategies/direction-long-only-long-short-short-only)** (strategy level only) | "Long-only requires every weight ≥ 0. Long + Short allows negative weights (short positions)." At the Combined level MPT is positive-only by construction, so this control does not appear there. | | **Weight limits** | "Constrain each instrument's weight to a range" — turning it on reveals **Min weight** and **Max weight**, which every instrument's weight must then respect. | | **Diversification** | "Force diversification" spreads weights more evenly across instruments instead of letting the optimisation concentrate them in a few. On a small set of instruments it can leave nothing that satisfies every constraint at once. | The weight-limit bounds themselves depend on the level and the direction: inside a **Combined** the weights run from 0 to 1; inside a single strategy set to **Long-only** they also run from 0 to 1, and set to **Long + Short** they run from −1 to 1. The weight limits have to be mutually satisfiable. A minimum weight that, multiplied by the number of instruments, comes to more than 100% cannot be met by any portfolio — and when that happens today, no weights are produced and the app shows no error message. ## What does the Resampled option do? **Resampled** repeats the optimisation on many resampled versions of the window's history and averages the weights they produce. The app describes it as "Michaud's method: repeats the optimization on many samples of the history and averages the results", with the effect "Steadier weights, less sensitive to noise." $$ \bar{w} = \frac{1}{B} \sum_{b=1}^{B} w^{(b)} $$ where: $B$ is the **Number of samples**, $w^{(b)}$ is the set of weights the optimisation returns on sample $b$, and $\bar{w}$ is the average that is actually held. In words: a lucky stretch that made one instrument look best in the observed history favours it in only some of the samples, so the average holds it at a moderate weight rather than piling onto it. - **Number of samples** runs from 10 to 1,000 and starts at 100. - It is very slow to compute, and the app says so with the sample count filled in — at the default: "Very slow to compute: every rebalance repeats the optimization 100 times." - The price is that the averaged weights are no longer a single point on the textbook efficient frontier. ## How is Black-Litterman related to MPT? **[Black-Litterman](/docs/strategies/black-litterman) is an allocation method built on MPT**, listed in the method picker as a method of its own rather than as an option inside MPT. It runs the same optimisation with every MPT setting on this page, and changes one input: the expected returns, which it replaces with a steadier estimate tilted toward momentum. Because only the expected returns change, it offers the **Optimal** and **Max return** targets and not **Min volatility**, which does not use them. Moving between MPT (Markowitz) and Black-Litterman in the picker keeps every MPT setting. ## How does Fincanva handle it? - **MPT is included from the Advanced plan**, at the strategy level and inside a Combined alike; Free and Starter do not offer it in either place. See [what each plan includes](/docs/account-security/what-each-plan-includes). - **Its weight limits start one plan level higher, at Ultimate.** On Advanced the method runs, but turning **Weight limits** on is refused with the plan level that includes it named; Ultimate and Professional allow it. See [what each plan includes](/docs/account-security/what-each-plan-includes). - **The Resampled option starts at Ultimate**, a step above the method: on Advanced, turning **Resampled** on is refused and the app names the plan that includes it, while MPT keeps running. Ultimate and Professional allow it. See [what each plan includes](/docs/account-security/what-each-plan-includes). - **Optimization target** defaults to **Optimal**. - **Weight limits** are off by default; when you turn them on, **Min weight** starts at 0 and **Max weight** at 0.5 (50%). - **Force diversification** is off by default. - At the strategy level **Position direction** starts at **Long + Short**, so shorting is allowed until you switch it to **Long-only**; at the Combined level MPT has no direction control and is positive-only. - The [calculation window](/docs/strategies/calculation-window) (**In-sample**) supplies the risk and return inputs, and defaults to **12 months**. - The **Covariance matrix** choice decides how volatilities and correlations are estimated from that window; a newly chosen MPT starts on Ledoit-Wolf · constant correlation — see [covariance matrix](/docs/strategies/covariance-matrix). - **Resampled** is off by default. - Weights are recomputed at every [rebalance](/docs/backtesting/rebalance) from the window ending at that date, so an MPT weighting moves over the life of a backtest rather than staying fixed. ## What does it look like in practice? Instrument A has an expected return of 6% and volatility of 10%; instrument B has an expected return of 10% and volatility of 20%; their correlation is 0.2. Hold them 60% / 40%: - Expected return: (0.6 × 6%) + (0.4 × 10%) = **7.6%**. - Volatility: √(0.6²×0.10² + 0.4²×0.20² + 2×0.6×0.4×0.2×0.10×0.20) = √0.01192 = **10.9%**. That single pair of numbers is one point on the frontier. Note what the low correlation bought: the mix carries 10.9% volatility, only 0.9 percentage points more than holding the calmer instrument A alone, while its expected return is 1.6 percentage points higher. Sliding the weights from 100% A to 100% B traces out the whole curve, and the frontier is the upper edge of it. ## What is the expected return based on? The expected returns and volatilities that MPT works from are estimates read off the historical calculation window — they are not forecasts. A mean-variance result is therefore only as stable as those estimates: two backtests over different windows can produce different "optimal" weights from the same instruments, because the inputs themselves changed. Picking the window whose weights looked best is [overfitting](/docs/investing-theory/overfitting), and searching across many windows for that best answer is [data snooping](/docs/investing-theory/data-snooping-bias). Fincanva describes how this method works; it does not recommend it or any target within it. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/nested-clustered-optimization # Nested Clustered Optimization Nested Clustered Optimization is an [allocation method](/docs/strategies/allocation-and-allocation-method) that splits one hard optimisation into several small ones: it groups the instruments that move alike, finds the lowest-risk mix inside each group, treats each group as a single instrument, and then finds the lowest-risk mix across the groups. An instrument's final weight is its weight inside its group multiplied by its group's weight. The method picker labels it **"NCO · Nested Clustered Optimization"** and describes it as "Optimizes inside each group of similar instruments, then across the groups". **Also seen as:** NCO ## Why split the optimisation into groups? Because estimation errors spread through a single large optimisation. When several instruments are almost identical, a minimum-risk optimiser over all of them at once can turn tiny differences in their measured correlations into large offsetting bets. Inside a small group the problem is well behaved, and the groups are then compared as a handful of synthetic instruments — so a measurement error inside one group cannot move the weights inside another. $$ w_i = w_{i \mid k} \times W_k $$ where: $w_{i \mid k}$ is instrument *i*'s weight inside its group *k*, $W_k$ is group *k*'s weight across the groups, and $w_i$ is the instrument's final share of the capital. Both levels aim at the lowest-risk mix, the "Min volatility" end of the [efficient frontier](/docs/strategies/modern-portfolio-theory). The number of groups is chosen from the data at each rebalance, not set by you. ## When does Nested Clustered Optimization fit, and when not? It fits a universe of many similar instruments — a basket of stocks that fall into sectors, say — where the groups are clear and a single optimisation would be most fragile. It fits less well in two cases: - **A universe with no clear groups.** The two-stage answer then drifts further from what a single lowest-risk optimisation would give. - **A book built on a hedge.** Two instruments that move in opposite directions are treated as maximally different and land in different groups, so the method cannot fully use the hedge between them. And like any lowest-risk optimisation, the across-group step can give a whole high-risk group a weight close to zero. ## How does Fincanva handle it? - Nested Clustered Optimization is offered **inside a single strategy only**, across its instruments; a Combined does not offer it. - It has no settings of its own. It reads the [calculation window](/docs/strategies/calculation-window) (**In-sample**, 12 months by default) and the **Covariance matrix** choice — see [covariance matrix](/docs/strategies/covariance-matrix). - Weights are never negative. - With most covariance estimators — including the recommended Ledoit-Wolf · constant correlation — every instrument must have moved in price at some point inside the window: an instrument whose price stayed flat for the whole window, such as a suspended listing, stops the backtest rather than receiving a weight. Two estimators are the exception; [covariance matrix](/docs/strategies/covariance-matrix) names them. - Weights are recomputed at every [rebalance](/docs/backtesting/rebalance) from the window ending on that date. ## Which plan includes Nested Clustered Optimization? Included from Advanced upwards. See [what each plan includes](/docs/account-security/what-each-plan-includes). ## What does it look like in practice? A strategy holds six instruments that fall into two groups of three: three bank stocks and three utility stocks. Inside the bank group, the lowest-risk mix is 50% / 30% / 20%; inside the utility group it is 40% / 40% / 20%. Treated as two synthetic instruments, the groups are then mixed for the lowest risk, which here comes out at 30% banks and 70% utilities. The first bank stock's final weight is 50% × 30% = **15%**; the first utility stock's is 40% × 70% = **28%**. Every one of the six weights is built the same way, and together they add up to 100%. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/per-strategy-risk-layer # Per-strategy risk layer The per-strategy risk layer is the set of [risk conditions](/docs/strategies/risk-condition) attached to one strategy inside a Combined, held separately from the Combined's own risk conditions. Because the two layers are independent, one strategy in a Combined can switch to its [Risk-Off](/docs/strategies/risk-on-and-risk-off) allocation while the others stay fully invested — going defensive is not an all-or-nothing decision for the whole Combined. **Also seen as:** per-strategy risk, strategy-level risk conditions The pieces of a Combined are [strategies](/docs/getting-started/strategy-in-a-combined). ## How do risk conditions work at two levels in a Combined? Each strategy inside a Combined carries its own **Risk** section, and the Combined carries a separate one titled "Combined risk", described as "De-risk the whole Combined when markets turn". A condition on one strategy changes only that strategy's own allocation. A condition at the [Combined level](/docs/getting-started/combined-level) changes how capital is split across the strategies. The two layers are evaluated independently, so at any moment both, one, or neither can be in a Risk-Off state. ## What happens when only one strategy goes Risk-Off? Only that strategy changes. It swaps in its own Risk-Off profile — typically taking less exposure and holding more cash — while the other strategies keep running their Risk-On profiles unchanged. The Combined's split of capital across its strategies is untouched, because that split is set by the Combined's own allocation — see [Combined weighting](/docs/strategies/combined-weighting) — and not by any one strategy's regime. The effect on the Combined as a whole is therefore partial: the share of capital sitting in the defensive strategy goes quiet, and the rest carries on. ## How does Fincanva handle it? - Every strategy inside a Combined has its own Risk section, and the Combined has its own; each holds at most two conditions, joined with Or — see [two-condition combination](/docs/strategies/two-condition-combination). - A strategy joins a Combined as a snapshot copy, and its risk conditions travel with that copy — see [strategy in a Combined](/docs/getting-started/strategy-in-a-combined). - Editing the risk conditions on a strategy inside a Combined does not change the standalone original it was copied from, and editing the original does not change the copy. - A strategy-level flip changes what that strategy holds; it does not change how much capital the Combined gives it. - If a strategy's Risk-Off profile matches its Risk-On profile, its flip changes nothing — see [Risk-Off canonicalization](/docs/strategies/risk-off-canonicalization). ## What does it look like in practice? A Combined holds three strategies and splits capital equally between them. The first strategy has a risk condition on a volatility index and a Risk-Off profile that takes clearly less exposure; the other two have no conditions at all. Volatility spikes and the first strategy's condition triggers: that strategy pulls most of its third of the capital out of the market, while strategies two and three stay fully invested in their own holdings. The Combined still gives each strategy a third of the capital — what changed is what the first strategy does with its third. When the condition clears, only that strategy switches back; the other two never moved. Had the same condition been set on the Combined's own Risk section instead, the defensive switch would have applied to the split across all three at once. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/percent-change # Percent change Percent change is how much a series has moved from an earlier point to now, expressed as a percentage of that earlier value: positive means the series has risen since then, negative means it has fallen. It is the plainest way to turn two levels into one comparable number, because a percentage strips out the size of the underlying value — a 10% rise is a 10% rise whether the price started at 5 or at 500. In Fincanva percent change is one of the **Indicator** choices on a [risk condition](/docs/strategies/risk-condition), turning a level series into a change series before the threshold comparison. **Also seen as:** percentage change, % change, price change, rate of change. ## How is percent change calculated? Percent change is the difference between the current value and the earlier value, divided by the earlier value. $$ \text{percent change} = \frac{P_t - P_{t-N}}{P_{t-N}} \times 100 $$ where: $P_t$ is the latest value of the series, $P_{t-N}$ is its value $N$ periods earlier, and $N$ is the lookback the **Period** field sets. The denominator is always the *earlier* value, which is why the same absolute move is a bigger percentage from a lower base. ## What does a positive or negative reading mean? A positive percent change means the series ends the window above where it started; a negative one means it ends below. Zero means it is back where it began, whatever happened in between — percent change compares only the two endpoints and knows nothing about the path between them, so a series that fell hard and fully recovered reads the same as one that never moved. Read it alongside a path-aware measure such as [max drawdown](/docs/analysis/max-drawdown) if the journey matters as much as the endpoint. This page describes a measurement, not a recommendation. ## How does Fincanva handle it? - Percent change is one of four **Indicator** options on a risk condition's series, alongside "Raw price", "Simple moving average", and "Average momentum". - With "Percent change" selected, a **Period** field appears next to the indicator; you type how far back the comparison reaches. - The indicator only transforms the series being watched. Whether the strategy ends up in [Risk-On or Risk-Off](/docs/strategies/risk-on-and-risk-off) is decided by the condition's [thresholds](/docs/strategies/condition-types), not by the change reading itself. - The shipped "S&P 500 12-month momentum" [risk template](/docs/strategies/risk-templates) is a 12-month percent change of the index. ## What does it look like in practice? An index stands at 4,400 today and stood at 4,000 twelve months ago. The 12-month percent change is (4,400 − 4,000) / 4,000 × 100 = +10% — the index is 10% above its level a year earlier. Now suppose it instead stands at 3,600 after that same year: the reading is (3,600 − 4,000) / 4,000 × 100 = −10%. The two readings are symmetric in wording but not in level: a −10% move from 4,000 lands at 3,600, and a +10% move back from 3,600 only reaches 3,960, not 4,000, because the second percentage is measured against the smaller base. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/ranking-based # Ranking-Based Ranking-Based is an [allocation method](/docs/strategies/allocation-and-allocation-method) that sorts a strategy's holdings by a ranking metric you choose, splits the sorted list into ten rank tiers, and pays each tier the relative weight you set for it. Because the sort is redone at every [rebalance](/docs/backtesting/rebalance), weight follows rank rather than staying attached to a particular instrument: an instrument that climbs the ranking gains weight, and one that falls loses it. **Also seen as:** rank weighting, decile weighting ## How does Ranking-Based assign weights? Ranking-Based ranks every candidate by the selected metric, highest value first, and then pays each rank tier the weight you typed for it. The tiers are deciles: **Tier 1** is the top 10% of the ranked list and **Tier 10** the bottom 10%. Weights are relative, not percentages — the app says "Weights are relative — any number from -999 to 999, decimals allowed. A negative weight holds that tier short." The ten tier weights are normalised to 100% of the sum of their sizes before capital is assigned, so 50/30/20 and 5/3/2 describe the same allocation, and a negative tier weight counts towards that total by its size. A tier left at 0 receives nothing, which is how the weakest ranks are dropped from the strategy entirely; a tier with a negative weight is held as a short position, its [direction](/docs/strategies/direction-long-only-long-short-short-only) given by the sign. The sort direction is always highest-value-first, whatever the metric measures. That is worth reading twice for the risk metrics: rank on Volatility and Tier 1 holds the *most* volatile instruments, not the calmest. ## Which ranking metrics can you choose? Five ranking metrics are available inside a single strategy. A Combined offers the same list without P/E Ratio. | Ranking metric | Sorts on | Reads the calculation window? | |---|---|---| | Price Change | recent price change | yes | | Average Momentum | average momentum | no | | Volatility | [volatility](/docs/analysis/volatility) | yes | | Sharpe Ratio | [Sharpe ratio](/docs/analysis/sharpe-ratio) | yes | | P/E Ratio | price-to-earnings ratio | no | **Average Momentum** ranks on [average momentum](/docs/strategies/average-momentum) — the average of an instrument's percent price change over 1 month, 3 months, 6 months and 12 months. It is the one ranking metric that blends several spans instead of reading a single window, which is why it ignores the calculation window entirely. Two consequences show up in a ranking: an instrument is not ranked on average momentum until it has 12 months of price history behind it, because until then the longest of the four spans reaches past the start of its history; and because three of the four spans are long, an instrument's rank moves more slowly than its price does. ## What does the shape of the rank weights change? The shape of the ten tier weights controls how concentrated the strategy is, independently of the metric. A steep drop from Tier 1 to Tier 10 pushes most of the capital into the best-ranked names and leaves the strategy effectively holding a handful of positions; a flat set of weights makes Ranking-Based behave like equal weighting, since rank no longer changes the payout. Tiers left at 0 drop out entirely, so a curve that zeroes the bottom half is acting as a filter as well as a weighting. This describes what each shape does — Fincanva does not recommend a shape or a metric. ## What happens if every tier weight is zero? A Ranking-Based setup whose ten tier weights are all 0 invests nothing: every tier receives nothing, so no instrument is held. Fincanva lets you save it, but the totals line reads "Total raw: 0 · Invests nothing — every weight is zero" and a yellow warning appears — "This allocation invests nothing: every weight is zero, so no capital goes anywhere." — which you can accept like any other warning. A fresh Ranking-Based setup starts in exactly this state, so the warning shows until you apply a preset or type a weight. ## How does Fincanva handle it? - **Ranking-Based is included from the Starter plan**, at the strategy level and inside a Combined alike; the Free plan does not offer it in either place. See [what each plan includes](/docs/account-security/what-each-plan-includes). - The default ranking metric is **Price Change**. - A fresh Ranking-Based setup starts on the **Equal Weight** preset — the same weight on all ten tiers — so it invests from the start, spreading capital evenly whatever the rank. Apply another preset or type your own numbers to make the ranking tilt the allocation. **Clear** returns every tier weight to 0. - The presets shipped today are Equal Weight, Balanced Top Tilt, Strong Top Tilt, Top 3 Equal, Top Decile Only and Linear Decay, plus the advanced Soft Exclusion, Top Half Tilt, Contrarian / Inverse Rank and Barbell. - Inside a strategy each tier weight can be any number from −999 to 999, decimals included, and exactly ten are kept — one per tier. A number outside that range is not changed for you: the field shows "Enter a rank weight between -999 and 999." until you correct it. - Ranking-Based works at both levels: inside a single strategy it ranks instruments, and inside a Combined it ranks the member strategies — see [Combined weighting](/docs/strategies/combined-weighting). - Price Change, Volatility and Sharpe Ratio read the [calculation window](/docs/strategies/calculation-window); Average Momentum and P/E Ratio do not, so changing the window leaves those two rankings unchanged. ## What does it look like in practice? A strategy holds ten instruments and ranks them by Price Change over a 12-month calculation window. With ten instruments and ten tiers there is exactly one instrument per tier. You type 50 in Tier 1, 30 in Tier 2, 20 in Tier 3 and leave Tiers 4 to 10 at 0. The raw total is 100, so the best-ranked instrument takes 50% of capital, the second 30%, the third 20%, and the remaining seven are not held at all. At the next rebalance the ranking is recomputed: if the previous leader slips to third, its weight falls from 50% to 20%, and whichever instrument now ranks first takes the 50%. Nothing about the instruments changed the weights — only their positions in the sorted list did. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/raw-price # Raw price Raw price is the **Indicator** option in a [risk condition](/docs/strategies/risk-condition) that applies no transformation at all, so the condition compares the watched series' own level against your threshold. It is the simplest of the four indicator options, and the one a new condition starts on: pick it when the number you want to test against is the level the series publishes, not something derived from it. **Also seen as:** price level, index level, untransformed series. ## When does a condition use Raw price? A condition uses Raw price whenever the number you want to compare against is the series' published level itself, not something derived from it. That covers a volatility index you compare against a level, a yield spread you compare against zero, and a price you compare against another price. Because nothing is derived, no window is involved: the **Period** field has nothing to read over and does not apply. In a **Double series** condition, Raw price on one side is how a series is compared against a transformed version of itself — for example a price against its own moving average. ## How does Fincanva handle it? - Raw price is one of four **Indicator** options, alongside "Simple moving average", "Percent change", and "Average momentum". - Raw price takes no lookback window — the **Period** field applies to the indicators that summarise a span. - The threshold you type is read in the series' own units: an index level for an index, a rate in percent for a yield series, a price for a stock or ETP. - Several built-in [risk templates](/docs/strategies/risk-templates) use Raw price, including the VIX and VIX ratio templates and every yield-curve spread template. ## What does it look like in practice? You build a Single series condition on a volatility index and leave the **Indicator** at "Raw price". The condition now reads whatever the index publishes: 18 one day, 31 a few weeks later. Those readings are compared straight against the number in the Risk-Off comparison, with no averaging, no percentage, and no window in between — so a single day's print is the whole signal. That directness is exactly why the [confirmation delay](/docs/strategies/confirmation-delay) exists: on a Raw price condition it is the only thing that stops one unusual day from asking for a switch. Change the same condition's **Indicator** to "Simple moving average" with a **Period** of 20 and the comparison would instead read the average of the last twenty periods — a smoother number, and one that needs a **Period** to be meaningful. **Learn more:** [Risk conditions](/docs/strategies/risk-conditions#what-a-single-risk-condition-is-made-of) Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/reinvest-delay # Reinvest delay Reinvest delay is a cooldown on re-entry: after a position closes, the instrument it held stays out of the strategy's choices for the number of months you set, so the strategy cannot buy that same instrument straight back. It is not an exit rule — it does not decide when a position closes, only how soon the instrument can return. In the app the control is labelled **Reinvest delay**, with the helper "Wait this long before re-entering an instrument after its position closes", and a screen reader announces its number field as "Months before re-entering a closed instrument". **Also seen as:** re-entry cooldown ## What does reinvest delay do to freed-up cash? Nothing directly: reinvest delay holds back the **instrument**, not the money. While the delay runs, the instrument whose position closed is left out of the candidates the strategy chooses from at each rebalance — exactly as if its selection rules had not picked it — even when those rules select it again. The cash the exit freed is handled at the next rebalance like any other cash in the strategy, by its [allocation method](/docs/strategies/allocation-and-allocation-method). Without the delay, an instrument that has just been closed can be bought again at any later rebalance that selects it. With it, a strategy that keeps selecting the same instrument cannot rotate straight back into it — the common use is to stop a stopped-out position being re-bought at the very next rebalance. The delay is counted in whole multiples of the strategy's rebalance interval, so the instrument comes back into play on a rebalance date rather than on an arbitrary day — the same whole-multiples clock that governs [rebalance](/docs/backtesting/rebalance) cadence and every timing setting bound to it. ## When does the clock start — at the exit, or at the rebalance that records it? **At the exit itself.** The delay is measured from the date the position actually closed, not from the rebalance that booked it. A position stopped out or taken-profit between rebalance dates carries the date of the day it was hit, so its instrument starts waiting from that day rather than from the next scheduled rebalance. In practice this matters less often than it sounds, and the reason is worth knowing: the delay counts **whole calendar months crossed**, not elapsed days. A position closed on 3 March and one closed on 20 March have both crossed one month boundary by 1 April, so a one-month delay expires for both on the same date. The exit date only buys you time when it falls in an **earlier calendar month** than the rebalance that would otherwise have recorded it. And the delay expiring is not the same as the instrument being bought: the strategy only checks eligibility at a rebalance, so an instrument whose delay runs out mid-period still waits for the next rebalance — and for its selection rules to pick it — before it can be bought again. ## How does Fincanva handle it? - Off by default. When you switch it on, the value starts at the strategy's own rebalance interval — always a valid multiple — and you raise it from there. - Entered in months (the field's suffix reads "mo"), up to a maximum of 120 months; a value that is not a whole multiple of the cadence is rejected with "Must be a multiple of `{rebalanceEvery}` months". - Changing the rebalance cadence does not change a value you have already set: if it is no longer a whole multiple of the new cadence, the field flags it with "Must be a multiple of `{rebalanceEvery}` months" and you pick a valid value. - The delay applies to the instrument whatever closed its position — a take profit, a stop loss, a [max hold](/docs/strategies/max-hold-months), an Exclude screener, a rebalance that dropped the instrument, or the end of its price history. ## What does it look like in practice? A strategy rebalances every month and has reinvest delay set to **3** months. On 10 March one of its holdings hits its [stop loss](/docs/strategies/stop-loss) and is closed. At the April and May rebalances the strategy's rules select that instrument again, but it is still inside its delay, so it is left out and the strategy allocates among its other candidates. At the June rebalance — three calendar months on from March — the instrument is eligible again and can be bought back if the rules still select it. Set the delay to 1 month instead and it makes no difference in this case: April is already one calendar month on from March, so the instrument can return at the April rebalance, the first one after the stop-out. Turn the setting off and the same is true — without a delay, the earliest the instrument can come back is the next rebalance that selects it. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/risk-condition # Risk condition A risk condition is a rule that watches a market series and, when it triggers, switches the strategy from its Risk-On allocation to its **Risk-Off** allocation — the more defensive profile you defined yourself. When the condition clears, the strategy switches back to Risk-On. A strategy can carry up to two risk conditions, and you build each one in the **Risk** card, described in the app as "Automatically de-risk when markets turn". Most conditions watch a market series; the quantitative rule [Strategy's own performance](/docs/strategies/strategy-s-own-performance) watches a Combined's own value instead. ## What does a risk condition do when it triggers? A triggered risk condition switches the strategy to its Risk-Off allocation profile — and nothing else. It does **not** pause, halt, or stop the strategy: the strategy keeps running, keeps rebalancing, and keeps holding positions, just under the other allocation profile. It does not liquidate to cash either, unless the Risk-Off profile you configured is itself cash. The app states the mechanic directly in the risk step: "Define risk conditions that switch the strategy to its Risk-Off allocation when triggered." What actually changes when a condition fires is described in [Risk-On and Risk-Off](/docs/strategies/risk-on-and-risk-off). ## What is a risk condition made of? Every risk condition is one watched series, one comparison, and two behaviour settings. | Part | Control | What it sets | |---|---|---| | Watched series | **Instrument** | the ticker the rule watches | | Transformation | **Indicator** | "Raw price", "Simple moving average", "Percent change", or "Average momentum" | | Window | **Period** | how many periods the indicator covers — for the indicators that read over a window | | Comparison | the **Signal** you chose, plus the operator and thresholds its sentence holds | Whether the series is compared to numbers you type or to a second series | | Patience | **Confirmation delay (weeks)** | How long a flip must stand before the strategy acts on it | | Timing | **Auto-rebalance** | Whether a flip forces an off-schedule rebalance | That table describes the two **Custom** shapes, Single series and Double series. The three **Quantitative regimes** rules — [Hidden regimes (Markov)](/docs/strategies/hidden-regimes-markov), [Clustering](/docs/strategies/clustering) and [Strategy's own performance](/docs/strategies/strategy-s-own-performance) — replace the Indicator, Operator and Thresholds with a model's own settings and keep the same two behaviour settings. All five shapes are covered in [Condition types](/docs/strategies/condition-types); the two behaviour settings in [Confirmation delay](/docs/strategies/confirmation-delay) and [Auto-rebalance on flip](/docs/strategies/auto-rebalance-on-flip). Both behaviour settings exist to damp [whipsaw](/docs/strategies/whipsaw) — the flip-and-flip-back a sensitive rule produces. ## How does the trigger test read? A risk condition asks for Risk-Off when its indicator satisfies the comparison you set. $$ \text{Risk-Off is requested when}\quad s_t \;\square\; \theta $$ where: $s_t$ is the value of the chosen indicator on the watched series at time $t$; $\square$ is the **Operator** you pick — "is above" or "is below"; and $\theta$ is the number you type in the Risk-Off comparison. A **Double series** condition replaces $\theta$ with a second series' value, $s^{(2)}_t$. A **Single series** condition runs this same comparison twice — one threshold asks for Risk-Off, a second asks for Risk-On again — and [Condition types](/docs/strategies/condition-types) covers that pair and why it exists. A quantitative rule asks for Risk-Off by its own test instead — a probability, a group of days or a metric of the Combined — stated on its own page. ## How does Fincanva handle it? - With no condition configured a strategy stays in Risk-On permanently — the empty state reads "Without a condition, the strategy stays in Risk-On at all times." - A strategy can carry at most two risk conditions, and they combine with OR: the list summarises this as "Any match → Risk-Off", so either one triggering is enough, and the conditions are listed under the line "Go Risk-Off when any trigger fires:" — see [two-condition combination](/docs/strategies/two-condition-combination). - Each condition carries its own **Confirmation delay (weeks)** and its own **Auto-rebalance** toggle — they are set per condition, not per strategy. - Configuring the Risk-Off allocation identically to Risk-On is a no-op: there is nothing to switch to, so triggering changes nothing. - The app does not notify you when a condition triggers — you see the current state by opening the strategy. - Fincanva does not tell you when to go defensive, which series to watch, or what threshold to set. See [Is this financial advice?](/docs/investing-theory/is-this-financial-advice#is-this-financial-advice). ## What does it look like in practice? You want a strategy to turn defensive while a broad equity index is trading below its long-term trend. In the condition builder you pick "Double series" under **Custom**, set **Series 1** to SPY with the **Indicator** left at "Raw price", and set the **Comparison series** to SPY with the **Indicator** "Simple moving average" and a **Period** of 200 — SPY against its own [200-day simple moving average](/docs/strategies/simple-moving-average-sma). The **Operator** reads "is below". Finally you set **Confirmation delay (weeks)** to 2, so a two-day dip below the average is not enough. The result: while SPY sits below its 200-day average for at least two weeks, the strategy runs its Risk-Off allocation; when SPY is back above the average, it runs Risk-On again. At no point does the strategy stop, and the only holdings that change are the ones the two allocation profiles differ on. A **Single series** condition would instead compare the indicator against two numbers you type — [Condition types](/docs/strategies/condition-types) explains why there are two of them. **Learn more:** [Risk conditions](/docs/strategies/risk-conditions) Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/risk-measure-selection # Risk measure selection Risk measure selection is the choice of which statistic counts as "risk" when an allocation method sizes positions by risk. Fincanva offers two: **annualized volatility** (the annualized standard deviation of returns) and **max drawdown** (the worst peak-to-trough fall). The choice matters because the two measures rank the same set of instruments differently, so the same strategy over the same window can end up with very different weights. **Also seen as:** Risk measure, risk metric, risk proxy ## Why does the choice of risk measure change the weights? The two measures look at different things. [Volatility](/docs/analysis/volatility) counts every swing across the whole window, up and down alike, and says nothing about where those swings led. [Max drawdown](/docs/analysis/max-drawdown) counts a single event — the deepest fall from a previous peak — and ignores how choppy the ride was otherwise. So an instrument that grinds steadily downhill can look calm on volatility and terrible on drawdown, while one that lurches around but keeps recovering can look wild on volatility and mild on drawdown. Whichever measure you pick becomes the working definition of "calm" that the method weights by. ## Which allocation method uses the risk measure? The **Risk measure** control belongs to the **[Inverse Volatility](/docs/strategies/inverse-volatility)** method, whose description reads "Less-volatile instruments receive higher weights". Textbook inverse-risk weighting gives each instrument a weight proportional to 1 ÷ its risk and then normalizes so the weights sum to 100%, so the instrument the chosen measure calls calmest receives the largest weight. The control's hint states both options plainly: "Annualized volatility = how much the price fluctuates · Max drawdown = its worst historical loss". ## How does Fincanva handle it? - The control is labelled **Risk measure** and offers exactly two options: "Annualized volatility" and "Max drawdown". - The window each measure is computed over is the profile's **In-sample** setting, in months — "Historical window used by the active method for volatility, correlation, beta, and similar calculations. Default 12." - Annualized volatility follows the standard 252-trading-day convention (the daily figure × √252) — see [volatility](/docs/analysis/volatility). - The risk measure belongs to the allocation profile, so a Risk-On and a Risk-Off profile can weight by different measures — see [allocation and allocation method](/docs/strategies/allocation-and-allocation-method). ## What does it look like in practice? Two instruments over the same 12-month window. Instrument A shows annualized volatility of 12% and a max drawdown of 35% — a slow, steady slide. Instrument B shows annualized volatility of 20% and a max drawdown of 18% — choppy, but it kept bouncing back. Weighting each in proportion to 1 ÷ its risk: | Risk measure | A's risk | B's risk | A's weight | B's weight | |---|---|---|---|---| | Annualized volatility | 12% | 20% | 62.5% | 37.5% | | Max drawdown | 35% | 18% | 34% | 66% | Same two instruments, same window, opposite ordering — under volatility A is the calm one and takes almost two-thirds of the capital; under max drawdown B is the calm one and takes almost two-thirds. That reversal is the whole point of the setting: you are choosing which kind of risk the weights should shrink away from. *Fincanva does not tell you which risk measure to use.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/risk-parity # Risk Parity Risk Parity is an [allocation method](/docs/strategies/allocation-and-allocation-method) that sizes every instrument so that each one contributes the same share of the portfolio's total risk. **Equal risk contribution is not the same thing as equal weight:** if two instruments are held in equal amounts but one is three times as volatile as the other, the volatile one supplies almost all of the portfolio's risk. Risk Parity shrinks the risky positions and enlarges the calm ones until each supplies an equal slice. **Also seen as:** equal risk contribution, ERC, risk budgeting ## What does "equal risk contribution" mean? An instrument's risk contribution is its weight multiplied by how much the portfolio's overall volatility changes when that weight changes. The standard definition splits total portfolio volatility into one slice per instrument, and those slices add back up to the whole. $$ RC_i = w_i \times \frac{\partial \sigma_p}{\partial w_i} \qquad\text{and}\qquad \sum_i RC_i = \sigma_p $$ where: $RC_i$ is instrument *i*'s risk contribution, $w_i$ is its weight, $\sigma_p$ is the portfolio's volatility, and $\partial \sigma_p / \partial w_i$ is instrument *i*'s marginal effect on that volatility. Risk Parity is the weighting that makes every $RC_i$ equal. Because $\partial \sigma_p / \partial w_i$ depends on how instrument *i* moves against the rest of the portfolio, not only on its own [volatility](/docs/analysis/volatility), correlations feed into a risk-parity weighting even though correlation is never something you set. ## Which settings does Risk Parity have? One: **Covariance matrix**, which decides how the volatilities and correlations behind the risk contributions are estimated — the plain sample estimate or a corrected one; see [covariance matrix](/docs/strategies/covariance-matrix). Equalising risk contribution itself leaves nothing to choose. The other input Risk Parity reads is the [calculation window](/docs/strategies/calculation-window) — the field labelled **In-sample** in the strategy editor — which sets how many months of history those estimates cover. Why the statistic a method treats as "risk" changes its answer at all is covered in [risk measure selection](/docs/strategies/risk-measure-selection). ## Where can you use Risk Parity? Risk Parity is available at both levels. Inside a single strategy it sizes the [instruments](/docs/getting-started/instrument) the strategy holds; inside a [Combined](/docs/getting-started/strategy-in-a-combined) it splits capital across the strategies the Combined contains, so each strategy contributes an equal share of the Combined's risk. ## How does Fincanva handle it? - **Risk Parity is included from the Advanced plan**, at the strategy level and inside a Combined alike. Free and Starter do not offer it in either place. See [what each plan includes](/docs/account-security/what-each-plan-includes). - Risk Parity's only setting is **Covariance matrix**. A newly chosen Risk Parity starts on Ledoit-Wolf · constant correlation, marked Recommended; a strategy saved before that choice existed keeps the sample estimate, so its results do not change by themselves. - The calculation window (**In-sample**) defaults to **12 months** and accepts any whole number of months from 1 upward. - Weights are recomputed at every [rebalance](/docs/backtesting/rebalance) from the risk figures measured over the window ending at that date, so a risk-parity weighting drifts over the life of a backtest rather than staying fixed. - Risk Parity never assigns a zero weight to an instrument you have selected: every instrument must carry a slice of the risk, so every instrument gets some weight. ## What does it look like in practice? A strategy holds two instruments with no tendency to move together. Instrument A has 10% volatility, instrument B has 30%. - **At equal weights (50% / 50%)** the risk slices are proportional to (weight × volatility)², so A supplies 0.05² = 0.0025 and B supplies 0.15² = 0.0225 — a split of **10% / 90%**. A "balanced" 50-50 portfolio is in fact nine-tenths driven by one instrument. - **Risk Parity** instead sets the weights to **75% / 25%**, because 0.75 × 10% = 0.25 × 30% = 7.5%. Now each instrument supplies exactly half the risk. The 50-50 portfolio looks balanced by weight and is heavily lopsided by risk; the 75-25 portfolio looks lopsided by weight and is balanced by risk. Which of those two is "balanced" is exactly the question Risk Parity answers differently from [Equal Weights](/docs/strategies/equal-weights). ## How is Risk Parity different from Inverse Volatility? [Inverse Volatility](/docs/strategies/inverse-volatility) reads each instrument's risk in isolation and weights by one divided by that figure. Risk Parity targets the finished portfolio's risk split, which also depends on how the instruments move together. In the worked example above the two methods happen to agree on 75-25, because the instruments were uncorrelated — that equivalence is a special case, and it breaks as soon as the instruments move together. Fincanva describes how these methods work; it does not recommend one. See [Is this financial advice?](/docs/investing-theory/is-this-financial-advice). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/risk-templates # Risk templates Risk templates are the ready-made [risk conditions](/docs/strategies/risk-condition) listed in the **Signal** menu of the condition builder: each one arrives with its instrument, indicator, operator, and thresholds already filled in, so picking one gives you a complete working condition in a single click. They are starting points, not recommendations — Fincanva describes what each template watches and leaves the choice, and any tuning, to you. **Also seen as:** presets, ready-made conditions. ## What do the built-in risk templates watch? Eleven templates ship today, grouped in the builder under **Volatility**, **Yield curve**, **Inflation**, and **S&P 500**. Each description below is the one the app shows. | Group | Template | What it watches | |---|---|---| | Volatility | **VIX** | "CBOE volatility index level. Risk-Off when volatility exceeds the threshold." | | Volatility | **VIX ratio** | "Ratio of short-term (VIX) to medium-term (VXV) implied volatility. Risk-Off when the short term exceeds the medium term." | | Inflation | **TIPS** | "Average momentum of Treasury Inflation-Protected Securities. Risk-Off when momentum turns sharply negative." | | Yield curve | **Short Term (5Y − 3M)** | "Short-end yield curve spread. Risk-Off when inverted." | | Yield curve | **Medium Term (10Y − 5Y)** | "Mid-curve yield spread. Risk-Off when inverted." | | Yield curve | **Medium Term (10Y − 5Y, inflation)** | "Inflation-indexed mid-curve spread. Risk-Off when inverted." | | Yield curve | **Long Term (30Y − 3M)** | "Long-end vs short-end spread. Risk-Off when inverted." | | Yield curve | **Long Term (30Y − 10Y)** | "Long-end spread. Risk-Off when inverted." | | Yield curve | **Long Term (30Y − 10Y, inflation)** | "Inflation-indexed long-end spread. Risk-Off when inverted." | | S&P 500 | **S&P 500 200-day moving average** | "Risk-Off when the S&P 500 crosses below its 200-day simple moving average." | | S&P 500 | **S&P 500 12-month momentum** | "12-month percent change of the S&P 500. Risk-Off when 12-month momentum turns negative." | An *inverted* yield curve means the shorter-dated yield in the pair sits above the longer-dated one, so the spread between them turns negative — which is what those templates compare against. The two inflation-indexed spreads read the same pairs on inflation-linked yields instead of nominal ones. ## What can you change once you pick a template? You can change every value of a template, because the builder shows the whole rule as one sentence and each value in it opens its own control. Each template declares the values it expects you to adjust — for most of them the two thresholds and their operators — and changing any other value appends " (modified)" after the template's description, so you can see the condition no longer matches its template. **Reset to template** puts the original values back. If you would rather start from nothing, the menu also offers **Custom** ("Build your own rule from scratch.") with two starting shapes, "Single series" and "Double series" — see [Condition types](/docs/strategies/condition-types). ## How does Fincanva handle it? - Every template ships with **Confirmation delay (weeks)** at 0 and **Auto-rebalance** off — maximum responsiveness, and therefore maximum exposure to [whipsaw](/docs/strategies/whipsaw); add patience or off-schedule rebalancing yourself if you want them. - Most templates are **Single series** conditions with two thresholds. The **S&P 500 200-day moving average** template is a **Double series** condition instead, comparing the index against its own moving average, so it has no numeric thresholds. - Several templates read their series untransformed — see [Raw price](/docs/strategies/raw-price). - Which fields a template exposes for tuning varies: most let you edit the two thresholds and their operators, while the **S&P 500 200-day moving average** template exposes none, so any change to it counts as a modification. - Where a template's construction is not published — the [Average momentum](/docs/strategies/average-momentum) indicator behind the **TIPS** template, for instance — Fincanva documents what the template observes, not how the value is built. ## Does Fincanva recommend a risk template? No. Fincanva describes what each template watches and what its fields mean; it does not say which template to use, whether to use one at all, when a strategy should turn defensive, or what threshold to set. A template being built in is not a signal that it works — it is a pre-filled form. See [Is this financial advice?](/docs/investing-theory/is-this-financial-advice#is-this-financial-advice). ## What does it look like in practice? You pick the **S&P 500 200-day moving average** template. The builder fills in a **Double series** condition: **Series 1** is the S&P 500 read as a level, and the **Comparison series** is the same index transformed by a [simple moving average](/docs/strategies/simple-moving-average-sma) over 200 days. The comparison between them is the whole condition, which is why its sentence holds no threshold — there is no number to type. You then select the confirmation delay in the rule's last sentence, set **Confirmation delay (weeks)** to 4 so a brief dip below the average is not acted on, and leave **Auto-rebalance** off so a flip rides the strategy's normal rebalance schedule. Because the confirmation delay is not one of the fields this template exposes for tuning, the template's description now reads with " (modified)" after it — a label, not a warning. **Reset to template** would undo both edits. **Learn more:** [Set up a risk condition](/docs/strategies/set-up-a-risk-condition) Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/risk-off-canonicalization # Risk-Off canonicalization Risk-Off canonicalization is what happens when a strategy's [Risk-Off allocation profile](/docs/strategies/risk-on-and-risk-off) is configured identically to its Risk-On profile: the switch has nothing to change, so a triggered [risk condition](/docs/strategies/risk-condition) produces no visible effect and the backtest comes out the same as it would with no risk condition at all. The condition is not broken — there is simply no difference between the two states to switch into. This page is about that one failure mode; the two profiles themselves are covered by Risk-On and Risk-Off. **Also seen as:** identical-profile no-op ## Why does nothing change when the condition fires? Going [Risk-Off](/docs/strategies/risk-on-and-risk-off) means swapping one allocation profile for another. If both profiles carry the same weighting method with the same settings, the swap replaces a profile with its twin and the holdings that come out are the ones that were already there. The regime still flips — the strategy is genuinely in its Risk-Off state — but nothing about what it holds, or about the equity curve, differs from the Risk-On state. See [risk conditions](/docs/strategies/risk-conditions) for what a flip normally changes. ## How does Fincanva flag identical profiles? The app raises a non-dismissable warning on the strategy: "Risk-Off allocation is the same as Risk-On." It appears once risk conditions are active and both profiles are materially the same, and it cannot be accepted away — the only fix is to make the two profiles actually differ. This is a different situation from a Risk-Off profile that was never picked at all, which shows the harder error "Risk-Off allocation needs to be set" — "Risk conditions are active, but no Risk-Off allocation method has been picked yet. Choose one below so the strategy knows what to do when a risk condition triggers." ## How does Fincanva handle it? - For a flip to change anything, the two profiles must differ in something the allocation uses: the [weighting method](/docs/strategies/allocation-and-allocation-method), that method's own parameters, or the profile's calculation window. - At the strategy level the profiles also differ if their leverage differs; at the Combined level, if their invested portion differs. - Matching profiles make the condition a no-op — the strategy behaves as if it had no risk condition, even though the condition is configured and active. - The profile's name ("Risk-On" / "Risk-Off") is a label, not a setting, so two profiles are still counted as identical when only their names differ. ## What does it look like in practice? A strategy runs Equal Weights, no leverage, in Risk-On. You add a risk condition on a volatility index and set the Risk-Off profile to Equal Weights, no leverage — the same thing. Fincanva shows "Risk-Off allocation is the same as Risk-On." You back-test through a downturn in which the condition triggers for four months. The equity curve is identical to the same strategy with no condition at all: through those four months it still held the same instruments, at the same weights, with the same exposure. Lower the Risk-Off exposure, or pick a different method for Risk-Off, and the two runs diverge from the first trigger onward — that difference is the entire effect of the risk condition. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/risk-on-and-risk-off # Risk-On and Risk-Off Risk-On and Risk-Off are the two allocation profiles a strategy can run: **Risk-On** is the normal profile, and **Risk-Off** is the defensive profile the strategy switches to while a [risk condition](/docs/strategies/risk-condition) is triggered. They are a pair — each carries its own weighting method and its own invested portion, so the same instruments can be held very differently in each. A strategy is always in one of the two, and it never sits in neither. **Also seen as:** RORO, defensive allocation ## What is the difference between Risk-On and Risk-Off? The difference is the allocation profile, not the activity: both profiles are complete allocations, and the strategy runs continuously under whichever one is active. In the **Allocation** card the two sit side by side — **Risk-On** is the allocation that runs while no risk condition is firing, **Risk-Off** the one that runs while one is. Each has its own [allocation method](/docs/strategies/allocation-and-allocation-method) picker ("Method for Risk-On" / "Method for Risk-Off") and its own invested portion, so Risk-Off can use a different weighting method, put less capital to work, or both. Until you configure the defensive side, the app shows "Risk-Off allocation needs to be set". ## What switches a strategy from Risk-On to Risk-Off? A risk condition does, and only a risk condition. While no configured condition is triggered the strategy runs Risk-On; while one is triggered it runs Risk-Off. With two conditions configured, either one is enough — the risk list reads "Any match → Risk-Off", the [two-condition combination](/docs/strategies/two-condition-combination). When the condition clears, the strategy returns to Risk-On. The condition can compare a market series with thresholds or with a second series, or it can be one of three quantitative rules that decide from a model instead — [Hidden regimes (Markov)](/docs/strategies/hidden-regimes-markov), [Clustering](/docs/strategies/clustering) and, on a Combined, [Strategy's own performance](/docs/strategies/strategy-s-own-performance); [condition types](/docs/strategies/condition-types) lists all five. How quickly the switch reaches your holdings depends on the condition's [confirmation delay](/docs/strategies/confirmation-delay) and its [auto-rebalance toggle](/docs/strategies/auto-rebalance-on-flip). ## Does Risk-Off stop the strategy or sell everything? No — Risk-Off does neither. Going Risk-Off swaps in the Risk-Off allocation profile and nothing more: the strategy keeps running, keeps its rebalance schedule, and keeps holding whatever that profile allocates to. It does not pause, halt, or stop, and it does not liquidate to cash unless the Risk-Off profile you configured is itself cash-heavy. If you set the Risk-Off profile to hold less capital at work, the difference shows up as a larger cash reserve — see [how risk conditions can lower the invested portion](/docs/strategies/invested-capital-and-cash-reserve#how-risk-conditions-can-lower-the-invested-portion). ## How does Fincanva handle it? - **Risk-Off is included from the Advanced plan**, at the strategy level and inside a Combined alike. Free and Starter run Risk-On only, so a strategy on either plan never switches; Advanced, Ultimate and Professional include it. See [what each plan includes](/docs/account-security/what-each-plan-includes). - With no risk condition configured, a strategy stays in Risk-On at all times and the single allocation you set applies always ("No Risk conditions configured — this allocation runs at all times."). - The Risk-Off profile is independent: its own method, its own parameters, its own invested portion. It may also be left identical to Risk-On, in which case switching changes nothing. - The allocation summary badges the two states as "Risk-On only" or "Risk-Off set up", and a Risk-Off profile matching Risk-On is labelled "Matches Risk-On". - Fincanva does not say how defensive a Risk-Off profile should be, or when a strategy should be in it. See [Is this financial advice?](/docs/investing-theory/is-this-financial-advice#is-this-financial-advice). ## What does it look like in practice? A strategy holds three equity ETPs, weighted equally, with all of its capital invested — that is its Risk-On profile. You set its Risk-Off profile to the same three instruments but with a lower invested portion, leaving part of the capital in cash. A risk condition then triggers. The strategy switches to Risk-Off at the next rebalance (or immediately, if the condition has **Auto-rebalance** on). It sells down each holding to the smaller target, and the freed capital sits in the cash reserve. It still holds all three ETPs, still rebalances on schedule, and still records positions and results — it is simply carrying less market exposure. When the condition clears, the strategy switches back to the Risk-On profile and the cash is put back to work. Had you instead set the Risk-Off profile identically to Risk-On, this whole sequence would have produced no change at all. **Learn more:** [Risk conditions](/docs/strategies/risk-conditions) Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/robust-worst-case # Robust worst case Robust worst case is an [allocation method](/docs/strategies/allocation-and-allocation-method) that generates a set of possible futures at each rebalance and chooses the weights whose **single worst** future is the least severe. It is the most conservative of the tail-focused methods: expected returns do not enter it at all, and nothing above the floor matters — only how bad the worst scenario gets. The method picker labels it **"Robust worst case"** and describes it as "Picks the weights whose worst scenario is least severe". **Also seen as:** worst-case optimisation, maximin allocation ## What does Robust worst case optimise? It maximises the return of the worst scenario — a maximin rule: $$ \max_{w} \; \min_{s} \; r_s(w) $$ where: $w$ is the set of weights, $s$ runs over the generated scenarios, and $r_s(w)$ is the portfolio's return in scenario $s$ at those weights. In words: for each candidate mix, find its worst scenario; then keep the mix whose worst scenario is the best of all those worsts. Compare [Scenario CVaR](/docs/strategies/minimum-cvar), which looks at the same kind of scenarios but averages the worst share of them. Robust worst case looks at one scenario only, which makes it the cleanest "protect the floor" objective and also the most sensitive to that one extreme scenario. ## Where do the scenarios come from? Each scenario is a possible next period assembled from real days of the [calculation window](/docs/strategies/calculation-window), the same way [Scenario CVaR](/docs/strategies/minimum-cvar) builds its scenarios. Two settings describe them, under **Advanced settings**: - **Number of scenarios** — "How many possible futures are generated at each rebalance." From 100 to 2,000; 500 by default. - **Horizon of each scenario** — "How many trading days each generated future covers." From 5 to 63 days; 21 by default. A kind of market the window never contained cannot appear in any scenario, so the floor it protects is the worst the window's own days can be recombined into. ## How does Fincanva handle it? - Robust worst case is offered at **both levels**: across the instruments of a strategy, and across the strategies of a [Combined](/docs/getting-started/strategy-in-a-combined). - It has no tail share and no other setting beyond the two scenario settings above. It reads the calculation window (**In-sample**, 12 months by default) and does not read the **Covariance matrix** choice. - With a single instrument there is nothing to choose: it receives the whole weight. - The picker marks it "slow to compute": each [rebalance](/docs/backtesting/rebalance) generates the scenarios and solves an optimisation over them. ## Which plan includes Robust worst case? It depends on your plan, at each level where the method is offered. **Inside a strategy** Included from Ultimate upwards. See [what each plan includes](/docs/account-security/what-each-plan-includes). **Inside a Combined** Included from Ultimate upwards. See [what each plan includes](/docs/account-security/what-each-plan-includes). ## What does it look like in practice? Across 500 generated one-month scenarios, three candidate mixes behave like this: | Mix | Average scenario | Worst scenario | |---|---|---| | A | +1.2% | −9.0% | | B | +0.9% | −6.0% | | C | +0.4% | −4.1% | In prose: A has the best average and the deepest floor, C the weakest average and the shallowest floor, and B sits between them on both. Robust worst case chooses **C**, because −4.1% is the least severe worst case — the averages play no part in the choice. A method that weighed the average, such as [Stochastic programming](/docs/strategies/stochastic-programming) with a low risk aversion, could choose differently. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/seed-universe # Seed universe A seed universe is the starting pool of instruments a [screener](/docs/getting-started/screener) filters within — the set it searches before a single filter has run. A screener never scans the whole market unless the seed universe *is* the whole market: it evaluates its filters only against the instruments in the pool it was handed, so the pool is the ceiling on everything the screener can ever return. The app labels this pool **Universe**; what a universe is and how filters narrow one is covered in [Universe](/docs/getting-started/universe). **Also seen as:** screening universe, starting pool, candidate set ## Where does a screener start hunting? In whichever pool you hand it, and there are two ways to hand it one. - **[Universe filters](/docs/screeners/universe-facets).** You choose an asset class and, optionally, narrow it further — on things like where instruments are listed, the exchange, the asset subtype, index membership, sector, and trading currency. Add none of those and the pool is the whole asset class; the app confirms that state with "No further universe filters". - **A hand-picked list of instruments.** The instruments you choose *become* the pool. The screener then filters inside that pool: only instruments you added there are ever considered. Either way the screener's [filters](/docs/getting-started/filter) run inside the pool and can only shrink it. A filter never reaches outside to pull in an instrument the pool excluded — which is why two identical screeners on different seed universes return different [matches](/docs/screeners/matches). ## What happens to my universe filters in Easy mode? The screening card runs in two modes, **Easy** and **Pro**, and moving from Pro to Easy changes how the pool is defined. The switch dialog lists what Easy hides — extra Include screeners, Exclude screeners, custom max-hold and reinvest-delay timings — with a general framing of "Easy mode hides these Pro settings. They're kept and restored if you switch back to Pro:". The universe line is worded differently from the rest: "Your screener's universe filters will be dropped — in Easy, your picked instruments are the universe." So in Easy the pool is your picked instruments, and in Pro the pool can additionally be defined by universe filters. Whether the filters survive a round trip back to Pro is not something the app's copy settles — that open point is recorded as a pending fact on this page rather than guessed at here. ## Why does the seed universe change results? Because it decides what was ever eligible. A screener's output is a subset of its seed universe, so widening the pool can only add candidates and narrowing it can only remove them — and a strategy then allocates across whatever came back, using its [allocation method](/docs/strategies/allocation-and-allocation-method). A screener that looks unproductive may simply have been pointed at a pool with few instruments that could satisfy its filters. ## How does Fincanva handle it? - With no universe filters set, the pool is the entire asset class you chose — "No further universe filters". - A universe edit is a draft until you commit it: **Apply** commits the change, **Cancel** discards it. - Editing the universe of a screen inside a strategy changes only that strategy's own copy of the screener. It never rewrites the saved screener the copy came from — see [Attaching a screener](/docs/strategies/attaching-a-screener-to-a-strategy). - Some asset classes have no further universe filters to offer, in which case only the asset-class choice applies. ## What does it look like in practice? A screener has one filter: revenue growth above the market median. You point it at a seed universe of all US-listed stocks — several thousand [instruments](/docs/getting-started/instrument) — and it returns several hundred matches, which the strategy then allocates across. You keep the identical filter and swap the seed universe for a hand-picked list of 30 instruments. Now at most 30 instruments can be tested, so at most 30 can match, and in practice perhaps twelve do. Same filter, same date, same market data — a different result, because the pool the screener started from was different. Nothing in the first run's several hundred matches can appear in the second unless it was one of your 30. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/simple-moving-average-sma # Simple moving average (SMA) A simple moving average (SMA) is the unweighted mean of a series' last N values, recalculated at each new point, so short-term noise is smoothed away and the underlying trend becomes easier to read. "Simple" means every value in the window counts the same — unlike a weighted or exponential average, which give recent values more pull. In Fincanva a simple moving average is one of the **Indicator** choices on a [risk condition](/docs/strategies/risk-condition): it transforms the instrument's series into its smoothed version before the threshold comparison is made. **Also seen as:** SMA, moving average, MA, rolling average. ## How is a simple moving average calculated? A simple moving average adds up the last N values of a series and divides by N, then repeats that at every new point. $$ \text{SMA}_N(t) = \frac{1}{N} \sum_{i=0}^{N-1} P_{t-i} $$ where: $P_t$ is the series value at time $t$ (the closing price, for a price series), $N$ is the number of periods in the lookback window, and $\text{SMA}_N(t)$ is the mean of the most recent $N$ values including the current one. Each new point drops the oldest value out of the window and takes the newest one in, which is what makes the average "move". ## How does the lookback window change an SMA? A longer window makes the average smoother and slower; a shorter one makes it closer to the raw series. Because the average always looks backwards, it lags the series by construction: after a turn in the underlying series, the SMA keeps carrying older values until they age out of the window, and the longer the window, the longer that takes. This is the standard trade-off of any moving average — less noise, later reaction. ## How does Fincanva handle it? - A simple moving average is one of four **Indicator** options on a risk condition's series, alongside "Raw price", "Percent change", and "Average momentum". - With "Simple moving average" selected, a **Period** field appears next to the indicator; you type the number of periods the average covers. The app then names the resulting series in days — for example "SPY 200-day SMA" in a condition's summary line. - The indicator only transforms the series being watched. Whether the strategy switches to its [Risk-Off](/docs/strategies/risk-on-and-risk-off) allocation is decided by the condition's [thresholds](/docs/strategies/condition-types), not by the average itself. - Fincanva ships a ready-made condition built on this indicator, the "S&P 500 200-day moving average" [risk template](/docs/strategies/risk-templates). ## What does it look like in practice? Take a 200-day simple moving average of a price series. On each trading day, the SMA is the sum of the last 200 closes divided by 200. If the closes over a stretch average out to 400, the SMA reads 400 while the latest close might be 415 — the price sits above its own average, which is what "above the 200-day SMA" means. If the price then falls to 380 and stays there, the SMA does not drop to 380 with it: it eases down day by day as older, higher closes leave the 200-day window and newer, lower ones enter. Shorten the window to 50 days and the same fall pulls the average down roughly four times faster, because each new close carries four times the weight in the mean. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/single-asset-simplification # Single-asset simplification Single-asset simplification is how a strategy that holds exactly one instrument skips allocation altogether: with a single holding there is nothing to weight against, so all of the strategy's invested capital goes to that one instrument. Allocation only becomes a real choice once there are two or more things to split capital between. **Also seen as:** trivial allocation, "nothing to allocate" ## Why does a one-instrument strategy skip allocation? An [allocation method](/docs/strategies/allocation-and-allocation-method) answers "how much of each?", and with one instrument the answer is fixed before you start. The app says so directly: where the method picker would be, the Allocation surface shows "Nothing to allocate yet", explained as "With one instrument and no Risk-Off split, 100% of capital goes to that instrument. Add more instruments or enable a Risk-Off split to make allocation meaningful." The **Single instrument** strategy type takes the same shortcut in the walk-through, which runs only Asset selection and Review — see [choosing a strategy type](/docs/strategies/choosing-a-strategy-type). ## When does allocation matter again for one instrument? Two things bring it back. Enabling a Risk-Off split makes allocation meaningful even with a single holding, because Risk-On and Risk-Off are separate profiles and the Risk-Off profile needs a method of its own — see [risk conditions](/docs/strategies/risk-conditions). Separately, **sizing** is never skipped: the **Leverage** control ("Multiplier on position sizes. 1.00 = no leverage. Range 0.00 – 2.00.") still applies, because how much exposure to take is a different question from how to split it. ## How does Fincanva handle it? - With exactly one instrument and no Risk-Off split, the allocation method picker and the per-method weighting controls are not shown — the weight is fixed at 100% of the invested capital — see [invested portion](/docs/backtesting/invested-portion) for what that share is and what stays in cash. - Adding a second instrument, or enabling a Risk-Off split, restores the full allocation surface. - Sizing stays available in the one-instrument case: leverage scales the position, it does not weight it against anything. ## What does it look like in practice? You build a **Single instrument** strategy on one equity ETP. The walk-through never asks for a weighting method, and the editor shows "Nothing to allocate yet" where the picker would be — the instrument holds 100% of the invested capital by construction, and [weight drift](/docs/backtesting/weight-drift) has nothing to drift against. You then add a second ETP: the method picker appears, and the strategy now needs a rule to decide the split. Nothing about the first version was incomplete — there was only ever one possible answer. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/stochastic-programming # Stochastic programming Stochastic programming is an [allocation method](/docs/strategies/allocation-and-allocation-method) that chooses today's weights by playing out a **tree of possible futures** in which the portfolio is allowed to react: from today, a set of scenarios for the next period; in each of them the portfolio may rebalance, paying a transaction cost; then a second set of scenarios values the result. Today's weights are chosen knowing that later adjustment is possible and costs money — something a single-period optimiser cannot take into account. It is the slowest allocation method in Fincanva. The method picker labels it **"Stochastic programming"** and describes it as "Plans over a tree of scenarios, accounting for the cost of rebalancing". **Also seen as:** multi-stage stochastic optimisation, scenario-tree optimisation ## What does Stochastic programming optimise? It balances the expected final value of the portfolio against how bad its worst outcomes are: $$ \max_{w} \; \mathbb{E}\left[\,W_{\text{final}}\,\right] - \lambda \cdot \text{CVaR}\left(W_{\text{final}}\right) $$ where: $w$ is today's set of weights, $W_{\text{final}}$ is the portfolio's value at the end of the tree, $\mathbb{E}$ averages it over every branch, $\text{CVaR}$ is the average loss of its worst outcomes (see [Minimum CVaR](/docs/strategies/minimum-cvar)), and $\lambda$ is the **Risk aversion** you set. In words: more final value is better, deep bad outcomes are worse, and risk aversion decides how much the second counts against the first. The two preferences do different jobs, and only one of them diversifies. **Risk aversion** is what spreads the weights: at 0 the method looks only at the expected final value, and the best way to maximise an average is to put everything on the single instrument whose scenarios end highest on average — whatever the transaction cost. Raising it makes deep bad outcomes count against a mix, and a mix of instruments whose bad outcomes do not coincide has shallower ones. **Transaction cost** does not diversify by itself: it prices every later rebalance. At 0% a rebalance in any branch is free, so today's weights matter only for the first period; the higher the cost, the more each later change eats into the final value, so the plan favours today's weights that are already worth keeping through the branches and trades less afterwards. ## Which settings does Stochastic programming have? Two preferences are always visible: - **Risk aversion** — "0 = looks only at the expected return; higher = weighs the worst losses more." From 0 to 10; 1 by default. - **Transaction cost** — "The method takes it into account when deciding whether to move the weights." From 0% to 1%; 0.1% by default. It shapes the plan only; the costs charged in the backtest itself are set separately — see [Transaction cost](/docs/backtesting/transaction-cost). Three more describe the tree, under **Advanced settings**: - **First-stage scenarios** — "How many possible futures for the first period." From 20 to 200; 50 by default. - **Second-stage scenarios** — "For each first-stage scenario." From 5 to 40; 10 by default. - **Length of each stage** — from 5 to 63 days; 21 by default. The second-stage scenarios are one shared set used under every first-stage branch, so the value of planning comes from the trading cost and the shape of the risk rather than from forecasting what follows each branch. Raising the second-stage count is the lever when the tail feels thin. ## Why is Stochastic programming so slow? Because at every [rebalance](/docs/backtesting/rebalance) it builds the scenario tree and solves one optimisation over all of it, and that optimisation grows with the number of instruments times the number of scenarios. The picker marks it "very slow to compute", the only method with that mark, and the method's card says why: "Very slow to compute: it builds a scenario tree at every rebalance." Large baskets are where it hurts. At the default tree, a strategy that can hold more than 30 instruments pushes the work past the point the app considers reasonable, and the card shows the warning **"Large basket for this method"**, naming the basket size, the threshold, and the two ways out: reduce the instruments or the first-stage scenarios, or choose CVaR on scenarios. The threshold moves with the tree — fewer first-stage scenarios allow a larger basket — and a tree that is too large on its own, whatever the basket, gets its own message: "The scenario tree alone is too large: with this many first- and second-stage scenarios, the computation may take a very long time whatever the basket." Both are advice, not refusals: the backtest still runs. ## How does Fincanva handle it? - Stochastic programming is offered at **both levels**: across the instruments of a strategy, and across the strategies of a [Combined](/docs/getting-started/strategy-in-a-combined). Inside a Combined the large-basket advice counts strategies instead of instruments. - It reads the [calculation window](/docs/strategies/calculation-window) (**In-sample**, 12 months by default) and does not read the **Covariance matrix** choice. - With a single instrument there is nothing to plan: it receives the whole weight. - How long a backtest takes also depends on your plan's compute power — see [compute time](/docs/backtesting/compute-time). ## Which plan includes Stochastic programming? It depends on your plan, at each level where the method is offered. **Inside a strategy** Included from Ultimate upwards. See [what each plan includes](/docs/account-security/what-each-plan-includes). **Inside a Combined** Included from Ultimate upwards. See [what each plan includes](/docs/account-security/what-each-plan-includes). ## What does it look like in practice? A strategy holds 10 instruments and keeps the default tree: 50 first-stage scenarios, each followed by the same 10 second-stage scenarios, every stage 21 trading days long. - With **Risk aversion 0**, the plan has no reason to diversify, and all the capital goes to the instrument whose scenarios end highest on average. Raising **Transaction cost** alone does not change that: the plan still holds one instrument. - With the defaults — **Risk aversion 1** and **Transaction cost 0.1%** — the worst outcomes now count against a concentrated bet, so the weights spread across several instruments; the cost then makes the plan prefer weights it will not need to trade away in most branches. Let the same strategy hold up to 40 instruments at the same tree and the card warns: "This strategy can hold up to 40 instruments. The computation grows with instruments × scenarios: above 30 instruments the simulation may take a very long time. Reduce the instruments or the first-stage scenarios, or choose CVaR on scenarios." Cutting the first-stage scenarios to 20 brings the tree back under the line for 40 instruments; switching to [Scenario CVaR](/docs/strategies/minimum-cvar) removes the tree altogether. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/stop-loss # Stop loss Stop loss is an automatic exit that closes a position once its loss reaches a threshold you set, such as a 10% loss, capping how far the position can fall before it is sold. It is the loss-side exit: it acts on one position at a time and looks only at how far that position is down — not at how long it has been held, which is [max hold](/docs/strategies/max-hold-months), and not at a gain, which is [take profit](/docs/strategies/take-profit). **Also seen as:** loss limit, SL. ## How does stop loss decide when to close? Stop loss closes a position once its loss reaches the threshold you set. The threshold is entered as a negative percentage (e.g. −10%) because it describes a loss, so a value closer to −100% keeps a position open longer, while one closer to −5% closes it sooner. Where take profit caps the upside, stop loss caps the downside. The loss is counted from the price the position was **first** opened at and keeps counting through every rebalance that keeps the position, exactly as for [take profit](/docs/strategies/take-profit#how-does-take-profit-decide-when-to-close). The check is not tied to the rebalance schedule: the loss is read on the position's own price bars, so a stop loss can close a position between two rebalances. It closes on the first bar that reaches the threshold — at the threshold level itself, or at that bar's open when the bar opens already past it, which is how a stop-out can book a loss larger than the threshold after a gap. [Execution time](/docs/strategies/execution-time#when-does-a-modelled-trade-fill-within-a-bar) has the full fill rule. ## What if one bar reaches both the stop-loss and the take-profit level? Only one of them closes the position, and the bar decides which. If the bar **opens** already past one of the two levels, that one wins. Otherwise a daily bar does not say which extreme came first, so Fincanva follows one fixed convention: a bar that closed **at or above** its open is taken to have reached its low first, and a bar that closed **below** its open its high first. For a long position that means a stop-out on a rising bar and a take profit on a falling one; for a short position it is the other way round. ## Can a stopped-out instrument be bought again? Yes, but never on the bar that closed it. New positions are opened when the strategy rebalances, and at no other time, so the earliest the same instrument can come back is a later rebalance at which the strategy's rules select it again. If you set a [reinvest delay](/docs/strategies/reinvest-delay), the instrument stays out of the strategy's choices until that delay has passed, counted from the day of the stop-out. ## How does Fincanva handle it? - Off by default; the threshold is entered as a **negative percentage** (e.g. −10%), and when enabled it starts at **−30%**. - Adjustable across a range of **−100% to −5%**, shown as a percentage (suffix "%"). - It sits on the **Position exits** card, described there as "Auto-close rules applied to each position". - Values outside the band are blocked with a "Stop loss must be between −100% and −5%." validation message. - A position closed by this rule is recorded with the [exit reason](/docs/strategies/exit-reason) **Stop loss**. ## What does it look like in practice? A position is opened at a price of 100 with stop loss set to close at a **10% loss**. When the price falls to 90, the position's return is −10%, which reaches the threshold, so the position is sold and the loss is capped at that point. Had stop loss instead been set to a 20% loss, the same position at −10% would remain open and could fall further before the rule closed it. *Fincanva does not recommend a stop-loss level, or whether to use one at all.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/strategy-s-own-performance # Strategy's own performance Strategy's own performance is a quantitative risk rule for a [Combined](/docs/getting-started/combined) that watches the Combined's own value instead of a market series, and switches it to its Risk-Off allocation when that value becomes too volatile, falls too far from its peak, or drops below its moving average — whichever of the three metrics you pick. It exists only at the Combined level. It is one of the three rules in the **Quantitative regimes** group of the risk condition builder, where the app describes it as "Watches your combined strategy itself, not an index: you move to Risk-Off when it gets too turbulent, falls too far from its peak or breaks its trend." **Also seen as:** portfolio-based rule, equity-curve trading, portfolio stop ## What does the rule watch? The rule watches your Combined as it would have run if it had always stayed Risk-On, with no costs — the app's note reads "Always held Risk-On, with no costs. No series to choose." It does not watch the Combined's actual curve, because that curve already reflects the rule's own switches: judging it would make every switch change the signal that caused it. Holding the watched version permanently Risk-On keeps the signal independent of the decision it drives. ## Which metrics can it use? The rule reads one **Metric**, and each has its own test on the watched value $P_t$: $$ \text{Realized volatility:}\;\; \sigma_t \ge \theta \qquad \text{Drawdown:}\;\; 1 - \frac{P_t}{\max_{s \le t} P_s} \ge \theta \qquad \text{Trend vs moving average:}\;\; P_t < (1 - g) \times \overline{P}_{t,n} $$ where $P_t$ is the watched value on day $t$, $\sigma_t$ its annualised volatility over the window, $\max_{s \le t} P_s$ its highest value so far, $\overline{P}_{t,n}$ its average over the last $n$ days, $\theta$ the threshold you set, and $g$ the gap from the average. In words: Risk-Off while the Combined swings more than you set, sits at least the set share below its [peak](/docs/analysis/max-drawdown), or trades below its moving average by more than the gap. | Metric | Window | Threshold | Risk-Off when | |---|---|---|---| | **Realized volatility** (default) | 10–252 trading days, default 21 | annual volatility, 5%–100%, default 20% | "volatility exceeds this value" | | **Drawdown** | none — "Not needed: measured from the previous peak." | loss from peak, 2%–50%, default 10% | "the Combined loses at least this share from its peak" | | **Trend vs moving average** | moving average of 10–252 days, default 200 | gap from the average, 0%–10%, default 0% | "the Combined falls below its moving average by more than this gap" | The same three tests in prose: volatility uses a trailing window and a yearly figure; drawdown needs no window because it is always measured from the running peak; the trend test with a gap of 0% fires as soon as the Combined is below its average. ## How does Fincanva handle it? - **Combined only.** The rule is offered at the Combined level and never inside a single strategy; there is no series to choose. - **About twice the calculation time.** To decide, the backtest first simulates the Combined held Risk-On with no costs, then runs it for real. The builder shows it as a notice: "About twice the calculation time." and "That is why the simulation does not start on its own: you start it." — after a change, the Combined waits for you to start the backtest. - **It stays Risk-On until its window is full**, and each test uses only data up to the day it judges. - **One threshold, no hysteresis.** The [confirmation delay](/docs/strategies/confirmation-delay) is the brake against switching back and forth; its hint on this rule reads "This rule has a single threshold: the delay is your brake against switching too often. 0 = immediate." **Auto-rebalance** works as it does on any condition. - **Strategy's own performance is included from the Ultimate plan**, at the Combined level. On Advanced it still appears in the list, tagged with the plan level that includes it. See [what each plan includes](/docs/account-security/what-each-plan-includes). - In the list of risk conditions a saved rule shows "Strategy's own performance" with its metric and its threshold, for example "≥ 20%" with "21-day window", or "< average" with "200-day moving average". ## What does it look like in practice? A Combined holding two strategies gets a Strategy's own performance rule with **Drawdown** at 15% and a confirmation delay of 1 week. Its always-Risk-On version peaks at 120,000. Over the next two months it falls to 108,000 — a 10% drawdown, under the threshold, so nothing happens. It keeps falling to 101,000: $1 - 101{,}000 / 120{,}000 \approx 15.8\%$, at or above 15%, so the rule asks for Risk-Off, and a week later the Combined switches to its Risk-Off allocation. It returns to Risk-On once the always-Risk-On version climbs back within 15% of its peak — above 102,000 — and the delay has passed. With **Realized volatility** at 20% instead, the same stretch would have switched only if the Combined's 21-day volatility rose to 20% a year, however far it had fallen. The figures are illustrative, not a suggested setting. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/take-profit # Take profit Take profit is an automatic exit that closes a position once its gain reaches a threshold you set, such as +20%, locking in the return at that level. It is the gain-side exit: it acts on one position at a time and looks only at how far that position is up — not at how long it has been held, which is [max hold](/docs/strategies/max-hold-months), and not at a fall, which is [stop loss](/docs/strategies/stop-loss). **Also seen as:** profit target, TP. ## How does take profit decide when to close? Take profit closes a position once its return since entry meets or passes the take-profit percentage you set. The return it measures is the position's own gain from the price it was opened at, not the strategy's overall return, so each holding reaches its target on its own schedule. A higher take-profit number means the position has to gain more before the rule closes it, and a lower one closes it sooner. The gain is counted from the price the position was **first** opened at, and it keeps counting through every rebalance that keeps the position: resizing a holding at a rebalance does not restart it. For a [short position](/docs/strategies/direction-long-only-long-short-short-only), a fall in price is the gain. The check is not tied to the rebalance schedule: the return is read on the position's own price bars, so a take profit can close a position between two rebalances. It closes on the first bar that reaches the threshold — at the threshold level itself, or at that bar's open when the bar opens already past it; [execution time](/docs/strategies/execution-time#when-does-a-modelled-trade-fill-within-a-bar) has the full fill rule. If the same bar also reaches the stop-loss level, [stop loss](/docs/strategies/stop-loss#what-if-one-bar-reaches-both-the-stop-loss-and-the-take-profit-level) explains which of the two closes the position. $$ r_t \ge \text{TP} $$ where: $r_t$ is the position's return since it was opened and $\text{TP}$ is your take-profit percentage. ## How does Fincanva handle it? - Off by default; when you turn it on it starts at **150%**. - Adjustable from **5% to 1000%**, entered as a positive percentage (suffix "%"). - It sits on the **Position exits** card, described there as "Auto-close rules applied to each position". - Values outside the band are blocked with a "Take profit must be between 5% and 1000%." message. - A position closed by this rule is recorded with the [exit reason](/docs/strategies/exit-reason) **Take profit**. The instrument can be bought again only at a later rebalance, and not before the [reinvest delay](/docs/strategies/reinvest-delay) has passed if you set one. ## What does it look like in practice? A position is opened at a price of 100 with take profit set to **20%**. When the price reaches 120, the position's return is +20%, which meets the threshold, so the position is closed and the +20% gain is locked in. Had take profit instead been set to 25%, the same position at +20% would stay open and keep running toward the higher target. *Fincanva does not recommend a take-profit level, or whether to use one at all.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/two-condition-combination # Two-condition combination Two-condition combination is how a strategy's two [risk conditions](/docs/strategies/risk-condition) work together: they combine with **Or**, so the strategy switches to its Risk-Off allocation as soon as *either* condition is triggered — the two do not have to agree. A strategy holds at most two conditions, a first and a second. This page covers only how the two are joined; what one condition watches and how it is built is on the risk-condition page. **Also seen as:** Or logic, Any match → Risk-Off ## How do two risk conditions combine? They combine with Or: whichever condition triggers flips the strategy to [Risk-Off](/docs/strategies/risk-on-and-risk-off), and the other one's state does not matter. The app labels this above the conditions list — with two conditions configured it reads "Any match → Risk-Off"; with one, "Match → Risk-Off"; with none, "Always Risk-On" — and the divider drawn between the two condition rows reads "Or". The empty state states the baseline: "Without a condition, the strategy stays in Risk-On at all times." ## Can you require both conditions to fire? No. There is no And option in the app today, so you cannot ask a strategy to go defensive only when both conditions are triggered at once — two conditions always combine with Or. A stricter trigger has to come from the conditions themselves rather than from the way they are joined: a tighter threshold, a longer [confirmation delay](/docs/strategies/confirmation-delay) before a flip counts, or a single **Double series** condition that already encodes a relationship between two instruments. See [risk conditions](/docs/strategies/risk-conditions) for what one condition can watch. ## How does Fincanva handle it? - A strategy holds at most two risk conditions; there is no third slot. - The two are joined with Or, and the join is not configurable — no And/Or picker exists in the app. - Each condition keeps its own behavior settings, so one can act immediately while the other waits out a confirmation delay before it counts. - Removing the first condition promotes the second into its place rather than leaving a gap. - Because either condition alone is enough, adding a second condition makes a strategy flip to Risk-Off *more* often, not less. ## What does it look like in practice? A strategy watches two things. The first condition is a single-series condition on a volatility index that triggers when the index crosses the Risk-Off threshold you set. The second is a "Double series" condition pitting a long-dated Treasury series against a short-dated one, triggering when the operator you chose is satisfied. In a month where volatility spikes but the two Treasury series barely move, the first condition alone is enough — the strategy goes Risk-Off. In a later month where volatility is calm but the Treasury comparison flips, the second condition alone does it. There is no month in which both are needed, and no way to ask for both. If you wanted the strategy to hold its Risk-On allocation until *both* signals agreed, the two-condition slots cannot express that; [Risk-Off canonicalization](/docs/strategies/risk-off-canonicalization) explains what does happen when there is nothing to switch into. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/strategies/whipsaw # Whipsaw Whipsaw is what happens when a rule flips a strategy one way, the market reverses shortly after, and the rule flips it back: the strategy sells near a temporary low and buys back near the recovery high, ending in the position it started from and poorer for the round trip. Whipsaw is the cost of sensitivity — the same responsiveness that lets a rule react early to a real change also makes it react to brief moves that mean nothing. Whipsaw is a property of the *rule's timing*, not of the market: the same choppy stretch whipsaws a fast trigger repeatedly and leaves a slower one untouched. **Also seen as:** getting whipsawed, false signal, chop ## Why does a fast trigger cause whipsaw? A fast trigger causes whipsaw because it cannot tell a brief dip from the start of a lasting decline — both look identical at the moment the threshold is crossed. So the trigger fires on both, and the two cases have opposite consequences: on a lasting decline the early exit avoids further losses, while on a brief dip the exit is followed by a re-entry at a higher price, so the strategy pays the gap between the two prices plus two rounds of trading costs. Because brief dips are far more common than regime changes, a very sensitive rule collects many small round-trip losses in exchange for occasionally being early on a real one. The damage compounds in a *choppy* market — one that moves sharply up and down without trending. Each swing crosses the threshold again, so a strategy can be whipsawed several times inside a few months, and the market can finish the period higher than it started while the strategy finishes lower. ## How does a fast trigger get whipsawed twice? Take a strategy that goes defensive whenever the index it watches falls 5% below its recent average, and returns to normal as soon as the index recovers, with no waiting period. | Week | Index | What the rule does | Result | |---|---|---|---| | 1 | 100 | invested | — | | 3 | 94 | condition triggers, strategy sells into cash | out at 94 | | 6 | 101 | condition clears, strategy buys back | back in at 101, having missed 7 points | | 9 | 95 | condition triggers again, strategy sells | out at 95 | | 12 | 102 | condition clears again, strategy buys back | back in at 102, having missed 7 points | The index ended the twelve weeks 2% above where it began. The strategy sat out both recoveries and bought back higher both times, giving up roughly 7% of the position on each round trip — around 14% in total — plus four sets of trading costs, and it holds exactly what it held in week 1. Nothing in the equity curve labels this as whipsaw; it shows up only as an unexplained gap between the strategy's result and the market's over a period in which both ended up. {/* VISUAL: chart — twelve-week price line with the Risk-Off and Risk-On threshold levels drawn flat across it and four sell/buy markers, plus a greyed copy showing what a three-week confirmation delay would have skipped — tracked in VISUAL_BACKLOG */} ## What does Fincanva give you to reduce whipsaw? Fincanva gives you two controls on a [risk condition](/docs/strategies/risk-condition) that both work by making a flip harder to complete. **[Confirmation delay (weeks)](/docs/strategies/confirmation-delay)** sets how long a flipped condition must hold before the strategy acts on it — its hint reads "0 = act immediately." and it accepts 0 to 12 weeks. In the worked example above, a delay of three weeks would have let both dips pass unacted on, because each one had already reversed before the delay elapsed. The second is that a condition carries **two** thresholds rather than one: the Risk-Off threshold is where the strategy switches out, and the Risk-On threshold is where it switches back. Setting them apart means the level that would take the strategy back in is not the same level that took it out, so a series hovering around a single point does not flip the strategy repeatedly. Which shape the condition takes — one series read against thresholds, or two series compared — is covered in [condition types](/docs/strategies/condition-types). See [How the Risk-Off and Risk-On thresholds work](/docs/strategies/risk-conditions) for what each threshold does, and [When risk management changes a strategy](/docs/strategies/when-risk-management-changes-a-strategy) for the reaction-speed trade-off in full. Neither control removes whipsaw — both trade it against reacting later to a flip that turns out to be real. Fincanva does not flag whipsaws in a backtest's output, so a run gives no count of how many round trips a condition produced. ## What counts as a good value? Whipsaw has no metric attached to it, so there is no value to read. What a backtest lets you compare is the same strategy run with different confirmation delays and thresholds: a rule whipsawing heavily tends to show a lower total return than the market over stretches when the market rose, alongside a [max drawdown](/docs/analysis/max-drawdown) no smaller than a strategy that never flipped. Which trade-off between responsiveness and whipsaw suits a given strategy is a judgement Fincanva does not make for you. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/changelog # A volatility target for Combined strategies, and more room for leverage **2026-09-24** · combined-strategies · 2026.09 A Combined's allocation profile can now carry a [volatility target](/docs/backtesting/volatility-target), which rescales the invested portion at every rebalance to keep the Combined's volatility near a yearly level you choose; it is included from Advanced. The [invested portion](/docs/backtesting/invested-portion) of a Combined can now go above 100%, borrowing the difference, within the plan's leverage ceiling. [Leverage](/docs/backtesting/leverage) above 1.00× on a single strategy now starts at Starter, and the ceiling is higher on every paid plan. The ceilings each plan sets are on [what each plan includes](/docs/account-security/what-each-plan-includes). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/changelog # Black-Litterman becomes its own allocation method **2026-09-25** · strategies · 2026.09 [Black-Litterman](/docs/strategies/black-litterman) is now an allocation method of its own in the picker, listed right after [MPT (Markowitz)](/docs/strategies/modern-portfolio-theory), instead of a switch inside MPT; the MPT settings no longer show a Black-Litterman switch. It aims at **Optimal** or **Max return** and keeps every MPT setting, and moving between the two methods keeps your settings. It is still included wherever MPT is. A strategy saved with the old switch on and the **Min volatility** target is shown as MPT (Markowitz) and keeps running exactly as saved. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/changelog # Black-Litterman, Resampled MPT and a choice of risk estimator **2026-09-24** · strategies · 2026.09 [MPT (Markowitz)](/docs/strategies/modern-portfolio-theory) has two new options. [Black-Litterman](/docs/strategies/black-litterman) replaces the noisy average returns with a steadier estimate tilted toward momentum, and comes with the method; [Resampled](/docs/strategies/modern-portfolio-theory#what-does-the-resampled-option-do) repeats the optimisation on many resampled histories and averages the weights, and is included from Ultimate. Every method built on a covariance estimate now shows a **Risk estimation** control with eight estimators — see [risk estimation](/docs/strategies/covariance-matrix); the basic ones come with the method and the three advanced ones start at Ultimate. What each plan unlocks is on [what each plan includes](/docs/account-security/what-each-plan-includes). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/changelog # Eight allocation methods for tail risk and diversification **2026-09-24** · strategies · 2026.09 Eight new allocation methods aim at the bad outcomes rather than at average risk, or at spreading risk as widely as possible: [Maximum Diversification](/docs/strategies/maximum-diversification), [Minimum CVaR](/docs/strategies/minimum-cvar) and its [Scenario CVaR](/docs/strategies/minimum-cvar#what-is-scenario-cvar) variant, [Minimum MAD](/docs/strategies/minimum-mad), [Conditional Drawdown at Risk](/docs/strategies/conditional-drawdown-at-risk), [Entropic Value at Risk](/docs/strategies/entropic-value-at-risk), [Robust worst case](/docs/strategies/robust-worst-case) and [Stochastic programming](/docs/strategies/stochastic-programming). Each works both inside a strategy and across the strategies of a Combined. They are included from Ultimate — see [what each plan includes](/docs/account-security/what-each-plan-includes). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/changelog # Equal and Clear all sit above your weights, with one rule everywhere **2026-09-23** · strategies · 2026.09 **Equal** and **Clear all** now sit directly above the weights they rewrite — the instruments table inside a strategy, and the Strategies table inside a [Combined](/docs/getting-started/combined) — instead of on the Allocation card below. Every [relative weight](/docs/strategies/fixed-weights) now follows one rule wherever you set it: up to ±999, decimals allowed, and a weight that sums to zero saves with a yellow warning instead of being refused. A fresh [Ranking-Based](/docs/strategies/ranking-based) strategy starts on Equal Weight. See [combined weighting](/docs/strategies/combined-weighting) and [strategy alerts](/docs/backtesting/strategy-alerts). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/changelog # Quantitative risk rules and the regime timeline **2026-09-24** · strategies · 2026.09 The risk condition builder has a new **Quantitative regimes** group with three rules. [Hidden regimes (Markov)](/docs/strategies/hidden-regimes-markov) and [Clustering](/docs/strategies/clustering) learn from one series when the market has been calm or turbulent, and are included from Advanced, at the strategy level and inside a Combined; [Strategy's own performance](/docs/strategies/strategy-s-own-performance) watches a Combined as a whole, and is included from Ultimate. Whenever a risk condition is active, the new [regime timeline](/docs/analysis/regime-timeline) under the growth chart on **Performance Metrics** shows the days spent in Risk-On and in Risk-Off. What each plan unlocks is on [what each plan includes](/docs/account-security/what-each-plan-includes). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/changelog # Single and Combined strategies are now separate sections **2026-07-13** · strategies · 2026.07 The library now presents **Single** and **Combined** as separate sidebar sections. Building one strategy directly and combining several strategies into one book are now distinct workflows, each with its own library. To build a single strategy, see [Create a strategy and choose its instruments](/docs/strategies/create-a-strategy-and-choose-its-instruments). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/changelog # Switch a Combined's component off and back on **2026-09-23** · combined-strategies · 2026.09 A [Combined](/docs/getting-started/combined)'s Strategies list now lets you pause a component and bring it back on: a paused component moves into a **Kept aside** group, and only the components still switched on count against your plan's limit. Bringing one back on is refused only where saving would already refuse it — see [what each plan includes](/docs/account-security/what-each-plan-includes). A single strategy switched off the same way shows **Switch back on** in its own settings. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/changelog # The Risk estimation setting is now called Covariance matrix **2026-09-25** · strategies · 2026.09 The allocation setting that chooses how a method estimates volatilities and correlations from history is now labelled **Covariance matrix**, because that matrix is what it sets. Nothing else changed: the same eight estimators, the same defaults, and the same plans. The chips that flag a setting different from the default now read "Covariance: …" instead of "Estimate: …", and the docs page moved with it — see [covariance matrix](/docs/strategies/covariance-matrix). Links to the old page still land on the new one. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/changelog # Three hierarchical allocation methods **2026-09-24** · strategies · 2026.09 A strategy can now allocate with three hierarchical methods, which group instruments by how alike they move before splitting the capital between the groups: [Hierarchical Risk Parity](/docs/strategies/hierarchical-risk-parity), [Hierarchical Equal Risk Contribution](/docs/strategies/hierarchical-equal-risk-contribution) and [Nested Clustered Optimization](/docs/strategies/nested-clustered-optimization). They work inside a strategy, not across the strategies of a Combined. All three are included from Advanced — see [what each plan includes](/docs/account-security/what-each-plan-includes). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/screeners/backtest-a-screener # Backtest a screener A screener backtest re-screens the market month by month over history and measures what the matches went on to return over six holding horizons, against a benchmark. You run it from the screener's **Backtest** tab. ↗ See this in Fincanva — a screener's Backtest tab ## Before you start You need a saved screener with at least one filter. With none, the **Backtest** tab shows "Backtest your screening rules" over "Add at least one screening rule in the filter bar above, then run it to see how it would have performed against the market, 2000 to today." — the tab is always there, it simply has nothing to run yet. A backtest runs against the screener's **last saved** filters and universe, so save your edits before running one. ## Steps 1. Open the screener and select the **Backtest** tab. Before its first run the tab shows a faded preview of the finished layout behind "See how this screener beat the market". 2. Select **Run backtest** — or **Backtest**, which is what the header's primary action reads once the screener has no unsaved changes. 3. Wait. The action reads `Backtesting {percent}%` and the panel shows "Computing performance across six horizons" with the same percentage. **Cancel** stops watching the run; it does not undo anything, and a result already on screen stays. 4. Read the verdict band when it finishes, then the panels below it. 5. Re-run it after changing filters, using **Re-run backtest** beside the out-of-date banner. ## What you should see The verdict band states the result as an edge over the benchmark — a hero figure read as "annualized above the benchmark" or "annualized below the benchmark", the horizon it was best at, and the benchmark's own name under **Benchmark universe**. Below it, **Edge by holding horizon** charts that edge across all six horizons, **What happens after selection** plots the screener's picks against the benchmark from the moment of selection, and **Which filters earn their place** breaks the result down filter by filter. A trust strip closes the view with "Rebalanced monthly" and "Past performance does not guarantee future results". Every figure in the band is an edge, so it is quoted in percentage points rather than as a return. A screener backtest that beat its benchmark is not a prediction and not a recommendation — see [Is this financial advice?](/docs/investing-theory/is-this-financial-advice#is-this-financial-advice). ## What exactly do the six horizons measure? They measure what the matched instruments returned over the 1, 2, 3, 6, 12, and 24 months after each monthly screening date, averaged across every such date in the tested history. So a screener backtest has six per-horizon averages and no equity curve: it never builds a portfolio, it repeats the screen and follows what came out. That is a different question from a strategy [backtest](/docs/getting-started/backtest), which replays allocation, rebalancing, and exits to produce one path — [screener backtest](/docs/screeners/screener-backtest) covers the distinction, and [holding horizon](/docs/screeners/holding-horizon) covers the windows themselves. ## Why is my result measured against a benchmark I did not choose? Because a screener's return means nothing on its own — the same list of matches looks strong in a rising market and weak in a falling one, and only the gap against a benchmark separates the filters from the market they ran in. The band names the benchmark it used under **Benchmark universe**. [The screener backtest benchmark](/docs/screeners/screener-backtest-benchmark) covers what that choice does to the numbers you read. ## Why did my result come back instantly the second time? Because a screener backtest you have already run is served from the result already held rather than computed again. That lasts until the daily market-data refresh, after which the first run of the new day computes in full and its figures can shift slightly even though you changed nothing. [Screener execution and caching](/docs/screeners/screener-execution-and-caching) covers both halves. ## Common problems ### The banner reads "Out of date — filters changed since the last backtest. Showing the previous run." You edited a filter after the run. Fincanva keeps the earlier result and dims it rather than deleting it, so you can still read it while knowing it belongs to the earlier filter set. Select **Re-run backtest** beside the banner to measure the filters you have now. ### The run failed: "This backtest couldn't complete" The body reads "Something went wrong while running it. Your screener and filters are unchanged — try again." Nothing was lost. Select **Retry backtest**. ### The band reads "Refreshing data…" instead of a percentage Market data is being loaded, and the run waits for it rather than answering from a partial picture. It keeps retrying on its own — there is nothing for you to do. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/screeners/build-a-screener # Build a screener You build a screener in its workspace: set the universe it draws from, add one or more filter conditions, then name it and save it to your library. ↗ See this in Fincanva — Screeners, on the filter strip ## Before you start No prerequisites — a screener is independent of any strategy, and you can build one before you have built anything else. Opening **Screeners** always takes you to a fresh, unsaved workspace titled "Untitled screener", so there is nothing to create first. ## Steps 1. Open **Screeners**. You land in an empty workspace called "Untitled screener" — a new draft, not a list of saved screeners. Your saved ones live in the **Library** pane in the sidebar, under its **Mine** and **Public** tabs. 2. Pick the asset type on the left of the filter strip: **Stocks**, **ETPs**, or **Crypto**. A new screener starts on **Stocks**. Changing it later asks "Switch asset type?" first, because each asset type has its own universe filters. 3. Narrow the [universe](/docs/getting-started/universe) if you want less than everything the asset type covers. The strip's chips — **Asset type**, **Country**, **Exchange**, **Asset subtype**, **Index**, **Sector**, **Currency** — each open a list; a chip you have not touched reads **All**, and **Reset** puts one back to its default. 4. Select **Add filter**. The flyout has three columns — **Category**, **Subcategory**, **Filter** — or you can type in **Search filters…** instead. Categories are **Universe**, **Fundamental**, **Technical**, **Macro**, and **Market & Sector**; a sixth, **Custom**, is listed but not usable yet ("Custom filters are post-V1."). 5. Pick a filter. It arrives as a chip at its own default condition and opens its editor. Choose the relation you want across the editor's tabs — **vs Value**, **vs Aggregate**, **vs Lagged Self**, **Highest / Lowest**, **Between** — and set the value. 6. Read the **You're saying** line before you commit. It restates the condition as a sentence, rewritten as you type, so you can check the rule says what you meant. Until you have picked values it reads "Choose values to see what this filter says." 7. Select **Apply**. The chip joins the strip and the **Matches** count updates. 8. Repeat steps 4–7 for each further condition. Conditions combine with AND — an instrument has to satisfy every one of them. 9. Select **Save**. A new screener asks "Name your screener" first; type a name and confirm with **Save**. ## What you should see The screener's name replaces "Untitled screener" in the header, `Last edited {when}` appears beside it, and the **Discard** button disappears because there are no unsaved changes left. The screener now shows in the **Library** pane under **Mine**, and the **Matches** tab carries the count of instruments that pass every condition. Reading that list, and the columns it offers, is covered in [Read your matches](/docs/screeners/read-your-matches). Fincanva does not tell you which filters to screen with, and a screener that returns a short, attractive-looking list is not a recommendation to buy anything on it — see [Is this financial advice?](/docs/investing-theory/is-this-financial-advice#is-this-financial-advice). ## How do I keep only the top few instruments rather than everything that passes? Use the **Highest / Lowest** relation on the filter you want to rank by, and set its **Rank**. That is the only ranking mechanism a screener has — there is no separate ordering or sort-weight step. "Market Cap → Highest → Rank 50" keeps the fifty largest instruments still standing when the ranking runs — which is not the same as the fifty largest overall, because a screener applies its conditions in the order they sit in the strip. [Sequential filtering and Top-N ranking](/docs/screeners/sequential-filtering-and-top-n-ranking) covers what that order does. ## Where do the extra Period, Lag, and Multiplier fields come from? They are the filter editor's optional **Advanced** panel, and only filters that support them show them. They shift or scale the reading before the comparison happens rather than changing the comparison itself; **Reset to defaults** puts them back. What each one does is covered in [lag, period, and multiplier](/docs/screeners/lag-period-and-multiplier). ## Common problems ### Why is Save greyed out on a screener I just started? You'll see "Add a filter or change the universe to enable Save." An untouched draft has nothing to persist, so add at least one filter, or narrow the universe, and Save becomes available. ### Why can't I save changes to a screener from the Public tab? You'll see "Public screener — use Copy to Mine to create your own version." A Public screener is Fincanva's, not yours, so it is read-only. Select **Copy to Mine** to get your own editable copy, then build on that. ### The results area says "No instruments match your filters" Nothing has gone wrong — the conditions together are simply too tight, or two of them contradict each other. What the empty state offers you is covered in [Read your matches](/docs/screeners/read-your-matches#the-list-is-empty-no-instruments-match-your-filters). ### I want to use my screener in a strategy — do I build it here? You can build it either way, and this workspace is not the only place. Attaching a screener to a strategy, including attaching a blank one and building it directly on the strategy, is its own flow — see [Attaching a screener to a strategy](/docs/strategies/attaching-a-screener-to-a-strategy). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/screeners/read-your-matches # Read your matches The **Matches** tab lists every instrument that passes all of a screener's conditions, in a table you can re-column, search, sort, and page through. ↗ See this in Fincanva — Screeners, on the filter strip ## Before you start No prerequisites. A screener with no filters at all still returns matches — the whole universe of its asset type — so the table has something to show from the moment you open one. Building the filters that narrow it is covered in [Build a screener](/docs/screeners/build-a-screener). ## Steps 1. Open the screener and select the **Matches** tab. The tab carries the count of instruments currently passing every condition. 2. Choose the column set with the tabs above the table: **Overview**, **Returns**, **Fundamentals**, **Ratios**, **Dividend**. Each one is a different set of columns over the same matches, not a different result. 3. Adjust the columns within a tab with **Columns**, which turns individual columns on and off for that tab. 4. Find one instrument with the search box — "Search ticker or name". 5. Sort by any column by selecting its header. Selecting a numeric column sorts it high-to-low first; a text column sorts A-to-Z first. Selecting the same header again reverses it. Until you select one, the list is ordered by **Market Cap**, largest first. 6. Move through the list with the pager at the foot of the table. Page sizes are 25, 50, and 100, and it opens at 50. The range beside it — `{from}–{to} of {total}` — tells you where you are. ## What you should see The table lists one row per matching [instrument](/docs/getting-started/instrument), under the columns of the tab you picked. **Overview** is identity and size — **Symbol**, **Asset type**, **Asset subtype**, **Market Cap**, a **1Y** sparkline, **Exchange**, **Country**, **Sector**, **Industry** — while the other return windows (**YTD**, **1M**, **MTD**) sit on **Returns** with **Sharpe** and **Beta**. While a run is in flight the area reads "Refreshing matches…" and the previous list stays on screen, dimmed, rather than blanking. What each column measures is covered in [results columns](/docs/screeners/fundamental-metric-columns). The picture beside each row is [its own logo, or a flag for its recorded origin](/docs/getting-started/instrument-logo). A match is a statement about what passed your rules today, not a view about what any of these instruments will do — see [Is this financial advice?](/docs/investing-theory/is-this-financial-advice#is-this-financial-advice). ## What order does the list open in? Matches open ordered by **Market Cap**, largest company first, and every column tab opens the same way — so the instruments on page 1 of **Overview** are the instruments on page 1 of **Returns**, **Fundamentals**, **Ratios** and **Dividend**. Selecting a column header replaces that order with your own for as long as you stay on the tab; moving to another tab returns to Market Cap. An instrument with no market cap sits at the end of the list, in either direction — it is unknown, not small. Exchange-traded products, crypto and indices have no market cap at all, so a screener whose universe is one of those has nothing to order by: every row ties, and the table falls back to the tie it always uses, each instrument's [permanent instrument identifier](/docs/data-methodology/permanent-instrument-identifier). That order is stable — the same screener opens the same way tomorrow, and paging never shows you a row twice — but it says nothing about the instruments, so sort by a column that means something to you. ## Why does the list change on its own between one day and the next? Because a screener always runs against the most recently loaded market close, not against a stored answer. The same filters over a new day's data produce a different list, and there is no option to run a screener as of some other date. [Screener execution and caching](/docs/screeners/screener-execution-and-caching) covers what is recomputed each time and what is not. ## My screener matches more instruments than my strategy holds — why? Because a strategy holds a capped number of positions and a screener caps nothing — it returns everything that passes. The control you set is **Max positions** on the strategy's **Screening** card, whose helper reads "Cap how many instruments are held at once". It is not the only limit between the filters and the holdings, and the two are easy to confuse: [the max symbols cap](/docs/screeners/max-symbols-cap) is the page that separates them and says which instruments survive when one bites. ## Common problems ### The list is empty: "No instruments match your filters" The body reads "Try removing or relaxing one of your filters." Your conditions are too tight together, or two of them cannot both be true. The empty state itself offers `Remove: {name}` for the filter you added last, and **Clear all filters**. ### The results area says "Couldn't run the screen." The message continues with the reason. Your screener and its filters are unchanged — nothing was lost — so run it again once the reason it names is dealt with. ### The list is far too long to be useful Add a **Highest / Lowest** condition with a **Rank** on the metric you care about, which keeps only the top or bottom N of what still passes. That is a change to the screener rather than to this table: the pager only pages the list, it never shortens it. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/screeners/aggregate-comparisons # Aggregate comparisons An aggregate comparison tests an instrument's metric against a population figure rather than a fixed number — the **vs Aggregate** relation on a screener filter. You choose a **Scope** (Market or Sector) and an **Aggregate** statistic (Index, Average, Median, 75th percentile, or 25th percentile), and the filter keeps instruments on your chosen side of that figure. It lets you screen relative to peers instead of against an absolute threshold. It is not the same thing as the **Market & Sector** filter category: those filters *read* a market or sector figure instead of the instrument's, while an aggregate comparison reads the instrument's own metric and only borrows a market or sector figure as the threshold (see [filter taxonomy](/docs/screeners/filter-taxonomy)). **Also seen as:** vs Aggregate, peer-relative screening ## How an aggregate comparison is built You set two things. The **Scope** names the group the figure is drawn from — **Market** or **Sector**. The **Aggregate** sets how that group is summarised into one number: - **Index** — the index-level figure for the chosen scope. - **Average** — the mean across the group. - **Median** — the middle value of the group. - **75th percentile** — the value three-quarters of the way up the group. - **25th percentile** — the value one-quarter of the way up the group. The filter then keeps instruments above or below that figure, according to the direction you set. Because the reference is a population statistic, the pass/fail line moves with the group as data updates, unlike a fixed value that stays put. ## How does Fincanva handle it? - The scopes available today are **Market** and **Sector**; no other scope is offered on any filter. - The aggregate statistic is one of Index, Average, Median, 75th percentile, or 25th percentile. - The comparison is relative — the threshold is recomputed from the population rather than typed in as a number. ## What does it look like in practice? A screener over technology stocks adds a Price/Earnings filter in **vs Aggregate** mode, sets **Scope = Sector** and **Aggregate = Median**, and keeps instruments below that figure. The filter now passes only technology names whose P/E sits under the sector's median P/E — a peer-relative screen that shifts as valuations move, where a fixed `P/E < 15` would not. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/screeners/asset-subtypes # Asset subtypes Asset subtypes are the abbreviations Fincanva uses to label the specific kind of instrument within a broader [asset type](/docs/getting-started/asset-type) — the **Asset subtype** field in a screener's [universe facets](/docs/screeners/universe-facets). For exchange-traded products they read ETF, ETN, ETC, CEF, ETD, and ETMF; for stocks they read Common, Common (secondary), Preferred, and Unit. Each is a narrower class inside the asset type, so filtering on a subtype keeps only instruments of that exact kind. **Also seen as:** security type ## What each asset-subtype abbreviation means Each abbreviation names a specific instrument structure inside the ETP (exchange-traded product) family: | Abbreviation | Full name | What it is | |---|---|---| | ETF | Exchange-Traded Fund | A fund holding a basket of assets that trades on an exchange like a share. | | ETN | Exchange-Traded Note | An unsecured debt note whose return tracks an index — you carry the issuer's credit risk, not a basket. | | ETC | Exchange-Traded Commodity | An exchange-traded security that tracks a commodity or commodity index. | | CEF | Closed-End Fund | A fund with a fixed share count that trades on an exchange, often at a premium or discount to its net asset value. | | ETD | Exchange-Traded Derivative | A derivative contract standardised and traded on an exchange. | | ETMF | Exchange-Traded Managed Fund | An actively managed fund in an exchange-traded wrapper. | The stock subtypes are plain English — Common and Preferred shares, a Common (secondary) listing, and Unit — so they aren't abbreviated. Note that **ETP** itself is not a subtype but the parent asset type these six sit under, and **ADR** and **OTC** are separate universe facets (the Country and Exchange fields), not asset subtypes. ## How does Fincanva handle it? - Asset subtype is a universe facet: it narrows a screener to instruments of that exact kind before any metric filter runs. - The subtypes offered depend on the asset type — stocks expose Common / Common (secondary) / Preferred / Unit; ETPs expose ETF / ETN / ETC / CEF / ETD / ETMF. - The same subtype also appears as a column in a screener's results, labelled **Asset subtype**. ## What does it look like in practice? Three instruments can track the same gold price yet be different subtypes. A gold **ETF** holds the metal (or gold-linked assets) in a fund and trades as shares. A gold **ETN** is a bank's debt note promising the index's return — if the issuer fails, the note can too, regardless of where gold is trading. A gold **ETC** is an exchange-traded security backed by the commodity itself. Filtering **Asset subtype = ETF** keeps the first and drops the other two. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/screeners/comparison-modes # Comparison modes Comparison modes are the ways a screener filter can test an instrument's metric — what the reading is measured *against*. The choices are **vs Value** (against a fixed number), **Between** (inside a range), **vs Lagged Self** (against the metric's own earlier reading), **Highest / Lowest** (a rank within the results), and **vs Aggregate** (against a market or sector figure, covered on its own page). Each mode changes what the filter's threshold means, not which metric it reads — the symbol that does the testing inside a mode is a separate choice, covered in [standard operators](/docs/screeners/standard-operators). **Also seen as:** filter relation ## How each comparison mode works - **vs Value** — passes instruments whose metric sits on the chosen side of one fixed number, for example `P/E < 15`. - **Between** — passes instruments whose metric falls inside a low–high range, for example `P/E between 10 and 20`. - **vs Lagged Self** — compares the metric to its own value at an earlier point you set (a [lag](/docs/screeners/lag-period-and-multiplier)), so you screen on change rather than level. - **Highest / Lowest** — ranks instruments on the metric and keeps only the top or bottom N; the pool it ranks is whatever is still passing at that point, so its position in the strip is part of the rule (see [sequential filtering and Top-N ranking](/docs/screeners/sequential-filtering-and-top-n-ranking)). - **vs Aggregate** — compares the metric to a market or sector statistic such as the median; see [aggregate comparisons](/docs/screeners/aggregate-comparisons). A handful of filters replace these modes entirely with pattern tests — crossings and valuation bands — which are [special relations](/docs/screeners/special-relations) rather than comparison modes. ## How does Fincanva handle it? - The mode is chosen per filter in the filter editor; the resolved sentence under **You're saying** restates it in plain language. - Not every mode is available for every filter — the editor shows only the relations that filter supports. - Switching mode keeps the metric but changes the inputs: a single value, a range, a lag, a rank, or a scope plus a statistic. ## What does it look like in practice? Take a Price/Earnings filter. In **vs Value** mode you set `P/E < 15`, so any instrument trading below 15× earnings passes. Switch the same filter to **vs Lagged Self** and set the lag to 12 months: now it compares each instrument's current P/E to its own P/E a year earlier, passing those whose P/E has fallen — a completely different screen built from the same metric. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/screeners/event-time-path # Event-time path An event-time path is a chart that lines up a [screener backtest](/docs/screeners/screener-backtest)'s matched instruments by *when they were selected* rather than by calendar date, so day 0 is always the pick date. From that shared starting point it plots the average path of the matches afterwards, letting you read what typically happened to instruments after a screener would have selected them. Because every match is re-centred on its own selection day, picks made in different years overlay on one timeline. It shows the *shape* of what followed a selection; a [holding horizon](/docs/screeners/holding-horizon) figure, by contrast, condenses one fixed length of hold into a single number. **Also seen as:** event-study plot ## Why day 0 is the selection date Setting day 0 to the selection date is what makes the picks comparable. Calendar-aligned, an instrument picked in 2015 and one picked in 2020 can't be averaged meaningfully; event-aligned, both start at their own day 0 and the chart can average "one month after selection", "six months after selection", and so on across every pick. The line to the right of day 0 is the average of those aligned paths, so a single curve summarises many selections at once. ## What the path does and doesn't tell you The path shows the average behaviour after selection — not any single instrument's outcome, and not a forecast. It reads left to right from day 0: a curve that rises after day 0 means the matches, on average, moved up over the window shown, while a fall means the opposite. It is a way to inspect the after-selection behaviour of a screener's picks alongside the match count and the filters that produced them. ## What does it look like in practice? A screener's event-time path sets day 0 at each instrument's selection date. Reading right from day 0, the average line shows how the picks moved one, three, six, and twelve months after they were selected — a pick from 2016 and one from 2021 both counted from their own day 0. The point at day 0 is the selection moment itself, so the path starts flat there; everything to its right is the average journey afterwards. *The path averages what happened after past selections on historical data, not what will follow the next one, and no shape it takes is a reason to buy or sell anything.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/screeners/filter-condition-anatomy # Filter condition anatomy A filter condition is one screening rule taken apart into its three parts: the **metric** it reads, the **operator** that tests that metric, and the **value** it is tested against. This page is the part-by-part reading of a single rule — what each piece does, how the editor restates it, and how the finished chip such as `ROE > 15%` is put together; [filter](/docs/getting-started/filter) is the page that defines the object itself, and [filter taxonomy](/docs/screeners/filter-taxonomy) is where you find the metric to start from. A screener keeps only the instruments whose readings satisfy every one of its conditions at once, so each condition you add is one more test an instrument has to pass. **Also seen as:** filter chip, filter rule ## What are the three parts of a filter condition? Every condition answers the same question in three pieces — which metric, tested how, against what. | Part | What it is | In `ROE > 15%` | |---|---|---| | Metric | The measurement the [filter](/docs/getting-started/filter) reads for each instrument, picked from the filter catalogue. | ROE | | Operator | The comparison applied to that reading. | `>` (greater than) | | Value | The number the reading is compared against, in the metric's own unit. | 15% | The metric comes from the [filter taxonomy](/docs/screeners/filter-taxonomy) — 118 filters grouped into three categories and 20 subcategories. The operator comes from the filter's own operator list: see [standard operators](/docs/screeners/standard-operators) for the comparison set, and [special relations](/docs/screeners/special-relations) for the pattern tests such as crossings that a handful of filters offer instead. The wider shapes a comparison can take — a fixed number, a range, the metric's own earlier reading, a rank, or a market or sector figure — are covered in [comparison modes](/docs/screeners/comparison-modes). ## What does the "You're saying" line show? **You're saying** is the filter editor's plain-language restatement of the condition you have just built, rewritten live as you change the operator or the value. It reads the three parts back as one sentence — "ROE is greater than 15%." — so you can check the rule says what you meant before you apply it. Until you have picked values it reads "Choose values to see what this filter says." The sentence uses words where the dropdown uses glyphs: `<` reads "is less than", `≤` reads "is at most", `=` reads "equals", `≥` reads "is at least", and `>` reads "is greater than". ## How does Fincanva handle it? - A filter arrives with the operator and value its catalogue entry declares, so a condition is valid the moment you add it — the ROE filter opens at `>` 20%. - Values snap to the stops that filter offers. You can type a number freely; on Enter, or when the field loses focus, it moves to the nearest stop. - Each filter offers only the operators and comparison modes it supports; the editor hides the rest rather than showing them disabled. - Conditions combine with AND and run in the order they sit in the filter strip — see [sequential filtering and Top-N ranking](/docs/screeners/sequential-filtering-and-top-n-ranking). - The optional **Advanced** panel adds Lag, Period, and Multiplier, which shift or scale the reading before the comparison; see [lag, period, and multiplier](/docs/screeners/lag-period-and-multiplier). - The chip is the same condition in compact form: the filter name, then any non-default Advanced settings as `(period) [lag]`, then the operator and the value. - The count of instruments still passing every condition is the [match count](/docs/screeners/matches). ## How do you build "ROE > 15%"? Four moves, each one touching a single part of the condition. 1. **Add the filter.** Open **Add filter**. The flyout has three columns — **Category**, **Subcategory**, **Filter**. Pick **Fundamental**, then **Profitability**, then **ROE**. The condition arrives at its catalogue default, `ROE > 20%`. 2. **Check the operator.** The operator dropdown groups its choices under **Compare**, **Range**, and **Rank**. `>` — labelled "greater than" — is already selected under **Compare**, so there is nothing to change. 3. **Set the value.** Type `15` in the value field. The ROE filter's stops run in one-point steps, so 15 lands exactly on a stop and the field shows 15%. 4. **Read it back.** **You're saying** now shows "ROE is greater than 15%." Apply, and the chip in the strip reads `ROE > 15%`. The condition now keeps every instrument whose most recent return on equity reads above 15% and drops the rest. Because `>` is strict, an instrument sitting at exactly 15% does not pass; switching the operator to `≥` ("at least") includes the boundary. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/screeners/filter-impact-lenses # Filter impact lenses Filter impact lenses are the three ways a [screener backtest](/docs/screeners/screener-backtest) reports what a single [filter](/docs/getting-started/filter) contributed: **On its own**, **Added in sequence**, and **If removed**. They appear in the **Which filters earn their place** table — one row per filter, expandable into the full six-[horizon](/docs/screeners/holding-horizon) breakdown. The three lenses answer three different questions and, critically, **are not measured on the same scale**: one is a return, two are differences. Reading one as if it were another is the single most common way to misjudge a filter. **Also seen as:** marginal contribution analysis, leave-one-out ## What each of the three lenses measures | Lens | The question it answers | What the number is | |---|---|---| | On its own | "How did this filter's own picks do?" | an **average annualized return** — a level, shown as a percentage, with no other filter and no benchmark subtracted | | Added in sequence | "What did adding this filter change, at its place in the chain?" | a **difference** — the change from the filters *before* it in the screener's order to the same set *with* it, in percentage points (pp) | | If removed | "What would dropping this filter cost?" | a **difference** — the full filter set minus the same set with this one filter taken out, in percentage points (pp) | ## Why the three percentages are not comparable **On its own is a return; the other two are differences.** A filter reading `+14.2%` on its own and `+0.3 pp` added in sequence is not contradicting itself: the first says its own picks averaged a 14.2% annualized return, the second says it moved the [screener](/docs/getting-started/screener) 0.3 points when stacked onto the filters above it. Subtracting, ratioing, or ranking across the two columns is meaningless. **The two differences use different baselines.** *Added in sequence* is measured against the filters that come **before** it, so it depends on [filter order](/docs/screeners/sequential-filtering-and-top-n-ranking) — the same filter can look large in first position and near-zero in last, because whatever it excludes may already have been excluded. *If removed* is measured against the **complete** set, so it does not depend on order; it is the honest "what do I lose by deleting this" figure and it is the one the table leads with, under the header "Removing it would cost you…". **A negative *If removed* means removal would help.** Because the lens is "full set minus set-without-it", a negative value says the screener performed better without that filter over the period. Those rows are tinted in the destructive (red) style so a filter that is actively costing you is visible without reading the number. ## How does Fincanva handle it? - The table's lead column is the **If removed** lens, drawn as a bar diverging from a centre line — right for positive, left for negative, widths scaled to the largest magnitude in the table. - One horizon at a time drives the lead column, chosen from the same six horizons; the selector opens on **12 months**. - Expanding a filter's row reveals the full grid: six horizons × the three lenses, so a filter can be strong at one horizon and weak at another. - The **On its own** column carries the sub-label "raw return" precisely because it is not a delta. - A value that cannot be computed shows "—" rather than a zero. ## What does it look like in practice? A screener holds three filters and the third one looks weak. Expanded at the 12-month horizon, its row reads: **On its own `+9.8%`**, **Added in sequence `+0.2 pp`**, **If removed `−1.1 pp`**. Read across the row rather than down a column. On its own, the filter's picks averaged a 9.8% annualized return — respectable in isolation, and it says nothing about the screener. Added in sequence, it moved the screener by only 0.2 points once the two filters above it had already narrowed the field, so most of what it excludes was excluded already. If removed is negative: the full three-filter screener trailed the two-filter version by 1.1 annualized points, meaning this filter cost the screener rather than helping it, and its row is tinted red. Notice that the third figure — not the flattering first one — is the one about *this screener*. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/screeners/filter-taxonomy # Filter taxonomy Filter taxonomy is the way Fincanva organises the filters a [screener](/docs/getting-started/screener) can use: **118 filters** in three categories — **Fundamental** (84), **Technical** (20), and **Market & Sector** (14) — split across **20 subcategories**. The category tells you what kind of data a filter reads; the subcategory tells you which part of that data. Every filter is reached along that path, so the taxonomy is how you find the metric you want rather than scrolling one long list. **Also seen as:** filter categories, filter families, filter catalogue ## What do the three filter categories read? Each category reads a different subject, and that changes what the filter can tell you about an instrument. | Category | Filters | What it reads | Example filter | |---|---|---|---| | Fundamental | 84 | The company's own reported financials, and the ratios built from them. | ROE | | Technical | 20 | The instrument's own price and volume history. | RSI | | Market & Sector | 14 | The market index, or the instrument's sector, rather than the instrument itself. | Mkt Median PE | Market & Sector filters behave differently from the other two because their reading does not belong to the instrument. A **market** filter (its name starts with `Mkt`) tests one figure for the whole market, so it is a regime gate: either the condition holds and every instrument still in the running stays, or it fails and the screener returns nothing. A **sector** filter (`Sec`) tests the condition once per sector and keeps the instruments belonging to the sectors that passed. ## What are the 20 subcategories? The subcategory is the second column in the **Add filter** flyout, and it narrows a category to one area of measurement. | Category | Subcategories (filters each) | |---|---| | Fundamental | Profile (3), Income Statement (23), Balance Sheet (16), Cash Flow Statement (12), Operating Margin (3), Profitability (4), Liquidity (2), Solvency (3), Valuation Ratios (9), Dividends (9) | | Technical | Momentum (5), Volatility (2), Relations (4), Risk-Reward (3), Indicators (4), Market Liquidity (2) | | Market & Sector | Market Technical (5), Market Fundamental (2), Sector Technical (6), Sector Fundamental (1) | Ten subcategories under Fundamental, six under Technical, four under Market & Sector — twenty in total. ## How does Fincanva handle it? - The **Add filter** flyout lists **Universe** alongside the three categories in its first column. Universe is not a filter category: it restricts which instruments the screener considers at all, before any metric filter runs. See [universe](/docs/getting-started/universe); its individual fields are the [universe facets](/docs/screeners/universe-facets). - Category names are translated by the app; subcategory names are shown in English in every language, because they come straight from the filter catalogue. - Each [filter](/docs/getting-started/filter) carries its own description in the flyout — the catalogue is the source of truth for what an individual filter measures, and this page does not repeat those descriptions. - Which filters a screener can use depends on its [asset type](/docs/getting-started/asset-type): some filters apply to stocks only, others to stocks, ETPs, and crypto alike. - Market and sector figures are also available *as comparison targets* on many instrument-level filters, which is a different mechanism from the Market & Sector category; see [aggregate comparisons](/docs/screeners/aggregate-comparisons). ## What does one filter from each category look like? Three conditions, one per category, on the same screener. - **Fundamental → Profitability → ROE.** Reads each company's return on equity from its own financial reports. `ROE > 15%` keeps the companies earning more than 15% on their equity. - **Technical → Indicators → RSI.** Reads each instrument's own price history. It says nothing about the company's accounts — two instruments with identical financials can sit at opposite ends of the RSI range. - **Market & Sector → Market Fundamental → Mkt Median PE.** Reads the market's median price/earnings ratio, not the instrument's. Set a condition on it and the whole screen is gated on the market's valuation level: when the condition fails on a given date, the screener has no matches at all, however cheap the individual companies look. Read together, the three answer three different questions — how profitable the company is, where its price sits in its own recent range, and what the market as a whole is doing. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/screeners/fin-suggestions # Fin suggestions A Fin suggestion is an alternative filter set that [Fin](/docs/getting-started/fin) proposes for a [screener](/docs/getting-started/screener), presented beside your current one so you can compare the two before anything changes. Fin either improves the filters you already have or builds a set from your [universe](/docs/getting-started/universe) when you have none, and it reports the result qualitatively — for example that it found a better-performing variant, or that it could not improve on what you have. Every [filter](/docs/getting-started/filter) in the comparison is tagged **Kept**, **Added**, **Modified**, or **Removed**, and your screener is untouched until you explicitly accept the suggestion. **Also seen as:** Improve filters, Suggest new filters ## What Fin can suggest Two actions start a suggestion, both on the **Backtest** sub-view: - **Improve filters** — Fin starts from the filters you already have and looks for a better-performing variant of them. It needs at least one filter; without one it is disabled with the hint "Add at least one filter first — there's nothing to improve yet." - **Suggest new filters** — Fin starts from your universe with no filters and proposes a set from scratch. This one is always available. While it works, the dialog shows Fin's progress and the line "Fin is testing thousands of filter combinations against market history to find a stronger setup." **Cancel** closes the dialog and abandons the suggestion. ## How to read the Kept / Added / Modified / Removed tags The review shows two columns — **Your screener** and **Fin's suggestion** — each listing its own filters in its own order, with a tag on every line that changed: | Tag | Where it appears | What it means | |---|---|---| | Kept | both columns | the filter is identical on both sides — Fin left it exactly as it was (no badge is drawn, since nothing changed) | | Modified | both columns | the same filter, with different settings — compare the two lines to see what moved | | Added | Fin's suggestion | a filter that is not in your screener at all | | Removed | Your screener | a filter Fin dropped, marked in the destructive (red) style | Read the columns as two complete filter sets rather than as paired rows: a screener can hold the same filter twice, so the lists are deliberately not joined line by line. See [filter condition anatomy](/docs/screeners/filter-condition-anatomy) for the parts of a filter a **Modified** tag can refer to. ## What your three choices are Nothing is applied automatically. The review offers: - **Discard** — close and keep your screener exactly as it was. - **Save as new screener** — keep your current screener and store the suggestion as a separate one. - **Use these filters** — load the suggested filters into the editor as **unsaved** changes and immediately re-run the backtest on them, so you see the suggestion's own result before deciding whether to save it. ## What happens when Fin finds nothing better When Fin cannot beat the screener you already have, the dialog says so plainly — "This is already a strong screener" and "Fin tested thousands of filter combinations against market history and couldn't improve on it." — and offers only **Close**. There is no comparison and no figure in that case, deliberately: there is no change to review. If the search itself breaks, you get "Fin couldn't finish" and "The search couldn't complete. Your screener is unchanged — try again." ## How does Fincanva handle it? - A suggestion changes **only the filters**. It never changes the screener's [universe facets](/docs/screeners/universe-facets) — the universe you set is the universe Fin works inside. - Fin is the only name for the assistant in Fincanva; a suggestion is Fin's output, not a separate product. - Your screener is never modified in place by a suggestion: **Use these filters** stages the change as unsaved, so you can still leave without saving. - A suggestion is a **backtested variant**, and the dialog says so: "Backtested result — past performance doesn't guarantee future returns." - Each launch starts a fresh search, so re-running **Improve filters** on the same screener can return a different suggestion. ## What does it look like in practice? Your screener holds `P/E < 20`, `Sector = Technology`, and `Market cap > $10B`. You press **Improve filters**. Fin works, then reports that it found a better-performing variant. In the comparison, `Sector = Technology` is **Kept** on both sides; `P/E < 20` appears as **Modified** — Fin's column shows a different threshold; `Market cap > $10B` is tagged **Removed** in your column and does not appear in Fin's; and a filter you did not have appears as **Added** in Fin's column. You now have three honest options: **Discard** and keep your three filters, **Save as new screener** to compare both over time, or **Use these filters** to try Fin's set as unsaved changes with a fresh backtest attached. *A suggestion describes what a filter set would have done on historical data. It is not a recommendation.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/screeners/fundamental-metric-columns # Fundamental metric columns Fundamental metric columns are the measured values a [screener](/docs/getting-started/screener)'s results table shows for each match: company financials, growth rates, valuation multiples, dividend figures, and price-derived measures. There are **35 columns in total**, spread across the table's five tabs — **Overview**, **Returns**, **Fundamentals**, **Ratios**, and **Dividend** — and the count includes the identity and classification columns (Symbol, Asset type, Exchange, Country, Sector, Industry) that sit alongside the metrics. A column reports what the instrument reads today; it is not a filter, and showing a column does not screen on it. **Also seen as:** results columns, results-table columns ## What does each results column show? Every column appears on at least one tab, and several appear on more than one. The **Unit line** is the small second line under the header, shown only where the measurement basis needs stating. | Column | Tabs | What it shows | Unit line | |---|---|---|---| | Symbol | all five | The instrument itself — its name, with its exchange and ticker beneath. See [instrument](/docs/getting-started/instrument). | — | | Asset type | all five | Stock, ETP, or crypto. See [asset type](/docs/getting-started/asset-type). | — | | Asset subtype | Overview | The narrower instrument type inside the asset type. See [asset subtype](/docs/screeners/asset-subtypes). | — | | Market Cap | Overview, Ratios | Total market value of all shares. | — | | 1Y | Overview, Returns | Return over the last 12 months, beside a one-year price sparkline. | — | | Exchange | Overview, Returns | Marketplace where it trades. | — | | Country | Overview | Country the company is based in. | — | | Sector | Overview | Broad industry group. | — | | Industry | Overview | Specific industry. | — | | YTD | Returns | Return since the start of the year. | — | | 1M | Returns | Return over the last month. | — | | MTD | Returns | Return since the start of the month. | — | | Sharpe | Returns | The instrument's own return over the last 12 months per unit of volatility, with no risk-free rate subtracted. See [Sharpe ratio](/docs/analysis/sharpe-ratio#does-the-screeners-sharpe-subtract-the-risk-free-rate). | — | | Beta | Returns | How much the instrument moves with the market. See [beta](/docs/analysis/beta). | — | | Sales | Fundamentals | Revenue over the trailing twelve months. | TTM | | Sales growth | Fundamentals | Change in trailing-twelve-month revenue against the year before. | TTM · YoY | | Gross profit growth | Fundamentals | Change in trailing-twelve-month gross profit against the year before. | TTM · YoY | | EBITDA growth | Fundamentals | Change in trailing-twelve-month EBITDA against the year before. | TTM · YoY | | Net income growth | Fundamentals | Change in trailing-twelve-month net income against the year before. | TTM · YoY | | FCF growth | Fundamentals | Change in trailing-twelve-month free cash flow against the year before. | TTM · YoY | | Working capital growth | Fundamentals | Change in working capital against the year before. | YoY | | D/E | Fundamentals | Debt to equity. | — | | Quick ratio | Fundamentals | Short-term liquidity. | — | | ROE | Fundamentals | Return on equity. | — | | EV | Ratios | Enterprise value. | — | | P/E | Ratios | Price to earnings. | — | | P/S | Ratios | Price to sales. | — | | P/FCF | Ratios | Price to free cash flow. | — | | P/BV | Ratios | Price to book value. | — | | EV/EBITDA | Ratios | Enterprise value to EBITDA. | — | | FCF yield | Ratios | Free cash flow yield. | % | | Last Price | Dividend | Most recent closing price. | — | | Div per share | Dividend | Dividend per share. | — | | Div yield | Dividend | Dividend yield. | % | | Payout ratio | Dividend | Share of earnings paid as dividends. | % | The six growth columns all read the same way: a trailing-twelve-month or point-in-time figure compared with the same figure a year earlier. That shared measurement basis is explained in [TTM and YoY](/docs/screeners/ttm-and-yoy). ## Which columns have a page of their own? Four of the 35 have their own concept page, because the same term appears elsewhere in the product and not only as a column header: [instrument](/docs/getting-started/instrument) behind Symbol, [asset subtype](/docs/screeners/asset-subtypes), [Sharpe ratio](/docs/analysis/sharpe-ratio), and [beta](/docs/analysis/beta). A fifth page covers no column of its own: [TTM and YoY](/docs/screeners/ttm-and-yoy) is the shared measurement basis behind the six growth columns. The remaining columns are defined in the table above and in the header hint each one carries in the app; every column in the results table has help on hover today. **Sharpe** and **Beta** here describe the individual instrument's own price history, not a strategy's. They are not the same figures a backtest reports for a strategy over a chosen period, and the two should not be read against each other: this Sharpe, unlike a backtest's, subtracts no risk-free rate. ## How does Fincanva handle it? - Columns are grouped by tab, and switching tabs changes the columns rather than the instruments — the same matches are shown throughout. - Every tab starts with **Symbol** and **Asset type**, so a row stays identifiable whichever tab you are on. - The **Columns** button hides or shows columns for the tab you are on; the choice is remembered per tab. - Any column header sorts the table, and sorting is applied across the whole result set, not just the rows currently on screen. - A cell with no value available reads as a dash rather than a zero — a missing reading and a reading of zero are not the same thing. - Return and growth columns are colour-tinted, and the 1Y sparkline takes its colour from the sign of its return. - Column values describe the instrument as it reads now. A screener's filters decide which instruments appear; the columns only report on them. ## How do you read one row across the tabs? One match — a mid-size industrial company — read across all five tabs. - **Overview** places it: the Symbol cell names it with its exchange and ticker, Asset type reads Stock, Market Cap puts it in the mid-size band, and Exchange, Country, Sector, and Industry classify it. The 1Y cell shows its twelve-month return beside a sparkline of the path it took to get there. - **Returns** breaks that path down: 1Y, YTD, 1M, and MTD are four different windows on the same price series, so a strong 1Y beside a weak MTD simply means a good year with a soft current month. Sharpe and Beta add how choppy the ride was and how closely it tracked the market. - **Fundamentals** turns to the accounts: Sales gives the trailing-twelve-month revenue level, and the six growth columns beside it give the direction of travel against the year before. D/E, Quick ratio, and ROE describe leverage, short-term liquidity, and profitability. - **Ratios** prices those accounts: EV alongside Market Cap, then P/E, P/S, P/FCF, P/BV, and EV/EBITDA as five different ways of dividing price by a fundamental, plus FCF yield as the inverse view of P/FCF. - **Dividend** covers the payout: Last Price, Div per share, Div yield, and Payout ratio — the last of these showing how much of earnings the dividend consumes. Read in that order the row goes from *what it is*, to *how its price behaved*, to *what the business did*, to *what you pay for it*, to *what it pays you*. No single column answers a question on its own; each tab is one lens on the same instrument. *These figures describe what an instrument reads on historical and current data, not what it will do.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/screeners/holding-horizon # Holding horizon A holding horizon is how long a [screener backtest](/docs/screeners/screener-backtest) assumes you keep each match after the [screener](/docs/getting-started/screener) selects it. Six horizons are measured on every run — **1, 2, 3, 6, 12, and 24 months** — and each one gets its own figure, so a single run tells you how the same filters looked over a short hold and over a long one. The horizon is a measurement window, not a setting on your screener: nothing about the filters changes between horizons, only how far forward the outcome is read. ## Why a screener backtest reports six horizons instead of one Filters do not work equally well over every length of hold, and one number would hide that. A screen that catches short-lived moves can look strong at one month and unremarkable at two years; a screen built on slow fundamental change can look flat early and stronger later. Measuring all six horizons on the same run makes that shape visible, and it is what the **Edge by holding horizon** card plots: one column per horizon, the annualized edge against the benchmark, positive above the line and negative below it. ## What "the best horizon" means The best horizon is simply the horizon with the **highest annualized edge over the benchmark** on this run — the one starred in the horizon label band and quoted in the verdict band as "holding picks for `{n}` months — the best horizon". It is a description of the run you just made, over the period it covered, not a holding period Fincanva recommends and not a prediction that the same horizon will lead next time. A run can perfectly well have a best horizon whose figure is still negative: it means every horizon trailed the benchmark and that one trailed least. ## How does Fincanva handle it? - The six horizons are fixed at **1, 2, 3, 6, 12, and 24 months**; you cannot add, remove, or re-length them. - Every horizon is measured from the same selection dates on the same monthly cadence, so the six figures are directly comparable to each other. - Horizon figures in the verdict band and the **Edge by holding horizon** card are **edges** against [the benchmark](/docs/screeners/screener-backtest-benchmark), so they are quoted in percentage points (pp), not as returns. - The per-filter [impact table](/docs/screeners/filter-impact-lenses) has its own horizon selector over the same six values, and it opens on **12 months**. - A horizon whose benchmark figure is missing shows "—" rather than a number, because an edge without a benchmark side cannot be computed. ## What does it look like in practice? One run of a three-filter screener returns `+4.1 pp` annualized at the 3-month horizon and `+0.6 pp` at 12 months. Read that as: on this history, the matches beat the benchmark by about four annualized points when held for a quarter, and by only about half a point when held for a year — the advantage was concentrated shortly after selection and faded as the hold lengthened. Because 3 months carries the largest edge, it is the starred best horizon, and the verdict band's hero figure is the `+4.1 pp`. Note what the two numbers do *not* say: `+4.1 pp` at 3 months is not four times better than `+0.6 pp` at 12 months in absolute money — both are annualized rates, and each is the average across every selection date the run covered. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/screeners/lag-period-and-multiplier # Lag, period, and multiplier Lag, period, and multiplier are the inputs in a [filter](/docs/getting-started/filter)'s **Advanced** panel that shift or scale what a metric reads before it is compared. **Lag** moves the reading back in time, **Period** sets the window it covers, and **Multiplier** scales it. Each input carries a unit that depends on the filter — Months Ago, Reports Ago, Quarters, Days, Bars, or Std Devs — so the same control means "four reports ago" on a fundamental filter and "twenty days" on a technical one. They change only the *reading*, never the [comparison mode](/docs/screeners/comparison-modes) or the operator applied to it. **Also seen as:** Advanced filter settings ## What the lag and period units mean You set the number; the filter decides which unit it counts in. | Unit | Used on | Means | |---|---|---| | Months Ago | fundamental / price-history filters | shift the reading back by that many calendar months | | Reports Ago | fundamental filters | shift back by that many financial reports (filings) | | Quarters | fundamental filters | count in three-month reporting quarters | | Days | technical / price filters | count in trading days | | Bars | technical filters | count in price bars (data points on the chart) | | Std Devs | technical filters | scale in standard deviations of the metric | The **Period** input is separate and sets the length of a windowed metric, in **Months** or **Years**. ## How does Fincanva handle it? - The unit is fixed by the filter — you enter the number, the filter decides whether it counts in reports, months, days, bars, or standard deviations. - Lag is optional; leaving it at zero compares the metric at its latest reading. - Period sets a window length (in Months or Years) for metrics that summarise a span rather than a single point. ## What does it look like in practice? A revenue filter in [**vs Lagged Self**](/docs/screeners/comparison-modes) mode uses **Reports Ago** as its lag unit. Set the lag to 4 and the filter reads each company's revenue from four financial reports back — for a company reporting quarterly, roughly a year earlier — and compares it to the latest revenue. "Reports Ago" counts filings, not calendar time, so a company that files quarterly and one that files half-yearly are shifted by different spans for the same lag of 4. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/screeners/matches # Matches Matches are the instruments in a screener's universe that pass every one of its filters at once, shown as a live count that updates as you add, edit, or remove filters. The count is the single number on the **Matches** tab; when no instrument passes, it reads zero in a red (destructive) style, signalling the screener has nothing to act on. Because filters combine with AND, an instrument has to clear all of them to be counted. **Also seen as:** match count ## How the match count changes as you add filters Every filter narrows the pool: a screener starts from its [universe](/docs/getting-started/universe) and keeps only the instruments that satisfy all of its [filters](/docs/getting-started/filter) together. Adding a filter can lower the count or leave it unchanged, but never raise it; removing or loosening a filter can only raise it. This is why a screen with more filters usually shows fewer matches — each condition is one more test an instrument must pass. Where a **Highest** or **Lowest** filter sits in that chain also matters, because it ranks only the instruments still passing at its own position — see [sequential filtering and Top-N ranking](/docs/screeners/sequential-filtering-and-top-n-ranking). ## What a zero count means A zero count means no instrument in the universe passes all the filters together, and the **Matches** badge turns red to flag it. It usually points to filters that are too tight or that contradict each other rather than to an error. Widen a range, remove a filter, or broaden the universe to bring instruments back into the set. ## How does Fincanva handle it? - The match count is the single count surface — it appears as the number on the **Matches** tab and updates live as you edit filters. - At zero it switches to the destructive (red) badge style; above zero it shows as a plain count. - Before a screener has run, the count can read "Run to see matches" instead of a number. - The set of matches is what a backtest or an attached strategy draws from. It is not the same as what a strategy ends up holding: a simulation trims the candidate list with the [max-symbols cap](/docs/screeners/max-symbols-cap) and then holds only as many as **Max positions** allows. ## What does it look like in practice? A screener over US stocks starts from its whole universe. You add a first filter, `P/E < 20`, and the count drops to, say, 620 matches; a second, `Sector = Technology`, brings it to 90; a third, `Market cap > $10B`, leaves 47. The readout now shows "47 matches" — the 47 instruments that satisfy all three filters at once. Remove the sector filter and the count rises again, because fewer conditions have to be met. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/screeners/max-symbols-cap # Max-symbols cap The max-symbols cap is the limit on how many of a screener's [matches](/docs/screeners/matches) a simulation carries forward as candidates: when a screen returns more instruments than the run will work with, the set is trimmed and only the most liquid matches survive. It applies where a screener feeds a strategy, not to the screener on its own — the count you read on a screener's **Matches** tab is not capped, while the candidate list the [simulation engine](/docs/getting-started/simulation-engine) receives from it can be shorter. Liquidity is the tie-break: when names have to be dropped, the most heavily traded ones are kept. **Also seen as:** symbols cap ## Why does my screener show more matches than my strategy holds? Because two separate limits sit between the filters and the holdings, and only one of them is the max-symbols cap. - **[Max positions](/docs/strategies/max-positions)** is the control you set yourself — its helper text reads `Cap how many instruments are held at once`. It decides how many positions the strategy carries at any one moment. - **The max-symbols cap** sits earlier, between the screen and the run. It decides how many matches are considered as candidates at all on a screening date, before the allocation picks anything. So a screener reporting 200 matches does not hand 200 candidates to the run, and the run does not hold every candidate it is handed. Both gaps are expected rather than errors, and Fincanva shows no notice when the cap has applied — you infer it from the distance between the match count and the holdings. A screener's own backtest is a different measurement again: it is taken against [a benchmark](/docs/screeners/screener-backtest-benchmark) rather than against what a strategy ends up holding. ## What happens to the matches that get dropped? They are not considered on that screening date, and nothing else about them changes. The cap keeps the most liquid matches and drops the least liquid, so the names that fall away are the thinnest-traded ones in that match set — instruments whose trading activity is small next to the rest of the set. They stay in the screener's own results, they stay in the [universe](/docs/getting-started/universe), and they keep the same [permanent instrument identifier](/docs/data-methodology/permanent-instrument-identifier). Being dropped is also not permanent. A screener is re-run on every screening date, so the trimming is redone each time against a fresh match set: a name outside the cap on one date can be inside it on the next, because either the match set or its liquidity ranking has moved. ## How does Fincanva handle it? - The cap applies to the candidate set a simulation screens in, never to the count a screener reports on its own. - Liquidity is the only tie-break. The cap does not prefer a sector, a country, an exchange, or an instrument that passed the filters by a wider margin. - The cap is not a published number — Fincanva states no figure for it and shows none in the app. - Trimming happens on every screening date, not once at the start of the run, because the screen itself is re-evaluated each time (see [screener execution and caching](/docs/screeners/screener-execution-and-caching)). - The cap changes which [instruments](/docs/getting-started/instrument) a run may hold; it does not change any filter, any threshold, or the screener you saved. - It is not a filter row you author. A Highest-N or Lowest-N ranking inside a screener is a row you write and can read back — see [sequential filtering and Top-N ranking](/docs/screeners/sequential-filtering-and-top-n-ranking) — whereas the cap is applied between the screen and the run and has no row of its own. ## What does it look like in practice? A screener returns 200 matches on a screening date. If the cap sits below 200, the set is trimmed before anything is allocated: the most liquid of the 200 are kept, the thinnest-traded are dropped, and the allocation then chooses its holdings from the shorter list. If the cap is at or above 200, nothing is trimmed and all 200 stay candidates. Read the two numbers apart. The 200 is what the filters found. What the strategy holds is a subset of a subset — the most liquid matches first, then as many of those as **Max positions** allows. If a specific thinly-traded name you expected keeps failing to appear in the holdings even though it shows up in the screener's results, the cap rather than the filters is the usual reason. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/screeners/screener-backtest # Screener backtest A screener backtest is a historical test of a [screener](/docs/getting-started/screener)'s filters: it re-screens the market month by month from 2000 to the latest market data and measures what the [matches](/docs/screeners/matches) went on to return over each of six fixed [holding horizons](/docs/screeners/holding-horizon), stated against a benchmark. It answers "would these filters have beaten the market?" rather than "what would this portfolio have been worth?", and it lives on the **Backtest** sub-view beside **Matches**. It is return-only today: no volatility, drawdown, or Sharpe figures are produced for a screener backtest. **Also seen as:** screen backtest ## How a screener backtest differs from a strategy backtest A [backtest](/docs/getting-started/backtest) of a strategy replays that strategy's own allocation, rebalancing, and exit rules over history and produces an equity curve plus a full metrics table. A screener backtest never builds a portfolio: it repeats the screen on a monthly cadence, then averages what the selected instruments did over the next 1, 2, 3, 6, 12, and 24 months. So a strategy backtest has one path and one final value, while a screener backtest has six per-horizon averages and no equity curve. The two also answer to different inputs — a strategy backtest changes when you change allocation or exits, a screener backtest changes only when the [filters](/docs/getting-started/filter) or the universe change. ## What happens while a screener backtest runs A run is submitted and then watched until it finishes, so the view moves through named states rather than blocking: | State | What you see | |---|---| | Never run | a faded preview of the finished layout behind "See how this screener beat the market", with **Run backtest** and the option to "let Fin suggest a stronger one" | | Running | a progress bar with "Backtesting `{percent}`%" and "`{percent}`% · evaluating monthly windows, 2000 → today", plus **Cancel** | | Refreshing data | "Refreshing data…" while market data reloads; the run keeps retrying on its own | | Complete | the verdict band and the full result, with "Last run …" | | Failed | "This backtest couldn't complete" and "Something went wrong while running it. Your screener and filters are unchanged — try again.", with **Retry run** | **Cancel** stops watching the run; it does not undo anything, and a previously completed result stays on screen rather than blanking. ## What the verdict band shows The verdict band is the standing answer to "did these filters beat the market?", and it appears on both the **Matches** and **Backtest** sub-views. It carries the [benchmark it measured against](/docs/screeners/screener-backtest-benchmark) (in the **Benchmark universe** dock), one hero figure — the annualized edge at the best horizon, read as "annualized above the benchmark" or "annualized below the benchmark" — and then all six horizons as compact figures. Every figure in the band is an edge, so it is quoted in percentage points (pp) rather than as a return: `+3.4 pp` means the matches annualized 3.4 points above the benchmark over that horizon, not that they returned 3.4%. A zero reads as a tie, in neutral styling, never as a win. ## What the "Out of date" banner means When you change the filters after a run, the app keeps the previous result and marks it out of date rather than deleting it. The banner reads: > Out of date — filters changed since the last backtest. Showing the previous run. The fix is the **Re-run backtest** action beside it. The old result stays visible but dimmed, so you can still read it while knowing it belongs to the earlier filter set. ## How does Fincanva handle it? - Every screener backtest starts in **2000** and ends at the latest available market data, and it re-screens on a **monthly** cadence — the methodology strip states "Rebalanced monthly". - The six holding horizons are fixed at **1, 2, 3, 6, 12, and 24 months** and are not configurable. - The run tests the **saved** screener, not unsaved edits — which is why saving a change marks the last result out of date. - The **Backtest** action needs at least one saved filter; with no rules the view shows "Backtest your screening rules" and points you at the filter bar instead. - A completed result is not carried across visits: reopening the screener returns the **Backtest** sub-view to its never-run state, so you press **Backtest** again. - That second run comes back quickly rather than recomputing, because the finished result is reused for an unchanged screener until new market data arrives — which is also why the same screener's figures can shift from one day to the next with no change to its filters. ## What does it look like in practice? A screener over US stocks holds three filters: `P/E < 20`, `Sector = Technology`, and `Market cap > $10B`. You press **Backtest**. The run steps to "Backtesting 41%", then completes. The verdict band names the benchmark, shows one hero figure — say `+2.8 pp` annualized at the 3-month horizon, marked as the best horizon — and lists all six horizons beside it, some positive and some negative. You then loosen the first filter to `P/E < 25`. Nothing recomputes on its own: the banner appears, the old result dims, and the numbers you are looking at still belong to `P/E < 20` until you press **Re-run backtest**. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/screeners/screener-execution-and-caching # Screener execution and caching Screener execution is the run that turns a screener's filters into its [matches](/docs/screeners/matches) — the instruments that pass every filter — evaluated against the latest market data Fincanva has loaded. Every run is answered against the [data frontier](/docs/backtesting/data-freshness-and-frontier) rather than the wall-clock date, over the screener's whole [universe](/docs/getting-started/universe). The two things a screener can produce behave differently when you ask again: a match run always computes and answers from that day's data, while a screener backtest you have already run comes back immediately for a limited time, which can end sooner and never lasts past the daily data refresh — after which it computes in full again. **Also seen as:** running a screen, executing a screener ## What are the states a screener run passes through? A match run is short and has three visible outcomes: while it is in flight the results area reads `Refreshing matches…`; on success the matches replace it; on failure it reads `Couldn't run the screen.` with the reason. A run that finds nothing is not a failure — it shows `No instruments match your filters`, which points at filters that are too tight or that contradict each other. A screener backtest is a longer job and reports more. Before it has ever run, the band carries no status at all and the panel shows the never-run preview instead. While it runs the action reads `Backtesting {percent}%` and the panel shows `Computing performance across six horizons` with that percentage — that running display covers the whole wait, from the moment you start the backtest until the results appear. On failure the status reads `Failed` and the action becomes `Retry backtest`. A failed backtest is kept for the same limited time as a finished one, so pressing `Retry backtest` inside that window brings back the same failure at once rather than computing again; after it ends — at the latest with the daily data refresh — a retry computes in full. While market data is being loaded the band reads `Refreshing data…` instead of computing. Editing a filter afterwards does not invalidate the result on screen: the banner reads `Out of date — filters changed since the last backtest. Showing the previous run.` until you re-run it. ## Why do I get the same matches every time — and why is a re-run backtest instant? For two different reasons. **Matches** are computed on every run: you get the same list because the same filters over the same day's data produce the same result, and it changes the moment either side changes. A **screener backtest** you have already run comes back without computing again, which is why opening it a second time shortly afterwards returns at once. That reuse lasts a limited time, not the whole day, and it can end sooner than that: once it ends, the next backtest computes in full again on the same data. The daily data refresh is the one event that ends both. When the daily market-data refresh advances the frontier, a match run starts producing different numbers and the first backtest of the new day computes in full again — so its figures can differ slightly from yesterday's even though you changed nothing. No result ever straddles a refresh. ## How does Fincanva handle it? - A screener always runs against the most recent loaded market close; there is no option to run it as of another date. - A match is an [instrument](/docs/getting-started/instrument), not a ticker string: it is listed under its current ticker and name, but its identity is its [permanent instrument identifier](/docs/data-methodology/permanent-instrument-identifier), so a company that changes ticker does not become a different match. - While market data is loading, a screener reports the refreshing state instead of computing — it never returns a partial or stale answer as if it were current. - A screener backtest re-runs the screener on every monthly screening date from 2000 to the frontier, which is why it takes long enough to report progress while a match run does not. - A result belongs to the screener that produced it, not to the account that asked for it — the same principle as [shared compute](/docs/backtesting/shared-compute) for strategies. ## What does it look like in practice? You open a screener with four filters and run it: the results area shows `Refreshing matches…` for a moment, then lists 47 matches. You loosen one filter and run again — a different screener now, so a different answer: 88 matches. You put the filter back and run once more: 47 again, recomputed from scratch but identical, because the filters and the day's data are the same as the first time. Now the backtest. You press `Run backtest`, watch it pass through `Backtesting 62%`, and the horizon returns appear when it finishes. You leave the page, come back twenty minutes later and press `Run backtest` again — the view did not keep the earlier result, but the answer returns at once instead of computing, served from the result already held — it is still within the limited time that result is kept. The next morning, after the overnight refresh has advanced the frontier by one trading day, the same backtest computes from the start, and its horizon returns shift slightly with the extra day of data. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/screeners/screener-backtest-benchmark # Screener-backtest benchmark The screener-backtest benchmark is the reference a [screener backtest](/docs/screeners/screener-backtest) measures itself against, which is why every headline figure such a backtest reports is a *gap* rather than a return: the screener's result minus the benchmark's result over the same holding horizon. A screen that averaged 10% a year in a stretch when the benchmark also averaged 10% a year showed no edge at all, even though 10% reads well on its own. Which series the benchmark is, and how it is put together, are not documented — Fincanva has not released either, so this page covers what the benchmark *does* and not what it is. **Also seen as:** Benchmark universe ## Why is a screener's result only meaningful next to its benchmark? Because a raw return over a long window mixes two things that a screener cannot take equal credit for: the market's own move across the period, and whatever the filters added on top of it. Over a run that spans decades the first of those dominates — most instruments rose, so most screens produce a positive number, and a positive number is therefore no evidence that the filters did anything. Subtracting the benchmark removes the shared part and leaves the part attributable to the screen, the same logic that [excess return](/docs/analysis/excess-return) applies to a strategy. That is also why the *level* of the figure is not the finding. Two screens that both returned 12% a year are not equally good if one ran in a decade the benchmark returned 5% and the other in a decade it returned 14%. ## How does the benchmark shape the numbers you read? In four ways, each of which changes how a verdict should be read: - **The verdict is directional.** A screener is reported as being above the benchmark, below it, or level with it — never as a bare return. - **Zero is a tie, not a win.** A gap of exactly zero resolves to neutral wording rather than being rounded up into a win. - **The gap is in percentage points.** It is the difference between two percentages, so a screener at 12% against a benchmark at 9% is +3 pp — three points of annualized return above the benchmark, not "3% more". - **There is one gap per [holding horizon](/docs/screeners/holding-horizon).** The benchmark is measured over the same set of holding horizons as the screener, so each horizon compares like with like — and a screener can be ahead at one horizon and behind at another. The benchmark is also drawn alongside the screener on the [event-time path](/docs/screeners/event-time-path), so the two can be read together rather than one at a time. ## Can I choose the benchmark for a screener backtest? No. Unlike a strategy's [benchmark](/docs/getting-started/benchmark), which you pick per strategy from market presets or — on the plans that include them — from one of your own live portfolios, a [screener backtest](/docs/screeners/screener-backtest) arrives with its benchmark already decided: there is no benchmark control on a screener's **Backtest** tab. The practical consequence is that a screener verdict and a strategy's benchmark comparison are two different measurements, and a figure from one should not be read as if it came from the other. ## Is the verdict a statement about what my strategy will hold? No — it is a measurement of the screener's [matches](/docs/screeners/matches) as a group. A strategy built on the same screener holds a trimmed, liquidity-ranked slice of those matches (see [max-symbols cap](/docs/screeners/max-symbols-cap)) and applies its own allocation, exit rules, and costs on top, so its result is a different quantity from the screener's verdict. Fincanva does not tell you whether a verdict is good enough to act on — see [Is this financial advice?](/docs/investing-theory/is-this-financial-advice). ## How does Fincanva handle it? - Every screener-backtest figure labelled above or below the benchmark is a comparison, not an absolute return measured from zero. - The comparison is a difference between two annualized figures, so it is read in percentage points. - A gap of zero is reported as level with the benchmark rather than as an outperformance. - The benchmark covers the same period and the same holding horizons as the screener, so both sides move when new market data arrives and the backtest is re-run (see [screener execution and caching](/docs/screeners/screener-execution-and-caching)). - The benchmark cannot be selected, changed, or switched off for a screener backtest. - Not every figure in a screener backtest is a gap against this benchmark: the per-filter impact table mixes a raw return with two deltas measured against other filter sets — see [filter impact lenses](/docs/screeners/filter-impact-lenses). ## What does it look like in practice? At the 12-month holding horizon a screener's matches averaged +10.8% annualized, while the benchmark averaged +7.8% over the same horizon. The verdict is the difference: **+3.0 pp annualized above the benchmark at 12 months**. The same run at the 1-month horizon tells a different story — the screener averaged +9.4% against the benchmark's +10.0%, a gap of **−0.6 pp**, so at that horizon the screen was behind. One screener, one run, two horizons, opposite signs. Note what the two absolute figures (+10.8% and +9.4%) cannot tell you on their own: both are solidly positive, yet one horizon beat its benchmark and the other did not. The level says how the period went; only the gap says what the screen contributed to it. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/screeners/sequential-filtering-and-top-n-ranking # Sequential filtering and Top-N ranking Sequential filtering is the way a screener applies its filters: one at a time, in the order they sit in the filter strip, each one narrowing the instruments the previous filters left. Top-N ranking is what the **Highest** and **Lowest** operators do inside that sequence — they keep the top or bottom N instruments on a metric, ranked among whatever is still passing at that point rather than across the whole universe. This is why a ranking filter's position in the list changes the result, while a threshold filter's position does not. **Also seen as:** filter order, the filter funnel, Top-N, best N ## How does a screener apply its filters? A screener starts from its [universe](/docs/getting-started/universe) and hands that set to its first filter. The instruments that pass become the input to the second filter, those survivors become the input to the third, and so on to the end of the list. What comes out of the last filter is the set of [matches](/docs/screeners/matches). That set is also what a [screener backtest](/docs/screeners/screener-backtest) measures. Because every filter has to be satisfied, the filters combine with AND and the count can only fall or stay level as you go down the list — a funnel, never a fork. If one filter leaves nothing, the screener has no matches and the filters after it have nothing left to narrow. ## Why does filter order matter? Order matters because **Highest** and **Lowest** rank the survivors at their own position, not the universe. Move a ranking filter and you change the pool it ranks, so you change which instruments come out — even though the rules themselves are identical. Threshold filters — `<`, `≤`, `=`, `≥`, `>`, Between — are order-independent among themselves: an instrument either clears a threshold or it does not, whatever ran before. Put one of them before a ranking filter and it shrinks the pool the rank draws from; put it after and it trims the ranked set. Both are legitimate screens; they are different screens. ## What does a Highest or Lowest filter keep? A Highest or Lowest filter keeps **at most N instruments** — the count you set, taken from the instruments still passing at that point. It can return fewer than N in two situations: when fewer than N instruments are still in the running, and when some of the survivors have no reading for that metric, because an instrument that cannot be measured cannot be ranked and drops out. Note what Top-N does *not* say: it selects by relative position, not by level. The "highest 10" on a metric are the highest of that particular pool, which says nothing about whether their readings are high in absolute terms. ## How does Fincanva handle it? - Filters run in the order they sit in the filter strip, which is the order you added them; the strip has no reorder control today, so changing the order means removing a filter and adding it again. - A ranking filter's count defaults to 5, and its stop list runs 1 to 15 one at a time, then in widening steps up to 300. - **Highest** and **Lowest** sit in the **Rank** group of a filter's operator dropdown, and only filters whose catalogue entry declares them offer them. See [standard operators](/docs/screeners/standard-operators). - A ranking filter reads the same metric as any other filter on that metric, including its **Advanced** settings, so "Highest 10 by revenue four reports ago" is a valid rank. - The [match count](/docs/screeners/matches) reflects the end of the whole sequence, not any intermediate stage. A strategy fed by that screener may work with fewer candidates than the count shows — see [max-symbols cap](/docs/screeners/max-symbols-cap). ## What changes when the same two rules run in both orders? A screener over 500 US stocks with two filters: `P/E < 20` and `Highest 10` on ROE. **Order A — threshold first, then rank.** | Step | Filter | In | Out | |---|---|---|---| | 1 | `P/E < 20` | 500 | 120 | | 2 | `Highest 10` on ROE | 120 | 10 | The result is the 10 most profitable stocks *among the cheaper half* — every one of them trades below 20× earnings. **Order B — rank first, then threshold.** | Step | Filter | In | Out | |---|---|---|---| | 1 | `Highest 10` on ROE | 500 | 10 | | 2 | `P/E < 20` | 10 | 3 | The rank now runs across all 500 stocks, so it returns the market's 10 most profitable companies — which tend to be expensive. The P/E filter then cuts that list of 10 down to the 3 that happen to trade below 20× earnings. Same two rules, same universe, same day: 10 instruments one way and 3 the other, with a completely different character. Order A asks "who is most profitable among the cheap ones"; Order B asks "of the most profitable companies, which are cheap". Reading a ranking filter's position as part of the rule, not as cosmetic list order, is the habit that stops this surprising you. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/screeners/special-relations # Special relations Special relations are the pattern tests that a small number of [screener](/docs/getting-started/screener) filters offer in place of the numeric operators — they ask whether something *happened* or which *state* an instrument is in, rather than whether a reading clears a threshold. There are fifteen of them, spread across six filters, in three families: **crossings**, **price against a line**, and **valuation bands**. A special relation never takes a threshold value; where it takes a number at all, that number is a time window, not a level. **Also seen as:** special strings, pattern relations, cross relations ## What does each special relation test? The relation names in the editor are the full labels; the chip shows a shorthand code. `{N}d` in a chip is the window in days, not a threshold. | Relation | Chip code | Offered on | Tests whether | |---|---|---|---| | Crosses Above | `X-Above {N}d` | SMA, Bollinger Bands, Mkt SMA, Sec SMA | the price crossed up through the line within the last N days | | Crosses Below | `X-Below {N}d` | SMA, Bollinger Bands, Mkt SMA, Sec SMA | the price crossed down through the line within the last N days | | Price Above | `> Price` | SMA, Bollinger Bands, Mkt SMA, Sec SMA | the price is currently sitting above the line | | Price Below | `< Price` | SMA, Bollinger Bands, Mkt SMA, Sec SMA | the price is currently sitting below the line | | Fast Bullish Cross | `Fast Bull-X {N}d` | Stochastic | the fast line crossed up within the last N days | | Fast Bearish Cross | `Fast Bear-X {N}d` | Stochastic | the fast line crossed down within the last N days | | Slow Bullish Cross | `Slow Bull-X {N}d` | Stochastic | the slow line crossed up within the last N days | | Slow Bearish Cross | `Slow Bear-X {N}d` | Stochastic | the slow line crossed down within the last N days | | Fast/Slow Bullish Cross | `F/S Bull-X {N}d` | Stochastic | the fast line crossed up through the slow line within the last N days | | Fast/Slow Bearish Cross | `F/S Bear-X {N}d` | Stochastic | the fast line crossed down through the slow line within the last N days | | Strongly Overvalued | `Strongly Overvalued` | Buffett Indicator | the market's valuation reading sits in the highest band | | Overvalued | `Overvalued` | Buffett Indicator | the reading sits in the band below that | | In Range | `In Range` | Buffett Indicator | the reading sits in the middle band | | Undervalued | `Undervalued` | Buffett Indicator | the reading sits in the band below the middle | | Strongly Undervalued | `Strongly Undervalued` | Buffett Indicator | the reading sits in the lowest band | The five valuation bands are mutually exclusive: on any given date the reading is in exactly one of them, so picking two bands in two conditions on the same date yields nothing. ## What is the window on a cross relation? The number on a cross relation is a **lookback window in trading days**, and the condition passes when the crossing happened at any point inside it. The choices are 7, 14, 21, and 28 days, and 28 is the default — so out of the box a cross relation asks "has this crossed in the last four weeks", not "did it cross today". A shorter window makes the test stricter, because the crossing has to be more recent to count. **Price Above** and **Price Below** carry no window. They describe where the price is right now relative to the line, so they stay true for as long as the price stays on that side, while a cross relation goes false once the crossing ages past the window. ## Is Crosses Above the same as a golden cross? No — Crosses Above tests the *price* against one moving average, while a golden cross is conventionally a *faster moving average* crossing above a slower one. The two are related signals but not the same test: with Crosses Above there is one line on the chart and the price crosses it; with a golden cross there are two lines and they cross each other. The relations that do compare two lines to each other are the Stochastic filter's **Fast/Slow** pair, and there the two lines are the oscillator's fast and slow lines, not a pair of moving averages. So "golden cross" is a useful mental picture for what Crosses Above signals, and the wrong description of what it measures. ## How does Fincanva handle it? - Only six filters carry special relations: SMA, Bollinger Bands, Stochastic (Technical → Indicators), Mkt SMA and Buffett Indicator (Market & Sector → Market Technical and Market Fundamental), and Sec SMA (Sector Technical). - On a filter that has them, the special relations replace the numeric operators rather than sitting alongside them, and each one is its own choice in the editor. - The eight cross shorthand codes stay in English in every language (`X-Above 28d`, `F/S Bull-X 14d`); the Price Above and Price Below chips and the five valuation-band chips are translated. - A filter's **Advanced** inputs still apply. The SMA filter's `Bars` input sets how long the moving average is, and `Months Ago` shifts the whole reading back in time; see [lag, period, and multiplier](/docs/screeners/lag-period-and-multiplier). - Because Mkt SMA and Buffett Indicator read the market rather than an instrument, a condition on them gates the entire screen: on a date where it fails, the screener returns no matches at all. Sec SMA gates whole sectors the same way. See [filter taxonomy](/docs/screeners/filter-taxonomy). - Fincanva describes what these relations detect. It does not rate a crossing as bullish or bearish for your purposes, and a relation being true is not a signal to act. ## What does a bullish moving-average cross look like? Take the [SMA](/docs/strategies/simple-moving-average-sma) filter with its default 252-bar average — roughly one trading year — on a stock that has been below that average for months and then rallies through it eight trading days ago. - Pick **Crosses Above** and leave the window at its default of 28 days. **You're saying** reads "SMA crosses above (28 days)." The crossing happened 8 days ago, which is inside the window, so the stock passes and the chip reads `SMA (252) X-Above 28d`. - Narrow the window to 7 days. The same crossing is now 8 days old, one day outside the window, and the stock stops passing — with no change to its price at all. - Switch to **Price Above** instead. The window disappears, and the stock passes for as long as its price stays above the 252-bar average, whether it crossed eight days ago or eight months ago. The three conditions read the same chart and select different things: a recent event, a recent-enough event, and a current state. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/screeners/standard-operators # Standard operators Standard operators are the comparisons a screener filter can apply to a metric — the choices in a filter's operator dropdown. There are eight, offered in three labelled groups: **Compare** (`<`, `≤`, `=`, `≥`, `>`), **Range** (Between), and **Rank** (Highest, Lowest). The operator decides how the metric's reading is tested; it does not change which metric is read. **Also seen as:** comparison operators, comparators, relations ## What does each operator group do? The three groups test three different kinds of thing: a threshold, an interval, and a position in a ranking. | Group | Operator | Reads as | Passes when | |---|---|---|---| | Compare | `<` | less than | the reading is below your value | | Compare | `≤` | at most | the reading is below your value, or exactly equal to it | | Compare | `=` | equals | the reading matches your value exactly | | Compare | `≥` | at least | the reading is above your value, or exactly equal to it | | Compare | `>` | greater than | the reading is above your value | | Range | Between | between … and … | the reading falls inside the low–high range, both ends included | | Rank | Highest | is among the highest … | the instrument is in the top N on that metric | | Rank | Lowest | is among the lowest … | the instrument is in the bottom N on that metric | **Compare** takes one value. **Range** takes two, a low and a high. **Rank** takes a count, not a threshold — you say how many instruments to keep, not what the metric has to read. ## Which boundary values pass? `<` and `>` are strict, so a reading that sits exactly on your value fails them; `≤` and `≥` include that boundary. Between includes both of its ends: $$ \text{min} \le \text{reading} \le \text{max} $$ where: `min` and `max` are the low and high values you set, and a reading equal to either one passes. This is the difference that surprises people most often, because the two operators sit next to each other in the dropdown and their labels read almost identically. `≤` is "at most", not "less than". ## How does Fincanva handle it? - Each [filter](/docs/getting-started/filter) offers only the operators its catalogue entry declares, so the dropdown differs from filter to filter and a group with nothing to show is hidden rather than shown empty. `=` is the rarest — one filter offers it. - A filter arrives with a default operator already selected, and it is not always a Compare operator: the ROE filter opens on `>`, the P/E filter opens on Between. - Compare and Range values snap to the stops that filter offers: type any number and it moves to the nearest stop on Enter or on blur. - Rank counts come from their own stop list, running 1 to 15 one at a time and then in widening steps to 300; the default is 5. - Rank behaves differently from the other two groups because it depends on which instruments are still in the running when it runs — see [sequential filtering and Top-N ranking](/docs/screeners/sequential-filtering-and-top-n-ranking). - The same Compare operators are reused when you compare a metric to its own earlier reading or to a market or sector figure, with one exception: `=` is not offered against the metric's own earlier reading. See [comparison modes](/docs/screeners/comparison-modes) and [aggregate comparisons](/docs/screeners/aggregate-comparisons). - A few filters replace the standard operators entirely with pattern tests — crossings and valuation bands. Those are [special relations](/docs/screeners/special-relations). ## How do less than and at most differ on the boundary? Take a P/E filter and a company whose price/earnings ratio reads exactly 20.0. - Set the operator to `<` and the value to 20.0. **You're saying** reads "P/E is less than 20.0." The company at exactly 20.0 **fails** — the test is strict, so 20.0 is not below 20.0. - Change the operator to `≤`, leaving the value at 20.0. **You're saying** now reads "P/E is at most 20.0." The same company **passes**. Nothing else changed: the same metric, the same value, the same instrument, one operator apart. If a filter drops an instrument you expected to keep, and its reading sits exactly on your threshold, the strict operator is usually the reason. Note that the value itself has to exist as a stop on that filter's scale — the P/E filter steps in halves, so 20.0 is available but 20.2 snaps to 20.0. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/screeners/ttm-and-yoy # TTM and YoY TTM and YoY are two shorthands you meet in fundamental filters and in the **Unit line** under a [results column header](/docs/screeners/fundamental-metric-columns). **TTM (trailing twelve months)** sums the last four reported quarters into a rolling one-year figure that always ends at the most recent report, rather than at a fiscal year-end. **YoY (year over year)** compares a figure to the same figure one year earlier, showing the change over a full year and cancelling out seasonal ups and downs. **Also seen as:** LTM ## How is a year-over-year change calculated? A year-over-year change is the difference between the current figure and the figure one year earlier, divided by that earlier figure. $$ \text{YoY} = \frac{V_{t} - V_{t-1\text{yr}}}{V_{t-1\text{yr}}} $$ where: $V_{t}$ is the current value and $V_{t-1\text{yr}}$ is the value one year earlier. ## Why TTM and YoY are used TTM gives an up-to-date annual figure between fiscal year-ends: instead of waiting for the full-year accounts, it adds the four most recent quarters, so the number moves every reporting season. YoY strips out seasonality: comparing this quarter to the same quarter last year avoids the distortion of holding a holiday quarter against a summer one. ## What does it look like in practice? Suppose a company's fiscal year ends in December. After it reports Q3, its **fiscal-year revenue** still shows last December's full-year total — up to nine months stale. Its **TTM revenue** instead sums Q4 of last year plus Q1, Q2, and Q3 of this year, giving a rolling twelve-month total that already reflects the most recent quarter. If that TTM figure is 8% above the TTM a year earlier, its revenue **YoY** is +8%. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/screeners/universe-facets # Universe facets Universe facets are the fields a [screener](/docs/getting-started/screener) uses to narrow its [universe](/docs/getting-started/universe) before any metric filter runs: **Country**, **Exchange**, **Asset subtype**, **Index**, **Sector**, and **Currency**, all sitting under a single [**Asset type**](/docs/getting-started/asset-type). Each facet is a multi-select chip on the filter strip, and a facet with nothing selected reads **All**, which restricts nothing. Facets decide *which instruments a screener may consider*; they never test a metric, so they run ahead of every [metric filter](/docs/getting-started/filter) and set the pool the [match count](/docs/screeners/matches) is drawn from. **Also seen as:** universe filters ## What each universe facet narrows [Asset type](/docs/getting-started/asset-type) is chosen first, and it decides which facets exist below it — the facets for stocks are not the facets for exchange-traded products. | Facet | Narrows the universe to | Available on | |---|---|---| | Asset type | Stocks, ETPs, or Crypto — exactly one at a time | always | | Country | USA Domestic, Canadian, ADR, EU (stocks); USA, EU (ETPs) | Stocks, ETPs | | Exchange | NYSE, NASDAQ, NYSE MKT, OTC, EU listed — plus NYSE ARCA and BATS for ETPs | Stocks, ETPs | | Asset subtype | Common, Common (secondary), Preferred (stocks); ETF, ETN, ETC, CEF, ETD, ETMF, Unit (ETPs) | Stocks, ETPs | | Index | NASDAQ 100, Dow 30, S&P 100, S&P 400, S&P 500, S&P 600, Russell 2000, STOXX 600 | Stocks | | Sector | the eleven sectors, from Basic Materials to Utilities | Stocks | | Currency | USD, EUR, GBP | ETPs | Crypto exposes no facets at all: choosing it selects the whole crypto set with nothing further to narrow. The [asset-subtype](/docs/screeners/asset-subtypes) abbreviations have their own page, because ETF, ETN, ETC, CEF, ETD, and ETMF describe genuinely different instrument structures. ## What "All" on a facet means **All** on a facet means "no restriction on this field" — every value passes, and the facet takes nothing out of the universe. Selecting *every* option in a facet has the same effect as All, because a facet only narrows anything when some, but not all, of its options are chosen. That is also why a facet you have opened up completely stops behaving like a restriction: its chip may still read a count, but nothing is being excluded. ## How Reset differs from Remove on a facet chip **Reset** (the ↺ button inside the facet's list) returns that one facet to its **default** selection, which may itself be a restriction. **Remove** (the ✕ on the chip) clears the facet to **All** and drops the chip from the strip. The two therefore end in different places: on Country, Reset returns you to USA Domestic + Canadian + ADR, while Remove opens the screener to every country group. The ↺ button appears only while a facet is away from its default, so its presence is itself the signal that you have changed that field. ## How does Fincanva handle it? - Asset type starts on **Stocks**. - For stocks, Country starts at **USA Domestic, Canadian, ADR** (EU off) and Asset subtype starts at **Common**; Exchange, Index, and Sector all start at **All**. - For ETPs, Country starts at **USA**; Currency, Exchange, and Asset subtype all start at **All**. - Switching asset type hides the other type's facets rather than deleting them — the app warns "Switching to `{target}` hides these universe filters: `{filters}`. You can restore them by switching back." — and switching back restores exactly what you had. - Facets combine with AND, and with each other and the metric filters, so adding a facet can only lower the match count or leave it unchanged. ## What does it look like in practice? You want large US technology names listed on one exchange, expressed in three chips. Start from the stock defaults, then set **Country: USA Domestic** — one selection instead of the default three, so ADR and Canadian listings drop out. Add **Exchange: NYSE**, which moves that facet from All to a single venue and removes every NASDAQ, OTC, and EU-listed instrument. Add **Sector: Technology**, again from All to one value. The universe is now "US-domestic technology stocks listed on NYSE", and only then do metric filters such as `Market cap > $10B` start testing what is left. Press ✕ on the Exchange chip and it returns to All — every venue is back; press ↺ inside the Country facet instead and it returns to USA Domestic + Canadian + ADR, not to All. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/changelog # Screener results open sorted by market cap **2026-09-23** · screeners · 2026.09 A screener's results table now opens ordered by market cap, largest first, on every tab and on both the app's workspace and the embedded screener. Where an instrument carries no market cap — exchange-traded products, crypto, index and macro series — that order has nothing to sort by; see [read your matches](/docs/screeners/read-your-matches) for what the table shows in that case. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/backtesting/how-backtesting-works # How backtesting works A backtest takes your strategy's saved rules and replays them across real market history — buying, selling and rebalancing exactly as those rules say — to produce an equity curve and the metrics that summarise it. It reads the strategy and changes nothing in it, and it covers history up to the latest available market close. A backtest is evidence about what those rules would have done in the past, never a forecast of what they will do next. ## What happens when you run a backtest? A backtest runs in four steps: your rules go in, Fincanva replays them through history, the replay produces an equity curve, and the curve is distilled into metrics. 1. **Rules.** The strategy you saved — its [universe](/docs/getting-started/universe), its allocation, its risk conditions, its exit rules. A run only reads them, so running a strategy never changes it. See [Backtest](/docs/getting-started/backtest). 2. **Historical replay.** Fincanva steps forward through real market history and applies those rules date by date, resetting holdings to their targets on the cadence you set. See [Rebalance](/docs/backtesting/rebalance). 3. **Equity curve.** The strategy's value on every simulated date, plotted as one line — the whole path it would have taken, not only where it ended. See [Equity curve](/docs/analysis/equity-curve). 4. **Metrics.** The curve distilled into numbers: [CAGR](/docs/analysis/cagr), [Sharpe ratio](/docs/analysis/sharpe-ratio), [Max drawdown](/docs/analysis/max-drawdown) and the rest. See [What every number in Performance Metrics means](/docs/analysis/what-every-number-in-performance-metrics-means). {/* VISUAL: svg-diagram — the four steps left to right (rules → historical replay → equity curve → metrics), each box naming what enters it and what leaves it — tracked in VISUAL_BACKLOG */} ## What does a backtest actually produce? A backtest produces two things you read directly: an equity curve, and a record of how the holdings moved between rebalance dates. The [equity curve](/docs/analysis/equity-curve) is drawn against its [benchmark](/docs/getting-started/benchmark), so the shape of the result is visible and not only its final figure. Falls below a previous peak show up as dips in the line — the same falls the [Max drawdown](/docs/analysis/max-drawdown) figure reports as a single number. Figure — equity-curve: an equity curve rising across a historical period with a flatter benchmark line beside it; each stretch where the line sits below its previous high is a drawdown. The second output is what happens to the holdings between one [rebalance](/docs/backtesting/rebalance) and the next. Between rebalances the actual weights pull away from the target weights — [weight drift](/docs/backtesting/weight-drift). On each scheduled rebalance date they snap back to target. Nothing corrects drift in between, so a mid-period portfolio is a drifted one, not the target mix. {/* VISUAL: svg-diagram — one holding's weight over time against a dashed target line: it drifts upward between rebalance dates and drops back to the target line at each one — tracked in VISUAL_BACKLOG */} ## What biases does a backtest remove? A backtest removes one of the classic research biases outright, reduces several more, and leaves the rest to the person building the strategy. [The nine biases Fincanva helps you avoid](/docs/getting-started/the-nine-biases-fincanva-helps-you-avoid) is the canonical account of all nine; the four below are the ones that bear most directly on a single run. - **[Survivorship bias](/docs/investing-theory/survivorship-bias) — removed.** Delisted instruments are retained and index membership is resolved as of the simulated date, so a run is measured against the market as it stood on each historical date. The choice of universe and period stays yours — see [How does Fincanva handle survivorship bias?](/docs/getting-started/the-nine-biases-fincanva-helps-you-avoid#how-does-fincanva-handle-survivorship-bias). - **[Overfitting](/docs/investing-theory/overfitting) — still yours.** It comes from how you build the strategy, not from the computation, so no engine removes it. See [How does Fincanva reduce overfitting?](/docs/getting-started/the-nine-biases-fincanva-helps-you-avoid#how-does-fincanva-reduce-overfitting). - **[Look-ahead bias](/docs/investing-theory/look-ahead-bias)** — see [How does Fincanva reduce look-ahead bias?](/docs/getting-started/the-nine-biases-fincanva-helps-you-avoid#how-does-fincanva-reduce-look-ahead-bias). - **[Cost-ignoring bias](/docs/investing-theory/cost-ignoring-bias)** — see [How does a Fincanva backtest account for trading costs and taxes?](/docs/getting-started/the-nine-biases-fincanva-helps-you-avoid#how-does-a-fincanva-backtest-account-for-trading-costs-and-taxes) and [Simulation assumptions](/docs/backtesting/simulation-assumptions). ## Limits and edge cases - **A backtest covers history up to the latest available market close.** New market days keep arriving, so a finished run ages. A strategy you have marked Live is re-run for you as new data lands; one you have only saved is not — its [run status](/docs/backtesting/run-status) turns **Needs re-run** after a data refresh and stays there until you run it again. - **A short history shortens the run.** A backtest can only cover the period for which the chosen instruments have data, so one instrument with a short history limits how far back the whole run can go. - **Rebalance dates are discrete.** Weights are reset only on the cadence you set, never continuously, so drift between two rebalance dates is part of the result rather than a flaw in it. - **A run can end early.** If a strategy's value collapses far enough, the run stops trading — see [Bankruptcy rules](/docs/backtesting/bankruptcy-rules). - **Evidence is not a promise.** Removing a bias makes the past more honest; it does not make the future more certain. Read every result as "what these rules would have done", never as "what these rules will do". Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/backtesting/bankruptcy-rules # Bankruptcy rules Bankruptcy rules are the thresholds at which a simulated run is treated as wiped out: when the value being tracked falls to 10% of the capital it started from — a total loss of more than 90% — every position is closed and no further trading happens. The rule applies at two levels, the whole run and each strategy inside a [Combined](/docs/getting-started/strategy-in-a-combined), and the two behave differently afterwards. A third, rarer case exists: a price move that jumps straight past the floor into negative capital, which ends the run as **Failed** instead. **Also seen as:** 10% floor, total loss ## When is a run treated as bankrupt? When its value crosses below one tenth of its reference capital, checked at each daily close. Both levels use the same test on a different reference: the whole run measures against the capital it started with, and a strategy inside a Combined measures against the capital most recently allocated to it. $$ \frac{V_t}{V_0} - 1 < -0.9 $$ where: $V_t$ is the value at the close of day $t$; $V_0$ is the reference capital — the starting capital for the whole run, or the capital last allocated to that strategy inside a Combined; and $-0.9$ is the threshold, a loss of 90%. Reaching it is the same thing as a [total return](/docs/analysis/total-return) worse than −90% against that reference. ## What happens after the whole run goes bankrupt? Everything closes and the curve stays flat. All positions are liquidated on the day the floor is crossed, no new positions are opened, and the capital curve runs flat from that day to the end of the [backtest](/docs/getting-started/backtest). It is permanent for that run: the whole-run test measures against the original starting capital and is never re-armed, so a later market recovery cannot restart it. The run still completes and its results are served normally — the flat line and the metrics that follow from it **are** the result, not an error, and the [run status](/docs/backtesting/run-status) reads **Up to date** like any other finished run. ## What happens after one strategy inside a Combined goes bankrupt? That strategy is closed, and it can come back. The same 90% test is applied to each strategy inside a Combined against the capital last allocated to it; a strategy that crosses the floor has its positions closed and stops trading, while the rest of the Combined carries on. Because its reference capital is reset every time capital is routed to it, a later [rebalance](/docs/backtesting/rebalance) that allocates to that strategy starts it again from the new amount. So a strategy's bankruptcy inside a Combined is a gap in that strategy's participation, not the end of it. ## What is a sudden move to negative capital? A gap large enough to skip the floor entirely. If a price move takes the value straight from above the threshold to below zero — rare, and associated with leveraged exposure — there is no valid state left to continue from, and the simulation is marked **Failed** rather than flatlined. A **Failed** run has no results to read; the distinction matters because the ordinary bankruptcy case does produce a full, readable result. ## How does Fincanva handle it? - The threshold is fixed at 10% of the reference capital and is not a setting you can change or switch off. - It is evaluated at each daily close, so a level breached and recovered within a single day is not what the test reads. - The whole-run case is permanent for that run; the case for a strategy inside a Combined is restartable at a later rebalance. - A bankrupt run is a completed run: the flat curve, the drawdown and the metrics are all reported. - The rule is a stopping condition inside the simulation: it describes what the backtest does when the floor is crossed, not what a broker or an exchange would do. ## What does it look like in practice? A strategy starts with \$100,000 and holds a leveraged position. During a sharp decline its value falls to \$9,500 at a daily close — below the \$10,000 line that is 10% of the starting capital — so the run is treated as bankrupt: every position is closed that day and the capital curve is flat from there to the end of the backtest, even though the market recovered afterwards. The result is still served in full, showing a maximum [drawdown](/docs/analysis/max-drawdown) of about 90% and a flat tail. Now the same test one level down. A Combined allocates \$10,000 to one of its strategies at the January rebalance; that strategy falls to \$900 by March — below 10% of the \$10,000 it was given — so it is closed and stops trading while the Combined's other strategies continue. At the July rebalance the Combined allocates to it again, \$8,000 this time; its reference capital is now \$8,000, and it resumes trading from there. The same strategy has therefore been bankrupt and active within one backtest, which the whole-run case can never be. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/backtesting/base-currency # Base currency Base currency is the currency your simulation results are reported in — the one currency every portfolio-level figure is converted into and labelled with. It is set in Settings under "Simulation defaults" as **Base currency** ("Currency in which simulation results are reported."). It is deliberately separate from an [instrument's](/docs/getting-started/instrument) own **asset currency**, the currency that instrument trades and is quoted in: a base currency of EUR can hold a US stock quoted in USD, and Fincanva converts that holding into EUR for every portfolio figure while still showing the stock's own price in USD. **Also seen as:** reporting currency, account currency ## What is the difference between base currency and asset currency? Base currency is yours; asset currency belongs to the instrument. - **Base currency** is a single choice you make once. Portfolio value, [target notional](/docs/portfolio-holdings/target-notional), deployed amounts, cash, and every band of the [P&L breakdown](/docs/analysis/p-l-breakdown) are expressed in it, so totals across a mixed-currency portfolio are addable. - **Asset currency** is a property of the instrument and cannot be changed. A share price, a dividend per share, and an execution price are quoted in the currency the instrument actually trades in. Amounts in an asset currency are converted into your base currency at the exchange rate for the date in question, so a foreign holding's contribution reflects both the instrument's own move and the currency's move over the period. ## Which currencies can I choose? Six base currencies are selectable today: **USD** (the default), **EUR**, **GBP**, **CHF**, **CAD**, and **AUD**. Asset currencies are a wider set, because they follow the market an instrument is listed on rather than your preference. Fincanva's price data carries thirteen currency codes: USD, EUR, GBP, GBX, CHF, CAD, AUD, NZD, JPY, SEK, NOK, DKK, and PLN. GBX is pence sterling — one hundredth of a pound — the quoting convention some London listings use, so a GBX price looks a hundred times larger than the same price in GBP. ## How does Fincanva handle it? - On the Holdings view's "Target positions & exits" sheet, the **"Last"** column is the instrument's own last price, shown in its **asset** currency and at that instrument's own precision. This is the column that surprises people: in a EUR account, a US holding's "Last" is still a dollar figure. - The same sheet's **"Target value"** column is the base-currency amount, with the asset-currency amount underneath it as a second line — and that second line appears only when the two currencies differ, so a same-currency holding shows one figure rather than the same number twice. - Base currency is part of what identifies a simulation, so changing it means the results for your own strategies are recomputed in the new currency rather than converted after the fact. - A public strategy you do not own is always reported in USD, whatever your own base currency is, so that every viewer sees the same figures. - The [starting capital](/docs/backtesting/starting-capital) options are displayed in whichever base currency you have selected — the amount is the same number, denominated in that currency. ## What does it look like in practice? Your base currency is EUR and your strategy holds Apple, which trades on NASDAQ in USD. On the Holdings sheet, Apple's "Last" reads as a dollar price, because that is the currency it is quoted in. Its "Target value" reads as a euro amount — the amount of your euro capital assigned to it — with the equivalent dollar amount as a second line beneath, because the two currencies differ. The portfolio's "Target notional" KPI, its cash, and every total on the page are euro figures, so they add up. If the euro strengthens against the dollar over a period, the euro value of that Apple holding falls even when its dollar price has not moved — the currency is part of the result, not separate from it. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/backtesting/capital-gains-tax # Capital-gains tax Capital-gains tax is the tax charged on a **realized gain** — the profit you make when you sell a position for more than you paid for it. It applies only to gains you have actually locked in by closing a position, not to paper gains on holdings you still own. Crucially, it is charged on your **net** result rather than on each winning trade in isolation: realized losses are set against realized gains, and what is left over carries forward to later years. Fincanva can model the tax with two rates, a short-term and a long-term one chosen by how long the position was held, but whether that split exists at all is decided by your [tax residency](/docs/backtesting/tax-residency) — Italy taxes a realized gain at one rate however long it was held. **Also seen as:** CGT, tax on realized gains ## How is capital-gains tax calculated? Capital-gains tax is the applicable rate multiplied by the **taxable gain** — and the taxable gain is your realized gains after realized losses have been set against them, not each winning position on its own. $$ \text{taxable gain} = \text{realized gains} - \text{realized losses set against them} $$ $$ \text{tax} = \text{applicable rate} \times \text{taxable gain} $$ where: **realized gains** and **realized losses** are the profits and losses locked in by positions closed during the year, and the losses that may be set against a gain include losses carried forward from earlier years, under the limits in the next section. The **applicable rate** is the short-term or the long-term rate, decided by your [tax residency](/docs/backtesting/tax-residency) and by how long the position was held. A year whose losses exceed its gains has a taxable gain of zero and carries the remainder forward; it is never a negative tax. This is the difference that changes what a backtest shows you. A strategy that closed one position for +1,000 and another for −400 in the same year is taxed on 600, not on 1,000. Reading the rate against gross gains overstates the drag that taxes put on a strategy — often substantially, for a strategy that trades a lot. Where the residency has both rates, a position sold after only a brief holding period meets the short-term rate and one held longer meets the long-term rate. The app labels the two fields "Short-term capital gains" and "Long-term capital gains". ## How long must a position be held to count as long-term? **More than one year — more than 365 days between opening and closing the position.** A position held for exactly 365 days is still short-term; it has to pass the threshold, not merely reach it. The clock starts when the position is **first** opened. Buying more of an instrument you already hold does not restart it, and selling part of a position is measured from that same first purchase — the clock only resets once the position has been closed completely. The threshold only does anything under the residencies that have two rates: **United States** and **Other**. Under **Italy** there is no short/long split at all, so the holding period does not change the rate — see [tax residency](/docs/backtesting/tax-residency) for which rates each residency starts from and which of them you can edit. ## What happens to a realized loss? A realized loss reduces the gains you are taxed on, and any part of it you cannot use this year is carried forward. **How long it stays usable, and against what, depends on your residency** — and the Italian rules carry an asymmetry that is easy to be caught by. **Under United States and Other residency:** - A loss is first set against gains realized in the same year — and within the year the character does not matter: a short-term loss can reduce a long-term gain, and a long-term loss a short-term gain. - Whatever is left over at the end of the year carries forward with **no time limit** — it stays available for as many years as the backtest runs. - A carried loss **keeps its short-term or long-term character**: a carried short-term loss reduces short-term gains, and a carried long-term loss reduces long-term gains. It does not cross over. - Fincanva does not model the annual deduction of net capital losses against ordinary income that US tax law allows. In a simulation, a loss is only ever useful against capital gains. **Under Italy residency:** - Losses stay usable for **five years**, after which an unused loss simply stops being available. The [tax regime](/docs/backtesting/tax-regime) you select decides how that window is counted: - **Declarative** — the year is settled as a whole: the year's losses are first set against the same year's gains, and a net loss for the year can reduce net gains in the **five years that follow**. - **Administered** — each gain is settled as it is realized: a loss can reduce gains realized **after** it, in the year it was realized and the **four years that follow**. A gain already taxed before the loss happened is not revisited. - There is a **single rate**, so there is no character to preserve — a carried loss reduces any compensable gain. - **A gain on an ETF cannot be reduced by any loss — from the same year or carried forward — but a loss on an ETF can be used to reduce other gains.** The asymmetry runs one way only. ### Why the Italian ETF rule matters to your results If you are modelling a portfolio built mainly of ETFs under Italian residency, **your losses help you and your gains do not.** Every ETF gain is taxed in full, whatever losses you have realized that year or are carrying; every ETF loss still goes into the pool that reduces your other, non-ETF gains. A portfolio of nothing but ETFs therefore gets no benefit from netting at all on the gains side, even in a year that also produced large losses. This applies to instruments Fincanva classifies as **ETFs**. Other exchange-traded products — ETNs, ETCs, closed-end funds — are treated as ordinary compensable instruments in the model, so their gains *can* be reduced by carried losses. ## How does Fincanva handle it? - The rates are percentages of the gain and are seeded from your [tax residency](/docs/backtesting/tax-residency), which is also what decides whether a short/long split exists at all — that page carries the per-residency table and says which fields you can still edit. - Tax is charged only on realized gains, and only when taxes are switched on in your [simulation assumptions](/docs/backtesting/simulation-assumptions); with taxes off it is zero. With taxes on, the value a run reports each day also sets aside the tax its still-open gains would owe if sold that day — see [taxes toggle](/docs/backtesting/taxes-toggle#what-does-turning-taxes-on-change). - The rate is applied in full: the tax charged is the applicable rate on the taxable gain. - When the tax leaves the account follows the [tax regime](/docs/backtesting/tax-regime): once a year, on the year's net result, under **United States**, **Other** and the Italian **Declarative** regime; as each gain is realized under the Italian **Administered** regime. - For Italian residency the rates are set by tax law for the selected [tax regime](/docs/backtesting/tax-regime) and shown as "Auto-updated" rather than edited by hand. ## What does it look like in practice? A strategy closes two positions in the same year: one for a **1,000 gain**, held eighteen months, and one for a **400 loss**. Under **United States** residency the loss is set against the gain first, so the taxable gain is 1,000 − 400 = **600**, not 1,000. The winner was held more than a year, so it is long-term and meets the 20% rate: 20% × 600 = **120 of tax**. Close the same winner at eleven months instead and nothing about the netting changes — the taxable gain is still 600 — but it is now short-term and meets the 35% rate: 35% × 600 = **210 of tax**. The holding period moved the bill by 90 on an unchanged pair of trades. Now give the strategy a **1,400 loss**, on a position held only a few months, instead of a 400 one. Losses exceed gains, so the taxable gain is zero and the tax is **0**. The short-term loss has wiped out the long-term gain within the year, and the unused 400 carries forward as a **short-term** loss — the character of the loss it came from — still available against short-term gains in any later year of the run. Run the same pair under **Italy** residency, on the default **Declarative** regime, and two things change. The single 26% rate applies whatever the holding period was, so both versions give 26% × 600 = **156 of tax**. And if the winner was an **ETF**, the netting does not happen on that side at all: the 1,000 ETF gain is taxed in full, 26% × 1,000 = **260 of tax**, while the 400 loss is not wasted — it stays available against any non-ETF gains the strategy made. Same two trades, same rate, 104 more tax, purely because of what the winner was. Under the **Administered** regime the order of the two trades matters too: if the winner closed first, its 1,000 was taxed when it was realized, and the later 400 loss is carried forward for future gains instead. *These figures describe the tax base Fincanva models in a simulation, not tax advice for your own situation — see [Is this financial advice?](/docs/investing-theory/is-this-financial-advice#is-this-financial-advice).* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/backtesting/cash-drag # Cash drag Cash drag is the market return a strategy gives up because part of its capital sits in cash instead of being invested. It is not a loss — the cash is still there — it is an opportunity cost: over a window in which the market rose, the uninvested share earned none of that rise. The more capital held back, and the stronger the market's move, the larger the drag. **Also seen as:** drag, opportunity cost of cash ## How is cash drag calculated? Cash drag over a window is approximately the cash share of capital multiplied by the market's return over the same window. $$ \text{cash drag} \approx (1 - w) \times r_{\text{market}} $$ where: $w$ is the [invested portion](/docs/backtesting/invested-portion) (the share of capital the allocation profile puts to work), $(1 - w)$ is the cash reserve, and $r_{\text{market}}$ is the market's return over the same dates. It is an approximation because it ignores compounding within the window and whatever the idle cash itself earns. ## What counts as a good value? Cash drag has no target value — it is the price of holding a reserve, and it is only measurable after the fact. Read it against the reason the cash was held: over a window in which the market fell, the same reserve that "dragged" in a rally is what limited the fall. A strategy carrying a large permanent reserve shows drag in most rising windows; a strategy that only holds cash defensively shows it in bursts. Fincanva reports what happened; it does not tell you how much cash to hold. ## How does Fincanva handle it? - The cash reserve is whatever the [invested portion](/docs/backtesting/invested-portion) does not deploy: an invested portion of 75% leaves a 25% reserve — see [Invested capital and cash reserve](/docs/strategies/invested-capital-and-cash-reserve). - A Risk-Off allocation profile commonly deploys less than its Risk-On twin, so drag typically appears in bursts, lasting as long as the strategy stays defensive — see [Risk conditions](/docs/strategies/risk-conditions). A condition that flips in and out repeatedly turns those bursts into a recurring cost — see [whipsaw](/docs/strategies/whipsaw). - [Leverage](/docs/backtesting/leverage) is the other dial on how much capital is at work: a multiplier below 1.00× leaves part of the capital uninvested, which is the same drag reached from the opposite end. - Idle cash accrues interest only when the **Costs & interests** [simulation assumption](/docs/backtesting/simulation-assumptions) is on, and that assumption is off by default: on the figures you meet first the cash earns nothing and the drag is the whole forgone market return. Switch costs on and the drag becomes that return net of what the cash earned — see [interest received and paid](/docs/analysis/interest-received-and-paid). - The near-riskless short-term return that a cash-like holding is judged against is the [risk-free rate](/docs/analysis/risk-free-rate). ## What does it look like in practice? A strategy switches to a defensive profile set to **Lightly invested** — 25% of capital deployed, 75% held as cash. Over the six months it stays defensive the market rises 12%. The invested quarter captures its share of that rise; the three-quarters in cash captures none of it, so the forgone market return is roughly (1 − 0.25) × 12% = 9 percentage points. Had the market instead fallen 12% over the same six months, the same 75% reserve would have avoided roughly 9 percentage points of the decline. The arithmetic is symmetric — only the market's direction decides which side of it you land on. *Fincanva does not tell you how much cash to hold.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/backtesting/compute-time # Compute time Compute time is the computation time shown for a strategy's [backtest](/docs/getting-started/backtest) — how long the engine took to produce its latest result — displayed in the **Compute** column of your strategies list. Because one result is computed per distinct setup and reused (see [shared compute](/docs/backtesting/shared-compute)), a strategy whose exact configuration has already been calculated returns in a fraction of a second instead of running from scratch. It is a read on how much work a run needed, not a quality or performance metric. **Also seen as:** computation time, run time ## Does a higher plan compute faster? Up to a point, and it is about waiting rather than about what a strategy may do. Compute power is how much of one simulation Fincanva computes at the same time, and your plan sets it. Set by your plan: 4 on Free and Starter, 8 on Advanced and 16 on Ultimate and Professional. See [what each plan includes](/docs/account-security/what-each-plan-includes). A larger share runs more of the same work at once: it buys no extra data, no further [allocation method](/docs/strategies/allocation-and-allocation-method) and no longer history, so nothing about the strategy or the period behind the result changes with your plan. It is not a promise about how long a run takes, either: the strategy, the period covered, and how busy the service is decide that — and a setup that has already been computed comes back from [shared compute](/docs/backtesting/shared-compute) in a fraction of a second whatever your plan. ## How does Fincanva handle it? - The **Compute** column shows the time for the last run, or a dash (`—`) when a strategy has not been run yet. - The value is dimmed when the run's [status](/docs/backtesting/run-status) reads **Needs re-run** — a dimmed compute time means the shown figure is from a superseded run. - A result is reused only while it is still current, so a strategy that was instant yesterday may compute in full today, once new market data has advanced the [data frontier](/docs/backtesting/data-freshness-and-frontier). ## What does it look like in practice? You duplicate a strategy without changing anything and run the copy. Because its configuration is identical to the original — which has already been computed — Fincanva serves that existing result rather than recomputing it, and the **Compute** column shows a near-instant time. Change a single setting on the copy, such as its [rebalance](/docs/backtesting/rebalance) frequency, and it no longer matches any existing result: the next run computes fresh, and its compute time reflects the full work. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/backtesting/costs-toggle # Costs toggle The costs toggle is the [simulation assumption](/docs/backtesting/simulation-assumptions) that decides whether a backtest's results include trading costs and financing, or are shown gross of them. In the app it is the switch labelled **Costs & interests**, described as "Trading costs, financing & interest" and shortened to "Costs" in the assumptions summary. It changes what the *same run* is showing, not the strategy itself. **Also seen as:** Costs & interests, Costs ## What does turning costs on change? Turning **Costs & interests** on deducts every modelled cost of trading and financing from the run you are looking at. Three components get wired in: - **[Transaction cost](/docs/backtesting/transaction-cost)** — a flat fee charged once per trade execution. - **[Slippage](/docs/backtesting/slippage)** — a proportional cost on each fill, for the gap between the quoted and the filled price. - **[Interest-rate markups](/docs/backtesting/interest-rate-markups)** — the financing cost of borrowing for leverage or for shorting, charged as a spread over a reference rate. The same switch turns on the interest credited to idle cash — see [interest received and paid](/docs/analysis/interest-received-and-paid). With the toggle off, all three are zero: the results assume trading and financing were free. ## How does Fincanva handle it? - **Trading costs are not included on the Free plan.** On Free the assumption stays off and the toggle cannot be turned on, so a Free backtest is always a costless one; Starter, Advanced, Ultimate and Professional all include it. See [what each plan includes](/docs/account-security/what-each-plan-includes). - **Costs & interests is off by default**, so the figures you meet first are gross of costs and financing. - Flipping it switches the displayed result immediately, with no new run — every combination is pre-computed when the strategy runs (see [simulation assumptions](/docs/backtesting/simulation-assumptions)). - It moves every number derived from the equity curve, not only the cost lines: total return, annualized return, the monthly figures and the risk metrics all change. - What it deducts shows up as its own bands in the [P&L breakdown](/docs/analysis/p-l-breakdown) — "Costs" and "Interest paid". - The two [interest-rate markups](/docs/backtesting/interest-rate-markups) are saved settings you can edit, separate from the toggle that switches them in or out; the per-trade fee and the slippage fraction are fixed platform assumptions with no setting in the app. - The Holdings view does not follow this toggle: it always reports with costs off, one of its [Holdings forced assumptions](/docs/backtesting/holdings-forced-assumptions). ## What does it look like in practice? One run, viewed twice. With **Costs & interests** off the run shows a total return of +42.0%. Flip it on and the same run shows +38.6%: the 3.4pp difference is the trading fees, slippage and financing the strategy would have paid over the period. Nothing about the strategy changed and no new backtest ran — you switched from the gross view to the after-cost view of the identical run. How wide the gap is depends on how much the strategy trades: one that rebalances monthly pays the per-trade fee far more often than one that holds for years. *The figures on this page describe what Fincanva models, not what you should do with your money — see [Is this financial advice?](/docs/investing-theory/is-this-financial-advice#is-this-financial-advice).* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/backtesting/daily-warm-of-live-strategies # Daily warm of Live strategies The daily warm is the once-a-day sweep that asks the compute engine to recompute every strategy in your [live book](/docs/getting-started/live-book), so those results are already finished by the time you open them. It exists because results are tied to the market data behind them: when the daily data refresh advances, yesterday's results are no longer current and something has to recompute them before anyone looks. The warm is that something, and it is why a strategy you follow Live usually shows finished numbers rather than a progress bar. **Also seen as:** pre-warm, warm-up ## When does the daily warm run? On your first visit of the day, not overnight. Opening Fincanva while signed in triggers one warm of your live book, and it runs once a day — so revisiting later in the day costs nothing and starts nothing. The sweep covers every *runnable* strategy in your live book: strategies whose results are already current are left alone, only the ones the data refresh made stale are recomputed, and any Live strategy parked awaiting a manual run is skipped entirely. That last one is deliberate — a strategy you edited and did not re-run is waiting for **you** to run it, and the warm never recomputes an edited strategy on your behalf. Public strategies are not part of it: they are kept warm by a separate server-side sweep of Fincanva's own, which is why a public strategy you have never touched can also open with finished results. ## Which strategies are warmed? Your daily warm covers the strategies you have marked Live — the ones that make up your live book — minus any of them parked awaiting a manual run. A strategy you have merely backtested and saved is not part of the sweep: it computes when you run it, and its [run status](/docs/backtesting/run-status) goes to **Needs re-run** as soon as a new market day arrives, until you re-run it. Marking a strategy Live is therefore what enrols it in the daily warm; choosing "Stop following" takes it back out. ## How does Fincanva handle it? - The warm runs once a day, on your first visit of that day. - It does not block anything: the app renders while the warm proceeds in the background, and a warm that cannot complete leaves your last-known statuses untouched. - It never places an order or changes a strategy — following a strategy Live is paper monitoring only (see [portfolio](/docs/getting-started/portfolio)). - Warming a strategy whose results are already current changes nothing about it. - Because identical setups reuse one result (see [shared compute](/docs/backtesting/shared-compute)), a strategy you follow may already be current before your own warm reaches it. ## What does it look like in practice? You follow six strategies Live. Overnight, new market data lands and the [data frontier](/docs/backtesting/data-freshness-and-frontier) advances by one trading day, which makes yesterday's six results stale. At 8:05 you open Fincanva: the daily warm fires once and recomputes the ones that need it. By the time you reach the Portfolios page the fastest are already **Up to date** and the rest show **Computing** with a progress percentage. You come back at 14:00 — today's warm has already run, so nothing starts again, and the results you see are the same ones computed this morning, now with one more day of history than yesterday. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/backtesting/data-freshness-and-frontier # Data freshness and frontier The data frontier is the most recent market date Fincanva has price data for, and it is where every [backtest](/docs/getting-started/backtest) ends — not at today's date. Prices arrive as one bar per trading day, so the newest usable data point is the last completed trading day that has been loaded: on an ordinary weekday that is yesterday's close, and on a Monday it is the previous Friday's. Data freshness is the matching question about a result: whether the result you are looking at was computed against the current frontier or an older one. **Also seen as:** data frontier, "data as of" ## Why does my backtest end yesterday and not today? Because today's close does not exist yet. A run ends at the frontier — the last trading day whose data has actually landed — so a backtest you start on Wednesday morning ends at Tuesday's close, and one you start on Monday ends at Friday's. Nothing about the run is truncated by this: the replay covers everything from your [start year](/docs/backtesting/simulation-start-year) up to the frontier, and every figure on the results page ends on that same date, including the month-to-date and year-to-date windows. Intraday prices are not part of the model at all — the smallest step Fincanva works in is one [trading day](/docs/data-methodology/market-day-and-trading-calendar-alignment). ## Why do my numbers change when I did not touch anything? Because the frontier moved. When new market data is loaded, the frontier advances by a trading day and every result computed against the old frontier is no longer current — so the same strategy, unedited, recomputes and comes back with one more day of history and slightly different figures. That is why a strategy can read **Up to date** in the evening and, without you touching it, read **Needs re-run** or **Computing** the next morning before settling back (see [run status](/docs/backtesting/run-status)). This is also distinct from [plan compliance](/docs/backtesting/plan-compliance): "up to date" is about the data, "compliant" is about what your account is allowed to run. ## How does Fincanva handle it? - Every backtest and every screener run uses the frontier as its end date — the wall-clock date is never used. - The frontier is the upper edge of every instrument's [coverage window](/docs/data-methodology/coverage-window); the lower edge is where that instrument's own history begins. - Market data is refreshed daily; while a refresh is in progress the [simulation engine](/docs/getting-started/simulation-engine) reports "Engine updating data" and already-computed results stay visible. - A frontier that has moved invalidates results computed against the previous one, which is what the [daily warm](/docs/backtesting/daily-warm-of-live-strategies) recomputes for the strategies you follow Live. - Because results belong to a setup and a data date (see [shared compute](/docs/backtesting/shared-compute)), no result ever mixes two different frontiers — a run is entirely on one side of a refresh or the other. - Day-to-day drift of this kind is expected behaviour, not a defect: one extra trading day changes every metric that ends at the frontier. ## What does it look like in practice? On Tuesday evening a strategy shows **Up to date**, a total return computed to Monday's close, and a Compute time from that run. Overnight, Tuesday's market data is loaded and the frontier advances from Monday to Tuesday. On Wednesday morning you open the same strategy without editing anything: the saved result was computed to Monday, the current frontier is Tuesday, so the result is no longer current — the status reads **Needs re-run**, and a re-run settles it back to **Up to date** with one more trading day included. The total return has moved slightly, and so has every metric that ends at the frontier. Open it again on Wednesday afternoon and nothing changes: the frontier is still Tuesday, because Wednesday's close has not been published yet. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/backtesting/dividend-tax # Dividend tax Dividend tax is the rate applied to dividend income in a backtest. A dividend a holding pays is credited to the strategy as received — after any [withholding tax](/docs/backtesting/withholding-tax) taken at source — and the dividend tax on it is charged afterwards, together with the strategy's other taxes. It is one of the two taxable events Fincanva models — the other is a realized gain, covered by [capital-gains tax](/docs/backtesting/capital-gains-tax) — and it is a single rate, with no holding-period distinction: a dividend is taxed the same whether the position is a week old or five years old. In the app it is the "Dividend tax" field, described as "Rate applied to dividend income." **Also seen as:** tax on dividends, dividend income tax. ## How much of a dividend reaches the strategy? All of it, at first — less any withholding at source — and then the dividend tax is charged on that amount. Over the run the strategy keeps the dividend minus both: at a dividend-tax rate of 26% on a dividend with no withholding, 74% of it stays in the strategy. The taxed portion leaves the simulation as tax and shows up in the "Taxes" band of the [P&L breakdown](/docs/analysis/p-l-breakdown) alongside tax on realized gains. Three rules decide how the charge works: - **Withholding comes first.** Dividend tax is applied to the dividend as it reached the account, after any withholding at source — never to the gross amount. - **The charge follows the [tax regime](/docs/backtesting/tax-regime).** Dividend tax is charged with the capital-gains tax: once a year, on the dividends of the whole year, under **United States**, **Other** and the Italian **Declarative** regime; as dividends arrive under the Italian **Administered** regime. Until then the full dividend is in the account as cash, but the value the run reports already sets aside the pending dividend tax from the day the dividend arrives. - **Losses do not reduce it.** Dividend tax is charged on dividend income on its own; realized [capital losses](/docs/backtesting/capital-gains-tax#what-happens-to-a-realized-loss) are set only against capital gains. A dividend-heavy strategy meets this charge on every dividend over a run, while a strategy holding non-distributing instruments may never meet it at all. ## How is dividend tax different from withholding tax? They are two different deductions on the same kind of income, and they are set up differently in Fincanva: | | Dividend tax | [Withholding tax](/docs/backtesting/withholding-tax) | |---|---|---| | Who sets the rate | You, in the tax settings (unless it is locked for your residency) | Nobody — Fincanva applies it automatically | | Where it is taken | In the simulation's tax accounting | At source, before the cash reaches the account | | Visible as | The "Taxes" band in results | The "Withholding tax rate" beside each dividend event | ## How does Fincanva handle it? - The rate is a percentage of dividend income, seeded from your [tax residency](/docs/backtesting/tax-residency) — which residency seeds which value, and where the field is read-only rather than yours to set, is on that page. - It applies only when the [Taxes assumption](/docs/backtesting/taxes-toggle) is on; with Taxes off, dividends are credited gross. - It is a saved setting, so editing it flips existing runs to **Needs re-run** until they run again. ## What does it look like in practice? A holding pays a **100 gross dividend** with no withholding at source, and the dividend-tax rate is the Italian default of 26%. The strategy is credited 100; the tax on it, 100 × 26% = 26, is charged later — at the start of the next year under the Declarative regime, on the same day under Administered — so over the run 74 stays in the strategy and 26 leaves as tax. Under a United States residency, where the field is seeded at 20%, the same dividend would cost 20 of tax, charged once the year is over. Now suppose the dividend was paid from a market that withholds tax at source — take an illustrative 15%, a round number and not the rate Fincanva applies to any particular holding. The strategy is credited 85, and the 26% dividend tax is charged on that 85: 22.10. Flip the Taxes assumption off and the full 100 is credited with neither deduction — the same run, viewed gross of tax. *The figures on this page describe what Fincanva models, not what you should do with your money — see [Is this financial advice?](/docs/investing-theory/is-this-financial-advice#is-this-financial-advice).* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/backtesting/holdings-forced-assumptions # Holdings forced assumptions Holdings forced assumptions are the fixed set of [simulation assumptions](/docs/backtesting/simulation-assumptions) the Holdings view always applies — **profits reinvested, Costs & interests off, Taxes off** — no matter which assumptions you have selected on the Analysis views. This is why the same strategy, on the same date, can legitimately show different numbers in Holdings and in Analysis: Holdings always reports a gross, fully-reinvested picture, while Analysis reports whichever combination of Costs & interests, Taxes, and Reinvest profits you have toggled. ## Why can Holdings and Analysis disagree on the same strategy? Because they are reading two different versions of the same run. A backtest is computed as every combination of the three assumptions, and each view picks one: the Analysis views follow your toggles, while Holdings is hard-wired to the gross, reinvesting combination. Once you turn Costs & interests or Taxes on in Analysis, that view's path through history is no longer the path Holdings is showing — costs and tax withdraw money as the simulation runs, which changes the capital available at each rebalance, and therefore the weights, position counts, and cash left over. Both views are correct; they are answering the question under different assumptions. ## Which assumptions does Holdings force? | Assumption | Analysis views | Holdings view | |---|---|---| | **Reinvest profits** | your choice | always on | | **Costs & interests** | your choice | always off | | **Taxes** | your choice | always off | In prose: Holdings gives you exactly one reading — reinvesting, gross of costs and gross of tax — and does not let you change it. That is also why the Holdings view carries no assumptions toggle group at all, while the Analysis views do: the controls would have no effect there. ## How does Fincanva handle it? - The forced set matches the default state of the Analysis assumptions (Reinvest profits on, Costs & interests off, Taxes off), so out of the box the two views agree. They diverge only after you switch Costs & interests or Taxes on in Analysis. - Holdings is re-parameterized by two things instead: the rebalance date you select and the "Capital" input. Neither of those is an assumption — they change which snapshot you see and how it is scaled. - Every Holdings figure inherits the forced set: the "Target notional", "Cash", "Positions" and "Accuracy" KPIs, the "Target allocation" chart, the "Order plan" card, and the "Target positions & exits" sheet. - The forced set applies to the Holdings view only. It does not alter the saved run, your saved assumption rates, or anything the Analysis views show. ## What does it look like in practice? A strategy shows a set of target weights in Holdings for the rebalance date of 1 June, and the same date appears in the Analysis allocation history. With Analysis on its default assumptions the two match. You then switch **Taxes** on in Analysis: its figures change immediately to the after-tax version — because the tax on the gains realized since the start has been taken out of the simulated account along the way — as events occur under the Administered [tax regime](/docs/backtesting/tax-regime), once a year under Declarative — the portfolio reaching 1 June is smaller, so the money behind each weight differs and small positions can round differently. Holdings does not move at all, because it never left the gross, reinvesting version. Nothing is broken and nothing needs re-running: you are looking at the same strategy under two different assumption sets, and only Analysis lets you pick which. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/backtesting/incomplete-combined # Incomplete Combined An Incomplete Combined is a [Combined](/docs/getting-started/combined) that currently holds fewer than two strategies — in practice, one. A Combined's whole job is to split capital between several strategies, so with only one there is nothing to combine: it cannot be backtested, and every results surface shows **example results** rather than numbers of its own. It is a normal, temporary state, not an error, and it clears the moment a second strategy is added. ## Why can't an Incomplete Combined run? An Incomplete Combined has no allocation problem to solve — one strategy receives all the capital, and the Combined layer adds nothing — so Fincanva does not run it at all. Its run control is disabled everywhere it appears, with the reason spelled out: "Add one more strategy to run this Combined." Because it has never run, it has no [run status](/docs/backtesting/run-status) history and no result to fall back on either. The block is its own gate on the Combined, not one of the setup checks that [strategy alerts](/docs/backtesting/strategy-alerts) cover. ## Do the Combined-level settings do anything while it is Incomplete? No — nothing you set at the [Combined level](/docs/getting-started/combined-level) is used while the Combined holds fewer than two strategies. An Incomplete Combined never runs at all, and one strategy would receive all the capital anyway, so there is no split to apply. The Combined-level capital split and the Combined risk layer still render, and you can edit and save them exactly as before; they begin applying as soon as a second strategy is added. The app states this above those settings. The notice is titled "These settings aren't in use yet", and reads "A Combined splits capital across at least 2 strategies. It holds one right now, so what you set here isn't used. Add the missing strategies in the Strategies card." — the count reads "none", "one", or the number the Combined holds. ## What do "Example results" show? The results pages of an Incomplete Combined show a real, fully rendered results layout filled with a **fixed sample Combined's** numbers, faded and non-interactive behind a prompt. The eyebrow reads **Example results**, the headline "This is what a complete Combined shows", and the body "This Combined has one strategy — add a second one from its Settings to run it.", with an **Add a strategy** button. The numbers on screen belong to the sample, not to your strategy — nothing there was computed from your settings, and the page's own controls do nothing while the example is showing. A results section that has no sample to preview falls back to the plain "No results yet" empty state, carrying the same one-strategy explanation. [Holdings](/docs/getting-started/holdings) behaves the same way as the analysis pages. ## How does a Combined become Incomplete? Two ways, and neither changes what the strategy *is*: - **Created and not yet filled.** **Combine**, on a single strategy's workspace, opens the Combined builder seeded with that strategy, and the Combined it produces starts Incomplete until you add the second. The **Combined strategy** tile in the **Create new** dialog arrives here from the other side: it creates a Combined holding one empty member and drops you inside it, so that one starts Incomplete too. It refuses only when you own [no strategies at all](/docs/getting-started/combined#what-do-you-need-before-you-can-create-a-combined). - **Reduced to one.** Removing strategies from a Combined until one is left leaves it an Incomplete Combined; it is not converted back into a single strategy. Being a Combined is a property of the strategy itself, not a count, so it stays a Combined at one strategy. A Combined always keeps at least one strategy inside it, so its last one cannot be removed — the floor is one, which is exactly the Incomplete state. ## How does Fincanva handle it? - The threshold is two: at two or more strategies the Combined runs normally, at fewer than two it does not run at all. - The block applies to every run entry point — the editor's run control and the results page's re-run alike — and it reacts to an add or remove immediately, before you save. - Adding or removing strategies is still fully allowed while Incomplete; only running is blocked. - The library list marks an Incomplete Combined with an **Incomplete** badge and shows the same reason on its run action. ## What does it look like in practice? You create a Combined and seed it with your momentum strategy. The library list shows it with an **Incomplete** badge, and its run control is disabled: "Add one more strategy to run this Combined." You open its analysis anyway and see a complete-looking results page — an equity curve, a metrics table, a monthly grid — under the eyebrow **Example results** and the headline "This is what a complete Combined shows". None of those numbers are yours; they are the sample's, shown so you can see what you will get. You add a second strategy, a defensive one. The badge disappears, the run control unlocks, and the first real backtest replaces the example with numbers computed from your two strategies and the [Combined-level](/docs/getting-started/combined-level) split between them. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/backtesting/interest-rate-markups # Interest-rate markups Interest-rate markups are the spreads Fincanva adds on top of a reference rate to model what financing would cost inside a backtest. Borrowing money to use leverage, or borrowing shares to sell short, is not free in real markets — a broker charges a rate above the market reference rate — and the markups let the simulation reflect that cost. There are two: a **borrowing rate markup** for leverage and a **short rate markup** for shorting. **Also seen as:** financing spread, short borrow fee ## How is the financing rate calculated? The financing rate the simulation charges is the reference rate plus the relevant markup. $$ \text{Financing rate} = \text{Reference rate} + \text{Markup} $$ where the reference rate is the market rate the model starts from — the [margin-loan rate series](/docs/data-methodology/special-data-series) — and the markup is the spread added on top. The borrowing markup applies to capital borrowed for leverage; the short markup applies to the cost of borrowing securities to short. ## How does Fincanva handle it? - Two markups are modelled: a "Borrowing rate markup" (default 1.5%), described in the app as the "Spread added above the broker rate when borrowing capital", and a "Short rate markup" (default 2%), the "Spread added above the broker rate when shorting securities". - Both are spreads over a reference rate, not the full rate themselves: with costs on, borrowing and shorting always pay the reference rate plus the markup. - The "Borrowing rate markup" also reduces what idle cash earns: it is subtracted from the reference rate before idle cash is credited — see [interest received and paid](/docs/analysis/interest-received-and-paid). - They are applied only when costs are switched on; with costs off, modelled financing costs are zero. - The resulting financing cost appears in the interest line of your capital and profit-and-loss breakdown. ## What does it look like in practice? A strategy runs a month with **leverage**, holding more exposure than its cash by borrowing capital. For that month the simulation charges interest on the borrowed portion at the reference rate **plus the 1.5% borrowing markup**, so the financing cost is higher than the reference rate alone. That charge shows up in the interest line of the [profit-and-loss breakdown](/docs/analysis/p-l-breakdown) as a drag on the month's result — the price, in the model, of carrying leverage. A short position would be charged the reference rate plus the 2% short markup in the same way. *The markups are modelling assumptions applied to historical results, not the rate a broker will charge you, and nothing here is a suggestion to use leverage or to short.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/backtesting/invested-portion # Invested portion The invested portion is the share of a Combined's capital that an allocation profile puts to work, from 0% up to 300%. Below 100%, whatever is left over is held as a cash reserve and deployed into nothing; above 100%, the Combined borrows the difference and invests more than its capital, which is leverage at the Combined level. It is one number for the whole profile of a Combined — a strategy assembled from other strategies — applied before those strategies are weighted against each other, so it controls *how much* of your capital is at work rather than *what* it is at work in. In the app it is the "Invested portion" control, whose helper reads "Share of capital this profile deploys. Above 100% it invests with leverage." and whose unit is "%". **Also seen as:** invested capital, share of capital deployed, portfolio leverage ## How is the deployed amount calculated? Multiply the profile's capital by the invested portion; the remainder is the reserve, and a negative remainder is borrowed money. $$ D = p \times C \qquad R = (1 - p) \times C $$ where $p$ is the invested portion as a fraction between 0 and 3 (0% to 300%), $C$ is the capital the profile has, $D$ is the amount deployed into strategies, and $R$ is the cash reserve. The deployed amount $D$ is what the allocation method then splits across the strategies the Combined holds; $R$ never reaches them. When $p$ is above 1, $R$ is negative: $(p - 1) \times C$ is borrowed, and the Combined's cash balance is negative by that amount. ## What are the invested-portion presets? Four presets cover the common cases, with a slider for anything else: | Preset | Invested portion | Cash reserve | |---|---|---| | **Fully invested** | 100% | none | | **Mostly invested** | 75% | 25% | | **Half invested** | 50% | 50% | | **Lightly invested** | 25% | 75% | | **Custom** | any value you set with the slider, up to your plan's ceiling | the remainder, or a debt above 100% | The presets stop at 100% on purpose: investing above it is always a **Custom** value, set on the slider. ## What happens to the cash reserve? The reserve stays as cash: it is not allocated to any strategy and takes no market exposure, so it neither rises nor falls with the instruments the Combined holds. It accrues interest in the simulation only when the **Costs & interests** [simulation assumption](/docs/backtesting/simulation-assumptions) is on; that assumption is off by default, so on the figures you meet first the reserve earns nothing at all — see [interest received and paid](/docs/analysis/interest-received-and-paid). Its effect on results is symmetric: a reserve dampens gains and losses in the same proportion, because only the deployed share of capital is exposed to the market. Holding half in cash halves the impact of a market move, in both directions. The return the reserve gives up over a rising window is [cash drag](/docs/backtesting/cash-drag), which is the same arithmetic read from the other side. ## What happens when the invested portion is above 100%? Above 100% the Combined invests more than its capital and borrows the difference: at 150% it deploys one and a half times its capital, and its cash balance goes negative by half its capital — a margin debt. The borrowed part works exactly like [leverage](/docs/backtesting/leverage) on a single strategy: gains and losses on the deployed amount are magnified in the same proportion, in both directions. The debt is financed the same way, at the same rate, and only when the **Costs & interests** assumption is on — [what leverage costs](/docs/backtesting/leverage#what-does-leverage-cost) is the canonical statement. ## How does Fincanva handle it? - A new allocation profile starts **fully invested at 100%**. The range runs from 0% up to 300%, bounded by your plan's leverage ceiling. - **Investing above 100% is included on any plan that includes a Combined at all — from the Advanced plan on** — up to 300%, bounded by the plan's leverage ceiling, which is stated once on [leverage](/docs/backtesting/leverage#how-does-fincanva-handle-it). The invested portion exists only on a Combined, so there is no lower plan step where it applies. Where the plan narrows the range, the control shows the cap with a tag naming the [plan level](/docs/account-security/plan-level) that raises it. See [what each plan includes](/docs/account-security/what-each-plan-includes). - A [volatility target](/docs/backtesting/volatility-target) can sit inside the same block and rescale the invested portion at every rebalance; the exposure it produces never exceeds 300% either. - The value belongs to the profile, not the Combined, so a Risk-Off profile can hold a different invested portion from the Risk-On one — see [Risk conditions](/docs/strategies/risk-conditions). - At 0% nothing is deployed and the run simply tracks an uninvested balance. - The invested portion is a Combined-level control. A single strategy's exposure is set on its own allocation profile with [leverage](/docs/backtesting/leverage) instead. - A profile that differs from the default is summarised under the allocation method as, for example, "Invested 150%". - Deploying $D$ does not mean spending exactly $D$: whole-share rounding leaves a little of it unspent, which is [target vs deployed](/docs/portfolio-holdings/target-vs-deployed). ## What does it look like in practice? A Combined holds 10,000 and its allocation profile is set to **Mostly invested (75%)**. Deployed is 0.75 × 10,000 = **7,500**, and the cash reserve is 0.25 × 10,000 = **2,500**. The allocation method then splits the 7,500 across the strategies in the Combined; the 2,500 sits in cash and is allocated to nothing. Now suppose the deployed holdings fall 10% over a month. The loss is 10% of 7,500 = 750, which is 7.5% of the Combined's 10,000 — not 10%, because a quarter of the capital was never exposed. The same arithmetic runs upward: a 10% rise would be 750, or 7.5% of total capital. The reserve did not protect the deployed part; it simply kept a quarter of the capital out of the move. Set the same Combined to a **Custom 150%** instead. Deployed is 1.5 × 10,000 = **15,000**, and the reserve is (1 − 1.5) × 10,000 = **−5,000**: 5,000 borrowed. The same 10% fall now costs 1,500, or 15% of the Combined's capital, before the interest on the 5,000 — and a 10% rise gains 15%. *Fincanva does not tell you how much of your capital to put to work or how much to hold in cash — see [Is this financial advice?](/docs/investing-theory/is-this-financial-advice#is-this-financial-advice).* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/backtesting/leverage # Leverage Leverage is the multiplier applied to a strategy's position sizes in an allocation profile: at 1.00× the positions add up to the strategy's capital, above 1.00× they add up to more than its capital, and below 1.00× to less. Holding more exposure than you have capital for means borrowing the difference, so leverage above 1.00× carries a financing cost that a strategy at 1.00× does not have. In the app the control is "Leverage", with the hint "Multiplier on position sizes. 1.00 = no leverage. Range 0.00 – 3.00." **Also seen as:** gearing, multiplier, margin. ## How much exposure does a leverage multiplier create? Multiply the strategy's capital by the multiplier; anything above the capital is borrowed. $$ E = L \times C \qquad B = \max(L - 1,\; 0) \times C $$ where $L$ is the leverage multiplier, $C$ is the strategy's capital, $E$ is the resulting market exposure, and $B$ is the borrowed amount that has to be financed. Below 1.00× nothing is borrowed and the unused share of capital — $(1 - L) \times C$ — simply stays in cash: a 0.70× profile is 70% invested and 30% cash, with the same [cash drag](/docs/backtesting/cash-drag) that any idle balance carries. ## What are the leverage presets? Four presets cover the range, with a slider for anything in between: | Preset | Leverage | Exposure per unit of capital | |---|---|---| | **Cash only** | 0.00× | none — no positions are held | | **No leverage** | 1.00× | exposure equals capital | | **Moderate** | 1.50× | 1.5 units of exposure, 0.5 borrowed | | **Max** | 3.00× | 3 units of exposure, 2 borrowed | | **Custom** | any value from 0.00× to 3.00× | as set | ## What does leverage cost? Above 1.00×, the borrowed part is financed for as long as it is held. The rate charged is the [margin-loan reference rate](/docs/data-methodology/special-data-series), a short-term interest rate, plus the **borrowing rate markup**, the spread described in the app as "Spread added above the broker rate when borrowing capital." — see [interest-rate markups](/docs/backtesting/interest-rate-markups) for both markups and their defaults. That cost is charged only when the [Costs & interests assumption](/docs/backtesting/costs-toggle) is on. With costs off, a leveraged run shows the magnified gains and losses but none of the financing that produced them, which flatters leverage specifically. It lands on the "Interest paid" line of the results — see [interest received and paid](/docs/analysis/interest-received-and-paid). ## What does leverage do to gains and losses? It multiplies both, by the same factor and in the same direction. A market move of $r$ on the exposure is worth $L \times C \times r$ to the strategy, so at 1.50× a 10% move is worth 15% of capital whether the market went up or down. There is no asymmetry: the multiplier that magnifies a good year magnifies a bad one identically, and a leveraged strategy can fall further and faster than the same strategy at 1.00×. The financing cost sits on top of that and does not care about direction. It is subtracted after a gain and added to a loss, so a leveraged run needs the magnified gain to clear the financing before it is ahead of the unleveraged version. ## How does Fincanva handle it? - The default is **1.00× (No leverage)**, and the field's own range is 0.00× to 3.00× — 3.00× is the most exposure a strategy's profile can hold, on any plan. - **Leverage above 1.00× is included from the Starter plan.** Every plan has a leverage ceiling: 1.00× on Free, and 3.00× on Starter, Advanced, Ultimate and Professional. On Free the Leverage field is capped at 1.00×, so its range there is 0.00×–1.00×, with a tag naming the [plan level](/docs/account-security/plan-level) that raises it. This is an app-side cap: the simulation engine carries no concept of a plan and applies none of this on its own. See [what each plan includes](/docs/account-security/what-each-plan-includes). - **The Leverage field's range always matches your plan's ceiling** — the one stated above. - **Every preset is listed on every plan.** On Free, Moderate and Max sit above the ceiling: they carry the tag of the plan level that includes them, and choosing one changes nothing and opens a window that says how far your plan goes and what the next plan up allows. - **Moderate stays fixed at 1.50× on every plan.** Anything else in between is reachable with **Custom** or the slider. - A Combined can still go further than a single strategy's own leverage, through its [invested portion](/docs/backtesting/invested-portion) above 100% and a [volatility target](/docs/backtesting/volatility-target), up to the shared 300% ceiling. - Leverage belongs to an allocation profile, so a Risk-Off profile can carry a different multiplier from the Risk-On one — including **Cash only** — see [Risk conditions](/docs/strategies/risk-conditions). - The profile summary line prints the multiplier next to the allocation method, as in "· 1.50×". - At **Cash only (0.00×)** no positions are opened at all; the run tracks an uninvested balance. - Leverage is the strategy-level exposure control, and it is **fixed**: the same multiplier through calm and turbulent markets. How much of a Combined's capital reaches its strategies in the first place is the [invested portion](/docs/backtesting/invested-portion), a separate control at the Combined level that can itself go above 100%. A Combined can also let its exposure move with the market's volatility — that is a [volatility target](/docs/backtesting/volatility-target), sometimes called dynamic leverage. ## What does it look like in practice? A strategy with **10,000** of capital runs a year at **1.50× (Moderate)**. Its exposure is 1.5 × 10,000 = **15,000**, of which **5,000** is borrowed. Suppose the reference rate is 4% and the borrowing markup is the default 1.5%, so the borrowed money costs 5.5% for the year: 5,000 × 5.5% = **275**. | Market move on the exposure | Gain or loss | Financing | Result on 10,000 of capital | |---|---|---|---| | **+10%** | +1,500 | −275 | **+1,225** (+12.25%) | | **−10%** | −1,500 | −275 | **−1,775** (−17.75%) | The same strategy at 1.00× would have made +1,000 or lost 1,000, with no financing at all. Leverage turned a 10-point market move into a 12.25-point gain or a 17.75-point loss — and the 275 was paid in both cases, which is why the downside is magnified by slightly more than the upside. *Leverage magnifies losses exactly as it magnifies gains. Fincanva does not recommend a leverage level or tell you whether to use leverage at all — see [Is this financial advice?](/docs/investing-theory/is-this-financial-advice#is-this-financial-advice).* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/backtesting/plan-compliance # Plan compliance Plan compliance is the check that asks whether a strategy's setup is allowed by the plan attached to your account, run before Fincanva serves that strategy's [backtest](/docs/getting-started/backtest) result. It is a pass/fail answer about the setup, never a judgement about the numbers. A strategy your plan does not cover produces no results at all — no metrics, no equity curve, no positions and no what-to-buy list — and Fincanva says so rather than staying silent: opening it shows its results veiled behind a panel, pressing **Backtest** is refused with a message that names your plan, and the strategy carries the [run status](/docs/backtesting/run-status) **Set aside** in your library. **Nothing is deleted.** ## What happens when a setup is not compliant? The strategy opens as usual and its results are veiled rather than taken away: the page keeps its shape, every number is hidden, and one panel sits over it. You are not redirected and nothing is reported as an error, because neither is true: the strategy is exactly where you left it. The panel names your plan, says which of the two reasons applies, and offers the way out that fits that reason. - **The account holds more strategies than the plan keeps active.** The panel reads **Set aside, not deleted**, then names the plan, the number it keeps active — 2, on Free — and the number you hold, closing with "It becomes active again when the plan covers it." There is no free action under it, because none exists: what remains is the named level, **Switch to Starter**, and no button at all where no plan would cover the account as it stands. The one exception is a genuinely vacant seat — see below. - **The strategy on its own asks for more than the plan grants.** The panel reads **It asks for more than the plan allows** and lists every limit it exceeds, one line each, with the strategy's value beside the plan's — `“Model 1” holds 40 positions, Free allows 5`, or `Screener “Momentum” in “Model 1” has 15 filters, Free allows 10`, where `Model 1` is the model the setting sits on and `Momentum` is the attached screener's own name — then `Correct these values in Settings and it becomes active straight away, without changing plan.` Its action is **Correct the settings**, and it is the loud button: correcting them costs nothing, and nobody should have to pay to leave a limit their own strategy crossed. Where a higher plan would cover the strategy, **Switch to Advanced** sits beside it as the quieter second choice. Where no higher plan covers it, that button is absent rather than pointing at nothing. The refusal is not only in the interface. The same verdict is applied when the results, the positions, or the what-to-buy list are requested directly, so nothing computes a number for a strategy the plan does not cover. Pressing **Backtest** answers with a sentence that names the plan you are on, every limit the strategy crosses with its value beside the plan's, and the plan that would lift the refusal — for a strategy on Free whose model holds 40 positions, `This strategy is outside your Free plan, so it cannot run: “Model 1” holds 40 positions, Free allows 5. Switch to Ultimate to run it.` When it crosses more than two limits, the first two are named and the rest are counted, `and 2 more`. Where no plan covers the strategy as it stands, the same message ends `No plan currently covers it — reduce what it holds and try again.` instead. **Its settings stay open and editable.** That is deliberate: editing is how a strategy that exceeds the plan on its own is corrected, and a save that brings it back inside the plan reopens it — the panel says so, `Correct these values in Settings and it becomes active straight away, without changing plan.` Two accounts on different plans therefore get different answers to the same strategy: each simulation is judged against the plan of the account that asked for it. **Nothing is deleted and nothing is edited.** A strategy outside your plan stays in your library exactly as you left it, and it becomes runnable again the moment the plan covers it. ## Which two things put a strategy outside a plan? Two, and they clear differently. - **Your account holds more strategies than the plan allows**, and this one is not among the ones kept active. Fincanva chooses which stay active rather than leaving it to chance: the strategies you [follow Live](/docs/getting-started/mark-live) first, then the most recently used. The rest read **Set aside**. This clears by moving to a plan that covers what you hold; the active set itself is decided once and does not shift on its own afterwards. - **The strategy on its own asks for more than the plan grants** — more positions, more strategies inside a [Combined](/docs/getting-started/combined), more attached screeners, or more filters inside one attached screener than your plan allows, or a start year earlier than your plan's floor. This clears either by moving to a plan that covers it, or by editing the strategy back inside the limit. Which strategies your plan keeps active has no bearing on it: the problem is the strategy's own settings, so only the settings or the plan can resolve it. A strategy kept aside inside a Combined — switched off with its pause button on the Combined's **Strategies** card, or carried over already switched off from the previous Fincanva platform — does not count toward how many strategies a Combined may hold: only the ones in use do, as on the previous platform, and a Combined always counts as at least two. Keeping one aside is therefore a way to edit a Combined back inside that limit, and switching one back on is refused while the limit is reached — unless the Combined was last saved with at least that many in use — see [strategy in a Combined](/docs/getting-started/strategy-in-a-combined#can-you-switch-a-strategy-in-a-combined-off-without-removing-it). Its own settings (positions, attached screeners, risk conditions, allocation method) are still held to the plan, in a Combined or in a single strategy, because they are still part of what the strategy contains. Switched off, it is left out of what a run uses. Whatever is switched on or off, a strategy holds at most as many components as the highest plan allows. **Filters inside an attached screener are the one limit no plan raises.** Every plan allows the same number of filters in a screener, so there is no higher level to move to and the panel offers none: the only way out is to remove filters from the attachment, or to detach it. The panel names the attachment on its line when it has a name, because one strategy can hold several and each carries its own filters: without the name, two attachments over the same allowance print the same line twice and neither says which one to trim. A screener you built inline in **Asset selection** has no name until you save it to your library or attach one from there, so its line stops at the model — `filters per screener · Model 1` — where an attached one adds the screener's name after it. A strategy can cross it without you editing anything and without your plan changing — [attaching a screener](/docs/getting-started/screener-attach) copies it into the strategy, and if the allowance itself moves afterwards the copy is over it where it stands. The other limits can be crossed without an edit too, but by moving to a plan that grants less. **A screener in your library that is already at the allowance will not take another filter**: **Add filter** opens and refuses, with the number you are at beside it. Narrowing the universe — country, sector, exchange — stays available in that same menu, because it is filters that are counted and not the universe; where there is no universe to narrow, as in a hand-picked basket, the button itself is off. You meet the limit where you are standing rather than at the save, nothing is trimmed in silence, and no plan is offered to switch to — because for this limit there is none. Inside a strategy, which of the two you meet depends on where the screener came from. One you built inline in **Asset selection** has no screener behind it, so it refuses at the button, as a library one does. The number it stops you at need not be the same, though: headroom a strategy carries over the allowance — because the allowance changed under it — belongs to the strategy rather than to one screener inside it, so another screener you built inline that is already using it leaves none here. One attached from your library keeps the rule for any filter that is new — what the strategy's copy may still take on is a filter the screener it came from already has, because that one exists whether you add it here or detach and attach the screener again — and there the refusal comes at the save rather than at the button, because whether a filter you are adding is one that screener still holds is something only Fincanva can see, and it is checked when you save. One that is already over the allowance — because the allowance changed under it — is left as it is rather than pruned, and stays editable in the direction that helps. **The ceiling is what already exists, and it only comes down.** A strategy carrying an attached screener with 12 filters may keep it at 12 and save it unchanged; bring the strategy's copy down to 11 and the twelfth is still available to it for as long as the screener in your library still holds it — add it back in place and the save is taken, because that filter still exists behind the strategy. You do not have to detach and attach again to get it; re-attaching is simply the other way of asking for the same rows. What is gone is a filter the library screener no longer holds either: then 11 is the ceiling, and it only comes down from there. Nothing can be saved above what is already there, in the strategy or in the library behind it. **Already there** counts the screener in your library as well as the strategy: a screener left at 12 by a change in the allowance can still be attached — to the strategies you already have and to new ones — because attaching moves filters that already exist rather than writing new ones. What you cannot do is change them on the way in: the filters that arrive have to be the ones that screener holds, so a thirteenth is refused, and so is naming a 12-filter screener while sending twelve different filters. Both cases give the strategy the status **Set aside**, and in your library its row stays a row: it carries, before the name, a small square with the bars of the plan level that would bring it back, the name is muted, and the computed metrics show dashes instead of numbers, because there are no numbers to show. Set-aside rows sink to the bottom of the list whatever sort you chose. Which of the two reasons applies is in that mark's tooltip, not in a sentence across the row. For the count case it names the ceiling and the plan — on Free, a ceiling of 2 saved strategies. For a strategy that exceeds the plan on its own it names each limit with the arithmetic — `Outside the Free plan: “Model 1” holds 40 positions, Free allows 5.` — because the correction is a number you have to hit yourself. Under both, the same closing line: `Nothing has been deleted — it becomes active again when the plan covers it.` A set-aside row keeps its **Live** switch, shown off and dimmed, and pressing it toggles nothing: it opens **The plan is full**, which says how many the plan goes up to — 2, on Free — that they are all taken, and that nothing is deleted because the next level raises the number. It closes with **Got it**, or takes you to the higher plan with **Switch to Starter**. An account cannot follow more strategies than its plan keeps active, and a switch that simply refused the click would leave you with no way to learn why. ## How does Fincanva decide which strategies stay active? Fincanva decides it, once, at the moment your plan stops covering your library: the strategies you [follow Live](/docs/getting-started/mark-live) first, then the most recently used. Those stay active; the rest read **Set aside**. The notice at the head of the list states the rule rather than leaving you to guess: **We kept the ones you follow, then the ones you used most recently. Nothing has been deleted.** **The decision is written down, and it does not move again.** Once the set is settled, ordinary use no longer changes it — editing an old strategy does not pull it back in, and does not push another one out. It is decided afresh only when your plan covers your whole library again: at that point the whole verdict is discarded, nothing is set aside, and a later change of plan is judged on the library as it is then rather than on a set decided months earlier. **Nothing is deleted by any of it.** A set-aside strategy keeps everything it had, its settings stay editable, and it comes back exactly as it was as soon as the plan covers it. Because the strategies you follow Live rank first, one of them is set aside only when you follow more strategies than your plan keeps active; a set-aside strategy stops being followed, and then declares that gap for good — see [Mark Live](/docs/getting-started/mark-live). There is one moment where you choose instead. If you delete a strategy that was active, your plan has room for one more — and that is the only way a seat ever falls vacant, since nothing else here deletes. From then on, every set-aside strategy that could actually reopen carries **Activate this one** on its own set-aside panel. One that exceeds the plan on its own does not: taking the seat would not change its settings. Nothing appears on its own, and no control sits somewhere waiting to be found: with no vacant seat, that button does not exist. You reach it when you decide to, on the row you mean. If you never press it, the same rule fills the seat the next time you open Fincanva. And the price does not move: a seat exists only because something was deleted for good, so changing which strategy is active still costs a strategy. ## Where do you see how much of your plan you are using? In the plan tile, in the sidebar above your account, which keeps the count of what you are following in view at rest. It is one raised button on a single row: while you hold a plan, paid or on trial, a black face with the plan written in lime; on Free, a lime face — on the left the plan's bars and its name; on the right, how many strategies you follow Live against how many your plan allows, written `Live 3/5`, or just `Live 7` on a plan with no Live ceiling — Ultimate and Professional, today. Saved strategies and saved screeners no longer get a row here: both are effectively unlimited by plan — screeners on every plan, strategies from Starter up — so Live, which still has a ceiling below Ultimate and Professional, is the one count worth stating at rest. During the free trial the tile names the plan as `{plan} · trial`, in the lime every plan the account holds is written in — trial or paid — and the right side shows the days left in place of the Live count: `{n} days left`, and `1 day left` on the last one. On a plan with no Live at all — Free, today — the right side instead reads `Free trial` while the account is still eligible for the trial, which is now only a moment, since the trial starts by itself the first time the account opens the app; otherwise it invites the step up to the first plan with Live, written `Switch to Starter` with an arrow. Collapsed to icons, the sidebar keeps the tile's bars alone; its tooltip carries the plan's name and the same Live count — or, during the trial, the days left. Between a downgrade and the one-time choice of which Live strategies to keep, an account can briefly follow more than its plan allows, and the tile states that too — `Live 5/1`. The sidebar's **Portfolios** entry carries the same Live count on its own, as a small green badge written `2 Live`; it is hidden when you follow none and when the sidebar is collapsed to icons. Pressing the tile opens a panel headed by the plan's own ribbon — the plan's name, with **Manage plan** at the top, which opens billing settings. Below it, **Your Live strategies** repeats the count (`3 / 5`) and lists every strategy you follow Live: each name links to the strategy, and each carries the Live switch, asking for the same confirmation as switching Live off from the strategy's own page before it stops following. From nine Live strategies onward, a search box, **Search Live strategies**, appears above the list. Once every Live slot is taken, it adds `Every Live slot is taken. Switch one off to follow another.` With nothing followed yet, it reads `No strategy is Live yet. Turn Live on from a strategy's page.` Wherever a higher plan allows more Live, the panel's foot always carries the invitation — `More Live with Ultimate`, from Advanced, beside **Switch to Ultimate** — full or not; on a plan with no Live ceiling there is nothing to offer and it is absent. On a plan that does not include Live — Free, today — the panel carries no Live list at all: it reads **Follow a strategy Live**, `With Starter you can follow a strategy Live.`, and — only while the account is still eligible for the trial — `Start your free trial` with `30 days, no card` beneath it, closing with **Switch to Starter**. How much you hold against your plan's ceilings, and what your plan gives you, still have their own place: [Settings → Usage](/docs/account-security/what-settings-usage-tells-you). A strategy set aside because your plan does not cover it is still marked on its own row in the strategies list, exactly as described above — the tile states Live alone, not the set-aside count. ## What Fincanva enforces today The refusal holds when a strategy the plan does not cover is opened, when its results are requested, and when a run is asked for — and, as of a later fix, at creation and at save too. **You may never *create* beyond the plan.** Making a new strategy, duplicating one, copying one from the public library, cloning it, or combining strategies into a [Combined](/docs/getting-started/combined) all ask the plan first and are refused outright when what they would produce is not covered — copying counts as creating, so a Free account can no longer pull an Ultimate-level public strategy into a full library. Combining strategies at all is gated the same way: **Combined is not available below Advanced**, and a press there is refused before anything is created. That gate does not exempt an Advanced-or-above account from the count refusal above — the Combined tile itself stays visible and clickable regardless of plan, and a Combined that would push you past what your plan grants is refused the same way any other creation is, with its own sentence, `Couldn't create the combined strategy`. A creation refused on the count answers with its own sentence, not the run one, and that sentence names the copy — at every door that copies, with no exceptions left. **Duplicate** in a dashboard row's menu, **Duplicate** in the header of an open strategy, **Duplicate** in the strategies explorer's own row menu, **Copy to Mine** in the first two of those, and the copy button on a **Public** strategy in the explorer all read — on a Free account whose library already holds as many strategies as the plan allows — `This would take you past what your Free plan allows, so the copy wasn't created: 3 strategies, Free allows 2. Switch to Starter for more.` It says the copy *wasn't created* rather than *it cannot run* because nothing was created: whatever you were duplicating from is untouched. The explorer's row menu used to word this one as a refused save; it no longer does, and no copy door anywhere does. **A duplicate refused for what the strategy *is*, rather than for how many you hold, is a different message — and which one you read depends on where you pressed.** Cloning a [Combined](/docs/getting-started/combined) on a plan that does not offer Combined is refused before anything is created, in every case. From a dashboard row's menu or an open strategy's header it answers short: `Couldn't duplicate the strategy` — no plan, no level, no number. From the explorer it answers `This strategy is outside your Free plan, so it cannot run. Switch to Advanced to run it.`, which names the plan and the level but describes a run that was never going to happen — you asked for a copy. Nothing is created either way, and the strategy you copied from is untouched. **Copy to Mine** has no such case where it is offered as *Copy to Mine*: in a dashboard row's menu and in an open strategy's header, your plan is read at that door for how many strategies you already hold and for whether the copy's [benchmark](/docs/getting-started/benchmark) is one your plan allows — both of which name the plan when they refuse — so a copy your plan stopped always tells you so. `Couldn't copy the strategy` is what you get when something other than your plan stopped it: the strategy is no longer public, or no longer there. **The copy button on a Public strategy in the explorer is the exception, and it is one because of how it copies.** In the tree it is a copy **icon** carrying no words, announced to a screen reader as `Copy "…" to Mine`; the window it opens is titled and confirmed **Duplicate**, and it duplicates rather than copies — so the Combined check above applies to it and a Free account copying a public Combined reads the run sentence there too. On the count, it reads the copy sentence like every other door. One door answers with a wall instead of that sentence: **New strategy** above the strategies library, on **Mine**, opens a dialog of its own rather than the creation dialog. It names the level that lifts the limit, states where you stand — `You are at 2. Nothing is deleted — the next level raises the number.` — adds `Fincanva applies this limit itself, so the level above is the only way past it.` and offers **Switch to Starter**. It is not the plan panel described above, which belongs to the sidebar tile. The same button on **Public** is not walled: that board lists strategies you do not own, so your plan is not read there and the click opens the creation dialog like any other door. **Every other way in refuses without naming the plan.** **New strategy** on the portfolios page, the **+** in the sidebar, the **+** on the tab bar, the create button on an empty strategies board — which you can still meet on a full plan, because that board is filtered to one kind while the plan counts your whole library — and the create buttons on the dashboard and in the explorer all open the creation dialog as usual. You submit, the creation is refused on the count, and the message you get is `Couldn't create your strategy. Try again.` — it says nothing about your plan and nothing about the level out. Combining is the one leg of that dialog with a sentence of its own — `Couldn't create the combined strategy` — and it names the plan no more than the other does. Ahead of the wall there is a warning rather than a second wall, and only ahead of it: from four-fifths of the ceiling onwards, the creation dialog carries a grey line under its title — `It will be the 801st of 999 on the Starter plan` — and it is absent both while you are still well inside the limit and once you have reached it. **The plan it names is never Free.** The only saved-strategy ceiling a plan sets is Free's 2, and no whole number below it reaches four-fifths of it — at 0 the count is empty, and the next and only other number short of the ceiling is already below the warning threshold — so on Free the wall arrives with no warning before it. The 999 the line counts against is the anti-abuse maximum, which no plan level raises, and not a plan number. **You may still *find yourself* beyond it**, and saving stays the route back rather than a second wall. A save is refused only when it would make some breach worse than the one the strategy already had — more positions, more member strategies, or more attached screeners than before, or a start year earlier than the one it already had. A strategy a downgrade left over the plan keeps its settings editable and can be saved as many times as you like as long as no save increases what it exceeds by; the one save that is never refused is the one that brings a number down. Only once a save reduces every breach to nothing does the strategy stop reading **Set aside**. **One refusal at the run door names no plan at all.** A few of the plan's limits are only read when a run is asked for, so a strategy can open normally — results in place, no panel, no **Set aside** on its row — and still be refused at the press: **Backtest** answers `Couldn't start the run`, without naming your plan and without offering a level, and nothing else on the page changes. On the walk the same refusal arrives as a panel instead of that message: **Saved — the backtest did not start**, which confirms your changes are saved and says the strategy is outside what your plan allows — again without naming the setting or a level. It clears the same two ways as any other plan refusal — move to a plan that covers the strategy, or bring the setting that asks too much back inside the plan — but Fincanva does not name that setting here, so [what each plan includes](/docs/account-security/what-each-plan-includes) is where you check what your level grants. **Set aside** is one of the three statuses Fincanva reads from your own account rather than from the compute engine — the other two being **Incomplete** and **To run** — so it is true right now and does not change when the engine is unreachable. It is also the first question asked about a strategy: a strategy outside the plan reads **Set aside** even when it is unfinished, because finishing it would not make it runnable. The same capability question seen from the data side is [data-tier gating](/docs/data-methodology/data-tier-gating). This page describes the check itself: what each plan includes, and what it costs, is on [what each plan includes](/docs/account-security/what-each-plan-includes). ## What does it look like in practice? Two accounts open the same strategy, one holding 40 instruments. The account on a plan that grants it sees the results and presses **Backtest**: the run starts and the status settles on **Up to date**. The account on Free opens the same strategy and finds its results veiled — the page keeps its shape, the numbers gone — with one panel over it reading **It asks for more than the plan allows**, the limit under it (`“Model 1” holds 40 positions, Free allows 5`) and **Correct the settings** beside **Switch to Ultimate** — the first plan whose ceiling reaches 40. Pressing **Backtest** produces no run either: `This strategy is outside your Free plan, so it cannot run: “Model 1” holds 40 positions, Free allows 5. Switch to Ultimate to run it.` The strategy is not touched, nothing is removed from it, its settings are still editable, and the same press succeeds unchanged once the account is on a plan that covers it. Recognising that shape matters, because it is the one case where an empty results view is neither a run that never happened nor data that has moved on — the two ordinary reasons covered by [run status](/docs/backtesting/run-status) and [data freshness](/docs/backtesting/data-freshness-and-frontier). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/backtesting/precomputed-toggle-variants # Precomputed toggle variants Precomputed toggle variants are the finished result sets Fincanva computes for every combination of the three [simulation assumptions](/docs/backtesting/simulation-assumptions) — Costs & interests, Taxes, and Reinvest profits — inside one single run, so that flipping a toggle selects an already-computed result instead of starting a new [backtest](/docs/getting-started/backtest). Three independent on/off switches make eight combinations, and one run fills them. That is the whole reason the after-tax curve appears the moment you ask for it. **Also seen as:** toggle combinations, assumption variants ## Why does flipping an assumption toggle update instantly? Because the result you switch to already exists. The three toggles are not inputs the run is waiting on — they choose which finished variant is displayed, so switching one is a read, not a recomputation. A run therefore produces the gross view and the after-cost, after-tax and non-compounding views together, and the results page moves between them with no queue, no progress bar, and no change to the run's [status](/docs/backtesting/run-status). ## Why are there eight variants? Three toggles with two states each give eight distinct combinations. Costs & interests, Taxes and Reinvest profits are each either on or off, and every way of setting the three of them together is one variant: $$ 2 \times 2 \times 2 = 2^3 = 8 $$ where: each factor is one assumption toggle with two states, on and off, and 8 is the number of distinct combinations of the three. All eight are produced when both costs and taxes are configured in your settings; fewer are produced when one of those sides is not configured, because a side with nothing set has nothing to switch between. Either way, every combination the app lets you select has a finished result behind it. ## How does Fincanva handle it? - The toggles read a variant; they never queue a run, so they work identically on an old result and a fresh one. - The rates behind the toggles are a different kind of change: editing a cost or tax rate is a settings change, which flips the run to **Needs re-run** and takes effect only after a re-run. - Reinvest profits also selects which annualized figure is shown — [CAGR](/docs/analysis/cagr) when it is on, [AAGR](/docs/analysis/aagr) when it is off — and that swap is instant for the same reason. - The live holdings view is always served from the reinvesting, costs-off, taxes-off variant, whatever the toggles above the backtest results are set to: it answers "what would this strategy hold now", not "what did it net historically". - Because the variants belong to the run, a strategy whose result is reused rather than recomputed (see [shared compute](/docs/backtesting/shared-compute)) arrives with all of its variants already in place. ## What does it look like in practice? You run a strategy once, with both cost and tax rates configured in your settings. The results open on the default view — gross of costs and tax, profits compounding. You flip **Taxes** on: the return, the annualized figure and the monthly table all drop to their after-tax values at once, because that variant was computed in the same run. You flip **Reinvest profits** off and the headline metric switches from CAGR to AAGR just as fast. Then you open Settings and change the capital-gains rate from 26% to 20%: nothing on the page moves, the run flips to **Needs re-run**, and the new rate only appears after you re-run — the eight variants belong to the run that produced them, and a new rate needs a new run. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/backtesting/rebalance # Rebalance Rebalancing is periodically resetting a strategy's holdings back to their target weights on a fixed cadence, so drift from market moves is corrected at each scheduled date rather than left to compound. Between rebalances the weights drift as some holdings rise and others fall; at each rebalance date the strategy trims what has grown past its target and tops up what has fallen below, returning the mix to plan. You choose how often this happens with **Rebalance every**, in months. **Also seen as:** rebalancing, periodic reweighting Fincanva previously called this a *rotation*; that term is retired — the app now only says Rebalance. ## How does Fincanva handle it? - **Rebalance every** is a whole number of months, chosen from **1, 3, 6, 12, 18, or 24**; the default is every month. - The rebalance interval is the master clock: other timing settings — like how long a position may be held, or how long a closed instrument stays out before it can be bought again ([reinvest delay](/docs/strategies/reinvest-delay)) — are counted in whole multiples of it (`Must be a multiple of {rebalanceEvery} months`), so changing the cadence re-snaps them. - The **Next rebalance** date is shown for each live strategy, in your browser's [time zone](/docs/backtesting/time-zone); [risk conditions](/docs/strategies/risk-condition) can trigger an extra, off-schedule rebalance when a strategy switches to its Risk-Off allocation. ## What does it look like in practice? A strategy targets 60% in a stock ETP and 40% in a bond ETP, rebalancing every month. Over the four weeks after a rebalance the stock sleeve rallies and the bond sleeve is flat, so the split drifts to roughly 63/37 — the portfolio is now carrying more equity risk than intended. On the next monthly rebalance date the strategy sells enough of the stock sleeve and buys enough of the bond sleeve to snap the mix back to 60/40, and the drift-and-correct cycle begins again. Choose a longer cadence — every 6 months — and the weights are allowed to drift much further before they are reset. See [rebalance frequency](/docs/strategies/how-often-your-strategy-rebalances) for how to pick a cadence. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/backtesting/reinvest-profits # Reinvest profits Reinvest profits is the [simulation assumption](/docs/backtesting/simulation-assumptions) that decides whether a strategy's realized profits are put back to work — so they compound — or are set aside as cash and stop contributing. In the app it is the switch labelled **Reinvest profits**, described as "Compound realized profits" and shortened to "Reinvest" in the assumptions summary. Only [realized](/docs/analysis/realized-vs-open-p-l) profit is affected: an open position's paper gain is already at work in the position itself. **Also seen as:** Reinvest, compounding, profit compounding Not to be confused with [**Reinvest delay**](/docs/strategies/reinvest-delay), a separate screening-strategy setting that keeps an instrument out of the strategy's choices for a number of months after its position closes. ## What changes when reinvest profits is off? With the assumption off, profit taken out of a closed position no longer increases the capital the strategy deploys on the next rebalance. Position sizes keep being computed from a base that does not grow with past wins, so profit accumulates beside the strategy instead of inside it — growth is additive rather than compounding, and a long run ends visibly lower than the same run with the assumption on. With it on, each realized profit raises the capital at work, so later positions are sized off a larger base. That is compounding, and it is the reason the gap between the two views widens the longer the run. ## Which annualized-return metric does it drive? This assumption also decides which annualized-return figure the metrics table shows, because only one of the two is meaningful for each case: - **On → [CAGR](/docs/analysis/cagr)**, the geometric annual growth rate — the right measure when profits compound. - **Off → [AAGR](/docs/analysis/aagr)**, the arithmetic average of the annual returns — the right measure when they do not. The row swaps in place, so a figure you read as "the annualized return" can be either metric depending on this one switch. Check which of the two labels the row is carrying before comparing two strategies. ## How does Fincanva handle it? - **Reinvest profits is on by default** — the one assumption of the three that starts switched on, so results compound out of the box. - Flipping it switches the displayed result immediately, with no new run (see [simulation assumptions](/docs/backtesting/simulation-assumptions)). - It applies to realized profit; unrealized gains on open positions are unaffected either way. - Cash the strategy is not holding in positions accrues interest in the simulation on its own terms, independently of this assumption — see [interest received and paid](/docs/analysis/interest-received-and-paid). - It is independent of the [costs](/docs/backtesting/costs-toggle) and taxes assumptions, so any combination of the three can be viewed. ## What does it look like in practice? Take 10,000 of starting capital and, purely to isolate the mechanic, a flat 8% a year for 10 years. - **Reinvest profits on** — each year's 8% is earned on a base that already includes previous years' profit: 10,000 × 1.08¹⁰ ≈ **21,589**. - **Reinvest profits off** — each year's profit is 8% of the original 10,000, i.e. 800, set aside ten times: 8,000 of profit on top of the untouched 10,000 = **18,000**. Same strategy, same yearly return, a gap of about 3,589 that comes only from whether profit was put back to work. The gap grows with the length of the run: it is small over two years and large over twenty. *A flat yearly return is an arithmetic illustration of compounding, not something a real backtest produces, and not a projection of any strategy's returns.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/backtesting/run-status # Run status Run status is the lifecycle state of a strategy's [backtest](/docs/getting-started/backtest) result, shown as a status chip that tells you whether the numbers you are seeing still reflect your current settings and the latest market data. The chip reads one of seven states, and it is always **one word or phrase — never a date**. **Also seen as:** backtest status **Every one of the seven describes the strategy, never Fincanva.** Three of them — **Set aside**, **Incomplete** and **To run** — Fincanva knows from your own account and your own strategy, so they are true right now and need no engine at all. The other four describe the last backtest result, which Fincanva checks against your current settings and the latest market data rather than trusting a stored badge. When Fincanva cannot reach the compute engine, those four fall back to the last state it recorded — and if that recording is older than the latest market data, the chip says so by reading **Needs re-run**, not by printing a timestamp beside a word that is no longer true. ## What each status means Each chip is one of these states, quoted exactly as the app shows them: - **Set aside** — your plan does not cover this strategy, so it cannot run however complete it is. In your library its row carries, before the name, a small square with the bars of the plan level that would bring it back, whose tooltip says which of the two reasons it is; its chip reads **Set aside** beside the same bars, and so does the strategy's own page header. It is the first thing Fincanva asks about a strategy, ahead of Incomplete, because finishing a strategy the plan does not cover would not make it runnable. Nothing is deleted and nothing is edited; the strategy becomes runnable again the moment the plan covers it. Pressing Backtest on it is refused with a message naming your plan — see [plan compliance](/docs/backtesting/plan-compliance) for the two things that put a strategy there and how each clears. - **Incomplete** — the strategy does not yet hold enough to run: a [Combined](/docs/getting-started/combined) with fewer than two components, or one you have started and not filled in. There is nothing to launch, which is why it does not read To run: a Combined below the floor shows its Run button disabled, saying what is missing. Finish it and it becomes To run. - **To run** — the strategy is complete but has never been backtested, so there is nothing to show yet. - **Computing** — a run was launched and has not come back. Inside a results view the same state carries a live progress percentage (`Computing results… {progress}%`); you do not need to refresh, the results replace it when done. - **Up to date** — the result matches your current settings and the latest data; the numbers are current. - **Needs re-run** — the result on screen no longer stands, so what you see is the previous run, dimmed. Two different things put a strategy here and they mean the same thing to you: a setting changed since the last run, or a new market day arrived after it. Press Re-run. - **Failed** — the last run produced no results. Pressing **Backtest** asks the engine to try again: if the engine takes the run, the strategy moves to **Computing**; if it declines, the strategy stays Failed until new market data arrives or you change the strategy's settings. Fincanva does not show why a run failed. Related reading: [bankruptcy rules](/docs/backtesting/bankruptcy-rules). A Single strategy that is switched off cannot run either: the top of its settings says "This strategy is switched off and is not simulated." with a **Switch back on** button, and a run is refused until you press it. A green, up-to-date chip means the last result is current — it is not a promise that the results page will render, and a "no results" placeholder does not always mean you simply haven't run the strategy. ## Can I re-run a strategy whose last run failed? Yes — pressing **Backtest** (or **Re-run**) on a strategy whose last run failed asks the engine to try again, so the press is never a guaranteed result. If the engine takes the run, it starts like any other and the chip moves to **Computing**. If the engine declines, no run starts and Fincanva answers `The run didn't restart: the engine still holds a failed result for these settings. Try again later, or change the strategy's settings`. Two other things also clear a failed run. **New market data** makes the strategy runnable again on its own, with nothing for you to do. **Changing the strategy's own settings** does it immediately: the starting year, the starting capital, the base currency, the portfolio settings, a cost or reinvest setting. That second one is the lever you hold when the engine declines the retry. **Changing only the benchmark is not a reliable way out.** A benchmark is a separate comparison series rather than part of the strategy's own settings, so swapping it can leave the run exactly where it was. Change something in the strategy itself. Opening a strategy whose last run failed shows a notice that stays on every tab of its workspace, headed `The last run failed` and reading `The engine produced no results for these settings. Press Backtest to try again.` On a public strategy you can view but not run, the notice reads only `The engine produced no results for these settings.` A results section on that strategy says `No results — the last run failed` rather than inviting you to run it, and the freshness marker beside the results reads `Last run failed` with a `see why` link that opens `The last run produced no results. Press Backtest to try again.` The **Backtest** and **Re-run** buttons stay enabled on a failed strategy, because pressing one is how you ask for the retry. A declined retry changes nothing: the strategy stays **Failed**, with its notice and its marker, until the engine takes a run. **Fincanva does not tell you why a run failed.** No notice, marker or message carries a reason, and there is nowhere in the app to look one up. ## Why it flips to Needs re-run Editing any setting that feeds the backtest flips the status to **Needs re-run**, because the saved result no longer matches your configuration. Changing the [rebalance](/docs/backtesting/rebalance) frequency, the benchmark, or a cost or tax rate in Settings all invalidate the last run. Flipping one of the three [simulation assumption](/docs/backtesting/simulation-assumptions) toggles does not: every combination is computed in the same run, so a toggle only picks which finished result is displayed. When a setting does invalidate the run, the app shows `Settings changed — re-run to update the results.` and keeps displaying the previous numbers, dimmed, until you re-run. A manual **Backtest** is today's reliable way to bring a strategy back Up to date. ## Why a new market day flips it too, even when you changed nothing A backtest result belongs to the market data it was computed against, so when a newer market day arrives the result stops being current — even though your settings are untouched. The chip moves from **Up to date** to **Needs re-run** for exactly the reason a settings change moves it: the numbers on screen no longer stand. Re-run brings the strategy onto the new day's data. This is why a book left alone overnight can read **Needs re-run** almost everywhere the next morning, with nothing edited and nothing broken. It is the honest reading, and it is the one Fincanva now gives you: a result from an earlier market day is not up to date, however recently it was computed. Strategies you [follow Live](/docs/getting-started/mark-live) are recomputed for you on Fincanva's daily schedule, so they return to **Up to date** without you doing anything — see [daily warm](/docs/backtesting/daily-warm-of-live-strategies) and [data freshness](/docs/backtesting/data-freshness-and-frontier). ## What happens when Fincanva cannot reach the engine? **Most of your book does not change its wording at all** — which is the point. A strategy that is **Set aside**, **Incomplete** or **To run** stays exactly as it was: those three are read from your own account and your own strategy, and are true whether or not the engine answers. The other four fall back to the last state Fincanva recorded, and the page carries the caveat once, above the list: `Couldn't reach the engine — showing results as of {date}.` Where nothing was ever recorded, that line names no date and reads `Couldn't reach the engine — showing the last available results.` instead. **A date qualifies an answer that is not current — never one that is.** The chips themselves stay one word, because a status says what is true, not when somebody last looked; `Up to date` needs no date because it is current by definition. Wherever Fincanva shows you a date next to a run result — this banner, or the same caveat in the strategy's own menu — it is telling you the same thing: this is the last thing it managed to see, and here is when. A recorded state is only believed while it can still be current. If the last recording predates the latest market data, the four engine-sourced states do not keep pretending: an **Up to date** or **Computing** recording from an earlier day reads **Needs re-run**, which is the truthful answer and the actionable one. Figures are kept either way, shown dimmed, so the page is never blank. Two further consequences are worth knowing. A **Computing** row that Fincanva cannot confirm drops its progress percentage and its spinner: the state stays true — a run was launched and has not come back — but the percentage would be a claim about an engine nobody can reach. It keeps its place in the list rather than being moved to the bottom. And the counts beside a list are counts of what was last recorded, not of what is true right now. **What you will never see is a strategy whose state has become a statement about Fincanva.** A perfectly healthy strategy does not turn into *unavailable* because a network call failed, and a strategy mid-recompute does not turn into *needs re-run* merely because the check did not go through — the two used to happen, and it hit hardest the strategies you [follow Live](/docs/getting-started/mark-live), because those are the ones Fincanva keeps recomputing for you. ## What does it look like in practice? A strategy is **Up to date**, rebalancing every three months. You open its settings and change the rebalance frequency to monthly, then save. Because the saved result was computed for the old cadence, the chip immediately flips to **Needs re-run** and the metrics dim. You press Re-run: the chip becomes **Computing**, the results view shows **Computing results… 40%**, and when the engine finishes it settles back to **Up to date** with the new monthly-rebalance numbers. You come back the following morning, having changed nothing: a new market day has arrived, so the chip reads **Needs re-run** again — and one more Re-run puts it back on the latest data. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/backtesting/shared-compute # Shared compute Shared compute is Fincanva computing one result per distinct strategy setup and reusing it wherever that same setup appears, so a strategy whose exact setup has already been computed returns its result immediately instead of running from scratch. A result belongs to the setup that produced it — the instruments, the rules, the settings, the start year, the benchmark — and not to the account that asked for it. Two strategies that are identical in every one of those respects are the same question with one answer. **Also seen as:** deduplication, result reuse ## Why was my run instant? Because the answer already existed. Pressing Run on a setup that has been computed before does not recompute it: the finished result is served, [compute time](/docs/backtesting/compute-time) reads a fraction of a second, and the [status](/docs/backtesting/run-status) goes to **Up to date** without ever passing through a visible **Computing** phase. The reverse also happens: a strategy you have just created can already be **Computing** the first time you look at it, because an identical setup is already being computed and its result is the one you will get. ## What counts as the same setup? Everything that feeds the [backtest](/docs/getting-started/backtest). Change one input — an instrument, a rebalance cadence, the benchmark, a cost or tax rate, the start year — and the setup is no longer the same, so no existing result matches it and the next run computes in full. Change nothing and it stays a match, which is why duplicating a strategy and running the copy is effectively free. The three [assumption toggles](/docs/backtesting/precomputed-toggle-variants) are the exception that proves the rule: they are not part of the setup, because all of their combinations are computed in the same run. ## How does Fincanva handle it? - Asking for a setup that is already computing does not start a second run of it — you wait on the one already under way and get its result. - Reuse is not a stored badge that can go stale: a reused result is still checked against your settings and the latest market data, so a match that is no longer current is recomputed rather than served (see [data freshness](/docs/backtesting/data-freshness-and-frontier)). - Public strategies benefit the most, because many accounts open the same setups — and a separate server-side sweep, not your [daily warm](/docs/backtesting/daily-warm-of-live-strategies), has usually computed them before anyone arrives. - Nothing about your strategy is shown to anyone else by reuse; what is shared is the computed answer to an identical setup. ## What does it look like in practice? A public strategy has been run many times, so its result exists. You use Copy to Mine and press Run on your copy without editing anything: the setup matches, the finished result is served, and the **Compute** column reads a near-instant time — no queue, no progress bar. You then change one thing, the [rebalance](/docs/backtesting/rebalance) cadence, from quarterly to monthly. That single edit makes the setup new: nothing matches it, the status flips to **Needs re-run**, and the next run computes the whole backtest for the first time, with a compute time that reflects the full work. Change the cadence back to quarterly and the original result matches again. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/backtesting/simulation-assumptions # Simulation assumptions Simulation assumptions are the three modelling choices applied to every [backtest](/docs/getting-started/backtest) — **Costs & interests**, **Taxes**, and **Reinvest profits** — that decide whether results include trading costs and financing, whether tax is deducted, and whether profits compound. They sit above the results as a toggle group labelled **Simulation assumptions**, with a `{count} on` count of how many are active. The word "Assumptions" is no longer used as a navigation label — this group carries the name. **Also seen as:** backtest assumptions ## Instant-recompute vs persisted The three toggles and the rates behind them behave differently, which is the key to reading them: - **Instant-recompute — the toggles.** Flipping **Costs & interests**, **Taxes**, or **Reinvest profits** switches what you see immediately, with no new run. Fincanva computes every combination when the strategy runs, so a toggle just reads the matching [already-computed variant](/docs/backtesting/precomputed-toggle-variants). - **Persisted — the rates.** The values behind the toggles — your cost and interest assumptions, and your tax rates and [regime](/docs/backtesting/tax-regime) — are saved in Settings. Changing a rate is a settings change: it flips the run to **Needs re-run** and only takes effect after the strategy re-runs. ## How does Fincanva handle it? - **Costs & interests** covers trading costs, financing, and interest; **Taxes** covers tax on dividends and realized [capital gains](/docs/backtesting/capital-gains-tax); **Reinvest profits** compounds realized profits. - These three choices govern the Analysis views. The [Holdings view](/docs/backtesting/holdings-forced-assumptions) ignores them and always reads the gross, fully-reinvested version, which is why the two can show different numbers. - By default a backtest is shown with Costs & interests and Taxes off and Reinvest profits on — so out of the box the numbers are gross of costs and tax, with profits compounding. - Reinvest profits also drives which annualized-return metric appears: on shows [CAGR](/docs/analysis/cagr) (geometric), off shows [AAGR](/docs/analysis/aagr) (arithmetic). ## What does it look like in practice? A strategy is showing a gross return with **Taxes** off. You flip Taxes on: the displayed return, its annualized figure, and the monthly numbers all drop to their after-tax values immediately, because that variant was pre-computed at the last run — no new run happens. What persists is everything you didn't touch: the run itself, the strategy's settings, and your saved tax rates are all unchanged, so flipping Taxes back off restores the gross view instantly. Editing a tax rate in Settings is the opposite kind of change — that is persisted, and the strategy must re-run before the new rate shows up. *Switching an assumption changes what a past run is reported to have produced, not what a strategy will produce.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/backtesting/simulation-start-year # Simulation start year The simulation start year is the first calendar year your backtest runs from. It sets where the historical replay begins, so it decides how much market history the results include — a start in 2000 spans more cycles than a start in 2015. In the app the setting is labelled "Starting year". **Also seen as:** Starting year ## What counts as a good value? There is no single right start year — it depends on the story you want the backtest to tell. An earlier start includes more market conditions, including sharp declines like 2008, so the metrics reflect how the strategy would have weathered them; a later start focuses on more recent regimes but hides earlier stress. A start year only works if the instruments in the strategy have price data that far back. ## How does Fincanva handle it? - **Your plan sets the earliest start year, and Fincanva applies it** — 2020 on Free, 2010 on Starter, 2000 on Advanced, no floor on Ultimate and Professional. The picker lists no earlier year, a save asking for one is refused, and a strategy that already starts earlier after a plan change is set aside, not moved. See [what each plan includes](/docs/account-security/what-each-plan-includes#what-sets-the-backtests-starting-year). - The default start year is 2000, or your plan's floor where that is later. - On a plan with no floor the picker runs from the current year back to 1793, so you can start earlier than 2000 as well as later. What limits a run in practice is price history, not the picker: a start year only produces results for the years your instruments actually have data for, and almost every instrument's history begins far later than 1793. - Choosing a later start year shortens the backtest and drops the earlier history from every metric. - Changing the start year is a settings change, so the [backtest](/docs/getting-started/backtest) recomputes on the next run. ## What does it look like in practice? A strategy is backtested twice with no other change. Starting in **2008** places the opening of the run right at a major market decline, so the early equity curve falls before it recovers and the drawdown and return figures carry that shock. Starting in **2010** begins after the worst of that decline, so the same strategy shows a smoother early curve and different headline metrics. Neither is "more correct" — they answer different questions, which is why the [start-date sensitivity](/docs/analysis/start-date-sensitivity) view exists. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/backtesting/slippage # Slippage Slippage is the difference between the price an order is quoted at and the price it actually fills at. In real markets an order rarely executes at exactly the price you saw when you placed it — the fill can be a little worse — and that gap is a real cost of trading. Fincanva models slippage so backtest results reflect it rather than assuming every trade fills at the ideal price. It is the **price** half of trading costs and is proportional to the value traded; the fee half is [transaction cost](/docs/backtesting/transaction-cost), a flat charge per fill that does not scale at all. **Also seen as:** execution slippage, fill-price slippage ## How is slippage calculated? Slippage is the fill price minus the quoted price, measured per unit or as a percentage of the quote. $$ \text{Slippage} = P_{\text{fill}} - P_{\text{quote}} $$ where $P_{\text{fill}}$ is the price the order actually executes at and $P_{\text{quote}}$ is the price it was quoted at; expressed as a fraction it is that gap divided by $P_{\text{quote}}$. ## What counts as a large value? Smaller slippage is better, because it eats less of each trade's value. Slippage tends to be larger for bigger orders and thinner, less liquid instruments, and it compounds with how often a strategy trades — a high-turnover strategy pays it more often than a buy-and-hold one. ## How does Fincanva handle it? - Slippage is modelled as a small proportional cost applied to each fill, so unlike the flat transaction fee it scales with the value traded. - It is a fixed platform assumption today — there is no setting in the app for changing the slippage a backtest models. - It is applied only when **Costs & interests** is on; with costs off, modelled slippage is zero. - The slippage paid feeds the costs shown in your results, alongside transaction fees and financing costs. In the positions view it is aggregated with the per-trade fee into the "Costs" figure rather than shown as its own line. ## What does it look like in practice? A strategy places an order for a stock quoted at **100.00**. Because the fill lands slightly worse than the quote, the order executes at **100.25**. The slippage is 0.25 per share, or 0.25% of the quoted price — a cost that never appears in a naive "filled at the quote" backtest but does appear here once costs are on. The 0.25% is illustrative arithmetic chosen to make the sum easy to follow, not the fraction the model applies. Over many trades this small per-fill gap adds up, which is why turnover-heavy strategies feel it most. *The slippage a backtest models is an assumption applied to historical results, not the fill you would get in a real market, so a result net of it is still not what a strategy will do.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/backtesting/starting-capital # Starting capital Starting capital is the amount of money a [backtest](/docs/getting-started/backtest) begins with — the initial portfolio value every simulated figure is scaled from. It is a single account-level setting, listed in Settings under "Simulation defaults" as **Starting capital** ("Initial portfolio value for new simulations."), and it applies to the strategies you own. Raising or lowering it rescales all the money figures a run produces and leaves the percentages — return, [drawdown](/docs/analysis/max-drawdown), [volatility](/docs/analysis/volatility) — essentially unchanged. **Also seen as:** initial capital, initial portfolio value ## Does starting capital change a strategy's results? Not in percentage terms. A strategy's rules do not depend on how much money is behind them, so the same rules over the same period produce the same percentage outcome at any capital; only the money amounts scale. $$ \text{profit} = \text{starting capital} \times \text{total return} $$ where total return is the strategy's return over the period as a fraction (so +45% is 0.45) and starting capital is the amount you set. Because the return is the same on both sides, the money figures move in exact proportion to the capital. ## When does starting capital actually matter? It matters at small capital, because a portfolio can only hold whole shares. Each holding's ideal money amount is its [target notional](/docs/portfolio-holdings/target-notional), and that amount has to be rounded down to a whole number of shares, leaving a little cash unspent — see [target vs deployed](/docs/portfolio-holdings/target-vs-deployed). That leftover is a fixed size per holding but a much bigger slice of a small portfolio, so at low capital more of the target goes unfilled, [accuracy](/docs/portfolio-holdings/accuracy) is lower, and a high-priced instrument may not fit at its intended weight at all. At large capital the same rounding is negligible. The rounding is redone at every [rebalance](/docs/backtesting/rebalance), so at low capital the shortfall recurs rather than being a one-off at the start. What happens to cash the strategy is not holding in positions is covered by [interest received and paid](/docs/analysis/interest-received-and-paid). ## How does Fincanva handle it? - The default starting capital is 100,000, and the setting offers a fixed ladder of ten amounts from 10,000 up to 10,000,000. Each option is displayed in your [base currency](/docs/backtesting/base-currency). - Starting capital is part of what identifies a simulation, so changing it means the results for your own strategies are recomputed on the new amount rather than converted. - A public strategy you do not own is always computed on the default 100,000, whatever your own setting is — so its money figures will not match the ones you would get by copying it and running it yourself. Its percentages will. - The Holdings view has its own [Capital](/docs/portfolio-holdings/capital) input for the target snapshot it shows — a different control, not this setting under another name. It starts at 100,000 rather than following your Starting capital setting, and changing it rescales that view only: the saved setting and the saved run are untouched. ## What does it look like in practice? Take the same strategy over the same period, once with 10,000 of starting capital and once with 100,000. Suppose it returns +45% over the period. The first run ends at 14,500 with a profit of 4,500; the second ends at 145,000 with a profit of 45,000 — ten times the money, the identical +45%, and the identical drawdown and volatility figures. The one real difference shows in the holdings: at 100,000 a 10% weight is 10,000, which buys 24 shares of an instrument trading at 412 and leaves 112 unspent; at 10,000 the same 10% weight is 1,000, which buys 2 shares and leaves 176 unspent — nearly 18% of that holding's target left in cash instead of 1%. *The figures on this page describe what Fincanva models, not what you should do with your money — see [Is this financial advice?](/docs/investing-theory/is-this-financial-advice#is-this-financial-advice).* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/backtesting/strategy-alerts # Strategy alerts Strategy alerts are the automatic checks Fincanva runs over a strategy's setup, graded into three severities — **blocking**, **warning**, and **info**. A blocking alert stops the strategy from being backtested until you fix it; a warning describes a setup that will run but is probably not what you meant; an info alert tells you what the strategy will do in place of a choice you did not make. Eight alerts exist today: one blocking, six warnings, and one info. They surface in both views — as a "Strategy alerts" group at the top of [All at once](/docs/getting-started/all-at-once), on the individual setting cards they belong to, and in the [Step by step](/docs/getting-started/step-by-step) Review hero. ## What do the three severities mean? Severity decides whether the alert stops the run and whether you can dismiss it. - **Blocking** — the strategy cannot be backtested. The header reads `Can't run · {count} errors` and the settings footer reads `{count} errors · fix before backtest`. There is no Accept button; the underlying setting has to change. - **Warning** — the strategy runs, but the setup is likely unintended. The header counts these as `{count} issues to review`. - **Info** — nothing is wrong; the alert states a fallback the strategy will use. Info alerts never change the header's tint. When no alert is active, the header reads **Ready to run**. Counts appear next to each other as `{count} blocking`, `{count} warnings`, and `{count} info`. ## What does Accept do, and can I undo it? Accept acknowledges a warning or info alert and moves it out of the active list into a **Handled · `{count}`** section — it changes nothing about the strategy itself, it only records that you have seen the alert. **Restore** brings one back to the active list, and **Reopen all** brings back every handled alert; **Accept all** handles the whole active batch at once. Accepting the last active warning returns the header to **Ready to run**. Two kinds of alert have no Accept: every blocking alert, and the warning "Risk-Off allocation is the same as Risk-On." — a Risk-Off profile that mirrors Risk-On does nothing at runtime, so the only real fix is to change the parameters. Acceptances are stored on the strategy and are never cleared automatically, so if the same condition arises again later the alert stays in Handled rather than reopening. ## Which alerts can appear, and what fixes each one? Each quote below is the exact text the app shows, followed by what triggers it and what clears it. - **Blocking — "Risk-Off allocation needs to be set."** The strategy has an active [risk condition](/docs/strategies/risk-conditions) but no Risk-Off allocation, so there is nothing to switch to. The alert's action button reads "Resolve Risk-Off", and its short form on the alert card is "Risk-Off not configured — Required before the strategy can run". Set the Risk-Off allocation to clear it. This is the only blocking alert today, so it is the only one that can produce `Can't run`. - **Warning — "Your screener will filter the instruments you selected — make sure the combination is what you want."** You have both hand-picked instruments and at least one attached screener, so the screener narrows your own list rather than searching the whole market. Remove one side, or Accept if the combination is deliberate. - **Warning — "Risk-Off allocation is the same as Risk-On."** Both allocation profiles carry the same [allocation method](/docs/strategies/allocation-and-allocation-method) and parameters, so switching between them changes nothing. Change one of the two profiles; there is no Accept for this alert. - **Warning — "This strategy has no rule to fully close positions. Once an instrument enters the portfolio, it stays — only its weight gets adjusted on rebalance."** Nothing in the setup can fully exit a position: no [stop-loss](/docs/strategies/stop-loss), no [take-profit](/docs/strategies/take-profit), no maximum holding period, no [exit screener](/docs/getting-started/screener-attach), and no Risk-Off profile that differs from Risk-On. Add one of those, or Accept. - **Warning — "Duplicate screener detected — one is redundant or contradicting the other."** The same source screener is attached more than once, counting entry and exit screeners together. Remove the duplicate. - **Warning — "You have an exit screener but no entry screener. The strategy's working universe is limited — if many instruments in it match the exit rule at the same time, the portfolio will sit in cash until they stop matching."** Only an exit screener is attached, so the pool the strategy can hold is whatever you picked, and the exit rule can empty it. Add an entry screener, or Accept. - **Warning — "This allocation invests nothing: every weight is zero, so no capital goes anywhere. Set at least one weight above or below zero."** The allocation in use is [Fixed Weights](/docs/strategies/fixed-weights) or [Ranking-Based](/docs/strategies/ranking-based) and every weight you typed is 0 — including the ten zero tier weights a fresh Ranking-Based setup starts with — so the strategy holds nothing. Its short form on the alert card is "Allocation invests nothing — Every weight is zero, so no capital is invested". The Risk-Off allocation is checked only while a risk condition is active. It is raised for a single strategy's own allocation and, the same way, for a [Combined](/docs/strategies/combined-weighting) whose own selected allocation invests nothing across its member strategies in use — its totals line reads "Invests nothing" either way. Accepting it accepts it for every strategy that shares the underlying condition — a Combined and its member strategies together. Set at least one weight other than zero, or Accept if an all-cash allocation is what you want. - **Info — "No instruments picked and no entry screener — the engine will filter by volatility ranking, keeping as many instruments as Max positions allows."** You have selected nothing and attached no entry screener, so the selection falls back to a volatility ranking, capped by [Max positions](/docs/strategies/max-positions) ("Cap how many instruments are held at once"). Pick instruments or attach an entry screener if you want the selection to be explicit. ## What does it look like in practice? You build a strategy over ten instruments, equal-weighted, rebalancing monthly, and you set no exit rules at all. The header shows `1 issue to review` and the "Strategy alerts" group lists the warning "This strategy has no rule to fully close positions. Once an instrument enters the portfolio, it stays — only its weight gets adjusted on rebalance." Nothing is broken — the strategy will still backtest — but it tells you the design has no way out of a position, only reweighting at each [rebalance](/docs/backtesting/rebalance). You have two routes: add an exit (a stop-loss, a take-profit, a maximum holding period, an exit screener, or a Risk-Off profile that differs from Risk-On), which makes the warning stop firing; or press **Accept**, which moves it to **Handled · 1** and returns the header to **Ready to run** without changing the strategy. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/backtesting/tax-regime # Tax regime The tax regime is the mode — **Declarative** or **Administered** — that governs how the taxable gains in your simulation are reported and settled. These are the two retail regimes used in Italy: under the Declarative regime you report your gains yourself in your own tax return, while under the Administered regime an intermediary calculates, withholds, and files the tax on your behalf. In the app the setting is "Tax regime", described as "How taxable events are reported in your jurisdiction." **Also seen as:** regime fiscale ## How the two regimes compare The regimes change *who reports and settles* the tax, not the rate on a given gain. The table shows the difference as it works in real life; the next section says what the regime changes inside a backtest. | | Declarative | Administered | |---|---|---| | Who calculates the tax | You | The intermediary | | Who files it | You, in your tax return | The intermediary, at source | | When it settles | At tax-return time | As events occur | | Your visibility of gross gains | Full (you report each) | Handled for you | ## What does the tax regime change in a backtest? Under **Italy** residency the regime changes three things in the simulation — when the tax is charged, how losses offset gains, and how a partial sale is valued — so two runs that differ only in regime can end with different tax figures even at the same rate. - **When the tax is charged.** Under **Declarative** the year is settled as a whole: the year's net result is taxed once, when the next year begins. Under **Administered** each gain is taxed as it is realized. - **How losses offset gains.** Under **Declarative** a loss offsets any non-ETF gain of the same year, whatever order they came in. Under **Administered** a loss only offsets gains realized after it; a gain taxed before the loss happened is not revisited. The window during which a loss stays usable is counted differently too — [capital-gains tax](/docs/backtesting/capital-gains-tax#what-happens-to-a-realized-loss) has both rules. - **How a partial sale is valued.** When a strategy sells only part of a position it built up over several purchases, **Declarative** treats the most recently bought shares as sold first, while **Administered** uses the average price of every share held. ## How does Fincanva handle it? - The regime is chosen from two options, "Declarative" and "Administered"; the default is Declarative. - The regime only changes a result under **Italy** [tax residency](/docs/backtesting/tax-residency). - The field is shown only for the **Italy** and **Other** residencies. Under **United States** it is not displayed at all, because the Declarative/Administered distinction is an Italian one. Under **Other** the field is shown, but the simulation applies the same rules as United States — tax settled once a year, on the year's net result — whichever regime you pick. - For Italian residency the capital-gains rates are set by tax law for the selected regime and shown as "Auto-updated" rather than edited by hand. - The regime only reaches your results through the [Taxes assumption](/docs/backtesting/taxes-toggle). With Taxes off, no regime changes any figure. ## What does it look like in practice? Two simulations under Italian residency realise the **same 1,000 gain** in March and a **400 loss** in September, and differ only in regime. Under the **Declarative** regime nothing is charged during the year: the year is settled as a whole when the next one begins, the September loss is set against the March gain, and the tax is 26% × 600 = **156**. Under the **Administered** regime the March gain is taxed when it is realized, 26% × 1,000 = **260**, and the September loss cannot reach back to it — it is carried forward, and only reduces gains the strategy realizes later. Same rate, same trades: the regime changed when the tax was paid and how much of the loss had been used by the end of the year. *This describes what Fincanva models in a simulation, not tax advice for your own situation — see [Is this financial advice?](/docs/investing-theory/is-this-financial-advice#is-this-financial-advice).* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/backtesting/tax-residency # Tax residency Tax residency is the country whose tax rules Fincanva applies to your simulated trades. It is the setting that decides *which* tax rates a backtest uses — and, less obviously, *what shape* those rates take, because not every jurisdiction taxes gains by how long you held them. In the app it is the "Tax residency" field, described as "Country whose tax rules apply to your simulated trades", with three options: **United States**, **Italy**, and **Other**. **Also seen as:** fiscal residency, country of residence ## What does changing tax residency change? Picking a residency re-seeds the whole tax card: the [tax regime](/docs/backtesting/tax-regime) and each rate are set to the values that jurisdiction uses, and the fields the cascade touched are flagged with an "Auto-updated" badge so you can see what moved. The starting values are: | Residency | Short-term capital gains | Long-term capital gains | Dividend tax | |---|---|---|---| | **United States** | 35% | 20% | 20% | | **Italy** | *not applicable — field hidden* | 26% (locked) | 26% (locked) | | **Other** | 20% | 20% | 15% | Residency also decides which of those fields you can still edit. Under **Italy** the long-term and dividend rates are read-only, with the hint "Set by Italian tax law for the selected regime." Under **United States** and **Other** all the rates are yours to set. ## Does the holding period change the tax rate? Whether the holding period matters at all depends on your residency. Under **United States** and **Other** rules both rates exist and the holding period decides between them; the threshold is **more than one year — more than 365 days between opening and closing the position.** A position held for exactly 365 days is still short-term; it has to pass the threshold, not merely reach it. Under **Italy** there is no short/long split: the app hides the short-term field entirely and a single rate applies to realized gains however long they were held. See [capital-gains tax](/docs/backtesting/capital-gains-tax) for how the rate is then applied — it is charged on your net result for the year, not on each winning position, so that page is also where the loss-offsetting rules live. ## Does residency change what happens to my losses? Yes, and it is the part of this setting people are most often caught by. A realized loss reduces the gains you are taxed on, but **how long it stays usable, and against what, is set by your residency**: - **United States** and **Other** — losses carry forward with no time limit, and a carried loss keeps its short-term or long-term character. - **Italy** — losses stay usable for five years, counted in a way that depends on the [tax regime](/docs/backtesting/tax-regime); there is a single rate so there is no character to keep; and **a gain on an ETF cannot be reduced by any loss, while a loss on an ETF can be used to reduce other gains.** [Capital-gains tax](/docs/backtesting/capital-gains-tax#what-happens-to-a-realized-loss) is the full account of all three, including what the Italian ETF asymmetry does to a portfolio built mainly of ETFs. ## How does Fincanva handle it? - The default residency follows your interface language: an English interface starts on **United States**, an Italian one on **Italy**. That is why one fresh account shows a 35%/20% short-and-long pair and another shows a single 26% rate. - Every residency starts on the **Declarative** [tax regime](/docs/backtesting/tax-regime). Under **Italy** and **Other** you can switch it; under **United States** the regime field is not shown, because the distinction is an Italian one. Only under **Italy** does the regime change a result: **Other** is taxed by the same rules as United States whichever regime is selected. - Residency only affects results when the [Taxes assumption](/docs/backtesting/taxes-toggle) is on. With Taxes off, no rate of any residency is applied. - It is a saved setting, not a view toggle: changing it flips existing runs to **Needs re-run**, and the new rates apply after a strategy runs again. - Dividends can also be reduced by [withholding tax](/docs/backtesting/withholding-tax) deducted at source, which Fincanva applies automatically and which has no rate field of its own. - In earlier versions of the app this setting was also labelled "Country". That name now belongs only to the geographic filter used when selecting instruments, so the two are unrelated controls. ## What does it look like in practice? The same strategy realizes a **5,000 gain on a briefly held position**, and only the residency differs. - **United States** — the position was held less than a year, so the gain is short-term and meets the 35% rate: 35% × 5,000 = **1,750 of tax**. - **Italy** — there is no short/long distinction, so the single 26% rate applies whatever the hold was: 26% × 5,000 = **1,300 of tax**. Hold the same position for more than a year and the US answer changes — the 20% long-term rate applies instead, so 20% × 5,000 = **1,000 of tax** — while the Italian answer does not move at all. The holding period is only a lever where the residency's rules make it one. Change one more thing and the residencies part company again: give the strategy a **2,000 realized loss** in the same year. The loss is set against the gain first — under Italy, on the default Declarative regime — so the taxable gain becomes 5,000 − 2,000 = **3,000** under both. The short-held US case now pays 35% × 3,000 = **1,050**, and the Italian case 26% × 3,000 = **780**. But if that 5,000 gain had been on an **ETF**, the Italian answer would not move at all — an ETF gain cannot be reduced by a loss, so it stays 26% × 5,000 = **1,300**, and the 2,000 loss waits instead for a non-ETF gain to reduce. Under **Italy** the unused remainder of a loss also expires after five years rather than carrying indefinitely. *The figures on this page describe what Fincanva models, not what you should do with your money — see [Is this financial advice?](/docs/investing-theory/is-this-financial-advice#is-this-financial-advice).* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/backtesting/taxes-toggle # Taxes toggle The taxes toggle is the [simulation assumption](/docs/backtesting/simulation-assumptions) that decides whether a backtest deducts tax, or shows its results gross of tax. In the app it is the switch labelled **Taxes**, described as "Tax on dividends & realized gains" and shortened to "Taxes" in the assumptions summary. Like the other assumptions it switches what the *same run* is showing; the strategy and its history are untouched. **Also seen as:** Taxes, taxation ## What does turning taxes on change? Turning **Taxes** on applies your saved tax settings to the run and deducts the resulting tax from its results. Those settings are your [tax residency](/docs/backtesting/tax-residency), your [tax regime](/docs/backtesting/tax-regime), the short-term and long-term [capital-gains](/docs/backtesting/capital-gains-tax) rates, and the [dividend tax](/docs/backtesting/dividend-tax) rate. Two kinds of event are taxable, and one is not: - **Realized gains** — a position closed at a profit is taxed at the applicable capital-gains rate. - **Dividends** — dividend income is taxed at the dividend rate, applied to the dividend as received after any [withholding tax](/docs/backtesting/withholding-tax) at source. - **Open (unrealized) gains** are not charged tax: no tax leaves the account for a holding you still own, however far it has risen. Open gains still show in the after-tax figures, though. With Taxes on, the value a run reports each day is **net of the tax the strategy would owe if it sold everything that day** — the tax on its still-open gains together with the tax on what it has realized but not yet paid. So the after-tax curve reflects a gain's tax while the gain is still open, and selling the position does not suddenly cut the curve by that tax. With the toggle off, the tax line is zero and every figure is gross of tax — dividends are credited in full, with no withholding at source either. ## How does Fincanva handle it? - **Taxes are included from the Advanced plan.** Free and Starter run every backtest with the assumption off and cannot turn it on; Advanced, Ultimate and Professional include it. See [what each plan includes](/docs/account-security/what-each-plan-includes). - **Taxes is off by default**, so the first figures you see are gross of tax. - Flipping it switches the displayed result immediately, with no new run — the after-tax variant was pre-computed when the strategy ran (see [simulation assumptions](/docs/backtesting/simulation-assumptions)). - The tax deducted appears as the "Taxes" band in the capital and [P&L breakdown](/docs/analysis/p-l-breakdown). - The rates behind the toggle are saved settings: editing one is a settings change that takes effect only after the strategy runs again. - The toggle is independent of the [costs toggle](/docs/backtesting/costs-toggle) — you can view a run after tax but before costs, or any other combination. - The Holdings view does not follow this toggle: it always reports with taxes off, one of its [Holdings forced assumptions](/docs/backtesting/holdings-forced-assumptions). ## What does it look like in practice? One run, two views. With **Taxes** off a strategy's curve ends at a total return of +42.0%, gross of tax. Flip Taxes on and the same curve ends lower — say +34.8% — because the gains the strategy realized along the way were taxed at the capital-gains rate, each dividend was taxed at the dividend rate, and the final value sets aside the tax still owed on the gains open at the end. When that tax actually leaves the simulated account depends on the [tax regime](/docs/backtesting/tax-regime) — as each gain is realized under Administered, once a year under Declarative and under United States and Other residency — rather than at the moment of every individual gain. The 7.2pp difference is not a different strategy or a different period: it is the same run with the tax that its trades and dividends would have triggered taken out. A strategy that realizes gains often meets that deduction more often than one that holds its winners. *The figures on this page describe what Fincanva models, not what you should do with your money — see [Is this financial advice?](/docs/investing-theory/is-this-financial-advice#is-this-financial-advice).* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/backtesting/time-zone # Time zone A time zone is the offset from universal time that decides what clock reading a moment is written as, and Fincanva writes every date and time in the app in the time zone **your browser reports**. Nothing is saved on your account: the browser you are signed in on is what decides, every time a page is loaded. A panel embedded in another site is the exception — it is read outside your session, so it falls back to UTC. **Also seen as:** local time, browser time ## Which time zone are Fincanva's dates shown in? Yours — the one your browser reports. Rebalance dates, run timestamps, "as of" dates and the dates along a simulation are all written in that zone while you are signed in, so a moment recorded late in the evening is shown on the evening you experienced it rather than on the day it fell on somewhere else. Because the browser decides, the same account read from two machines in two zones shows the same moment as two different local readings. Neither is wrong: they are one instant written on two clocks. ## Why did a date look wrong for a moment when I first arrived? Because the very first page loaded on a first visit is written in **UTC**, before your browser has had a chance to report its own zone. If you are east of Greenwich and reading late in the evening, that first load can show yesterday's date; the page settles onto your own zone immediately after, and every page from then on is already correct. It is one load on one visit. If a date still looks a day out after the page has settled, it is not this. ## Can I change the time zone Fincanva shows dates in? There is no setting for it. Fincanva has no time-zone preference to store and no control to change one — it follows whatever your browser reports, so the way to change what you see is to change the time zone of the device or browser you are reading in. ## What does the time zone not change? The moments themselves. A rebalance, a run and a simulation date are the same instants whatever zone you read them in — only how they are written down moves. Nothing Fincanva computes depends on your zone, so two people in two countries reading the same strategy see identical numbers and identical results, written against their own clocks. Relative wordings are unaffected too. A countdown or an age — how many days until the next rebalance, how long ago a run finished — measures a distance between two moments, and a distance is the same in every zone. ## What does it look like in practice? You are in Tokyo (UTC+9) and a backtest finishes at 08:00 on 12 March, London time. Fincanva shows it to you as 17:00 on 12 March, because that is the same instant on your clock. A colleague in New York (UTC−4) opens the same strategy and sees 04:00 on 12 March. The three of you are looking at one run. Now run it at 23:30 London time on 12 March. You see 08:30 on **13 March** — a different date for the same run, and the correct one for where you are. This is the case that made the rule worth stating: before Fincanva followed the browser, that run could be labelled with a day nobody reading it had actually been in. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/backtesting/transaction-cost # Transaction cost Transaction cost is the flat fee Fincanva charges once for each trade execution in a backtest. It is a fixed amount per fill — **not** a percentage of the order's value and **not** a charge per share — so a large order and a small one carry exactly the same fee. It models the commission a broker charges to execute a trade, and it is the fee half of trading costs; the price half is [slippage](/docs/backtesting/slippage), which *is* proportional. **Also seen as:** transaction fee, commission, brokerage commission ## How is transaction cost charged? One execution, one flat fee, added to the cash flow of that execution. Because a buy and a sell are two separate executions, a full round trip on one holding costs the fee twice. Nothing about the fee scales with the order: doubling the size of a trade does not double its fee. That has one practical consequence worth reading off directly — a flat fee is a **larger share of a small order than of a large one**. The same fee is a rounding error on a 20,000 order and a visible bite out of a 200 one, so it weighs most on strategies that trade small amounts often. Slippage works the other way round: it is proportional, so it scales with the value traded. The two are separate components and both are switched in by the same [costs toggle](/docs/backtesting/costs-toggle). ## How does Fincanva handle it? - The fee is a flat **1.2 per fill**, in the simulation's base currency. - It is a fixed platform assumption today — there is no setting in the app for changing the per-trade fee. - It is charged only when **Costs & interests** is on; with costs off, the modelled transaction cost is zero. - Every execution counts separately, so the total for a period follows the number of fills, not the amount of money traded. - In results it is aggregated with slippage: the "Trading costs" figure and the "Costs" column in the positions view carry both. ## What does it look like in practice? A strategy holds 10 positions and [rebalances](/docs/backtesting/rebalance) monthly, and each rebalance replaces about half the book — 5 sells and 5 buys, so 10 fills a month, 120 fills over a year. At 1.2 per fill that is 120 × 1.2 = **144** in transaction cost for the year. What that costs depends entirely on the capital, because the fee does not scale with it. On 10,000 of starting capital, 144 is about 1.4% of capital consumed by fees in one year. On 100,000 running the identical strategy, the same 144 is about 0.14%. Same trades, same fee count, ten times less drag — which is why per-trade fees hit small accounts and high-turnover strategies hardest. *The figures on this page describe what Fincanva models, not what you should do with your money — see [Is this financial advice?](/docs/investing-theory/is-this-financial-advice#is-this-financial-advice).* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/backtesting/volatility-target # Volatility target A volatility target is a setting on a Combined's allocation profile that rescales the [invested portion](/docs/backtesting/invested-portion) at every rebalance so the Combined's volatility stays close to a yearly level you choose: when the Combined has been calm it invests more, up to a maximum leverage you set, and when it has been turbulent it invests less. It keeps the risk steady rather than the amount invested — the app's note reads "Keeps risk steady, not the capital invested." It is not the same as [leverage](/docs/backtesting/leverage), which is one fixed multiplier on a strategy's positions: a volatility target changes the Combined's exposure over time, which is why it is also called dynamic leverage. **Also seen as:** volatility targeting, vol targeting, volatility scaling, risk targeting, dynamic leverage ## How does a volatility target set the exposure? At each rebalance a scaling factor compares the target with the volatility the Combined has actually shown, and the invested portion is multiplied by it: $$ k = \min\!\left(\frac{\sigma^{*}}{\hat{\sigma}},\; L_{\max}\right) \qquad e = \min\left(p \times k,\; 300\%\right) $$ where $\sigma^{*}$ is the **Target volatility (annual)**, $\hat{\sigma}$ is the annualised volatility of the Combined's own invested holdings — the assets it actually holds, per unit invested, measured over the **Measurement window** — whatever share of the Combined sits in cash beside them, $L_{\max}$ is the **Maximum leverage**, $p$ is the invested portion, $k$ is the scaling factor and $e$ is the effective exposure — the share of capital actually invested until the next rebalance. Because $\hat{\sigma}$ reads the holdings' own volatility rather than the scaled account, it does not move just because $k$ moved it the rebalance before: when $\hat{\sigma}$ lands back at the target, $k = 1$ and exposure returns to exactly $p$, the invested portion you set. In words: if the holdings have been twice as volatile as the target the Combined invests half as much; if they have been half as volatile it invests twice as much, but never more than the maximum leverage allows, and never more than 300% of its capital. ## How is a volatility target different from leverage? Leverage and a volatility target both let exposure differ from capital, and they differ in what stays fixed. [Leverage](/docs/backtesting/leverage) is set once on a strategy's allocation profile and holds the same multiple of capital through calm and storm, so the strategy's risk rises and falls with the market. A volatility target sits on a Combined and moves the exposure so the *risk* stays roughly level, investing more in quiet markets and less in turbulent ones. The two can be combined: a strategy inside a Combined keeps its own leverage, and the Combined's volatility target then scales how much of the Combined's capital reaches its strategies. ## How does Fincanva handle it? - **Where it sits.** The **Volatility target** switch is inside the invested-portion block of a Combined's allocation profile, with the help "Raises or lowers the invested portion to keep the portfolio's volatility close to the target." It belongs to the profile, so the Risk-On and Risk-Off profiles can each have their own. - **Target volatility (annual)** runs from 2% to 40%, default 10%. - **Maximum leverage** runs from 1× to 3×, default 1×, and never above your plan's leverage ceiling. Its help reads "How far the invested portion may rise when volatility is low. At 1× the target can only reduce it." - **Measurement window** runs from 20 to 250 trading days, default 60 ("The trading days over which the portfolio's volatility is measured."). - **Recalculated at every rebalance.** Between rebalances the factor stays as the last rebalance set it. Until the window holds enough history to measure the Combined's volatility, the factor is 1 and the invested portion runs unscaled. - **Effective exposure.** Under the fields the editor shows the range the setting can produce — from 0% to the invested portion times the maximum leverage — with a sentence such as "100% × a factor from 0 to 2×, recalculated at every rebalance." - **The 300% ceiling.** When the invested portion times the maximum leverage would exceed 300%, the editor warns "Part of the leverage will never be used" and offers a button, such as "Set 2×", that lowers the maximum leverage to the largest value that still has an effect. - **Above 100% the Combined borrows.** Exposure above the capital is financed exactly like an [invested portion above 100%](/docs/backtesting/invested-portion) — see there for the borrowing and its cost. - **The summary chip** under the allocation method reads, for example, "Vol target 10% (max 2×)". - **The volatility target is included from the Advanced plan**, the first [plan level](/docs/account-security/plan-level) that includes a Combined; Free and Starter do not offer it. See [what each plan includes](/docs/account-security/what-each-plan-includes). ## What does it look like in practice? A Combined is **50%** invested with a volatility target of **10%**, a maximum leverage of **3×** and the default 60-day window. At three rebalances the measured volatility of its holdings is different: | Measured volatility | Factor $k$ | Effective exposure | |---|---|---| | 20% | 10 / 20 = 0.5 | 25% | | 10% | 10 / 10 = 1 | 50% | | 5% | 10 / 5 = 2 | 100% | In the turbulent period the Combined halves its exposure, to 25%. Once the holdings' volatility lands exactly back on the 10% target, $k = 1$ and exposure returns to exactly **50%** — the invested portion you set, not 100%: the factor rescales *your own* invested portion, not the whole account. In the calm period it doubles that same 50% to 100%. Now raise the invested portion to **150%** with the same maximum leverage of **3×**: that asks for up to 450%, above the 300% ceiling, so the editor warns that part of the leverage will never be used — at 150% the useful maximum is 2×. The numbers are illustrative, not a suggested setting. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/backtesting/weight-drift # Weight drift Weight drift is the gap that opens between a strategy's target weights and its actual weights between two rebalances, because holdings that rise take up a growing share of the portfolio while holdings that fall take up a shrinking one. No trade causes it — it is arithmetic: each holding's value moves, the portfolio total moves with it, and every weight is just a share of that moving total. Drift is corrected at the next [rebalance](/docs/backtesting/rebalance), not continuously. **Also seen as:** drift, portfolio drift, allocation drift ## Why do actual weights drift away from their targets? A weight is a holding's value divided by the portfolio's total value, so a single price move changes every weight at once. When one sleeve rallies, its own value rises and it also lifts the total — but its numerator rises faster than the shared denominator, so its weight climbs. Every other holding's weight falls even if its price never moved, because the same value is now a smaller share of a larger total. The effect compounds the longer a strategy goes without rebalancing. ## What does weight drift do to a strategy's risk? Drift moves a strategy away from the risk profile it was designed with. The holdings that grow are, by definition, the ones that have recently risen, so drift concentrates the portfolio into whatever has just performed best — a strategy built as a balanced mix gradually behaves more like its strongest sleeve. That cuts both ways: the drifted portfolio captures more of a continuing rally in that sleeve, and more of a reversal in it. Fincanva reports what the drifted portfolio actually did; it does not tell you how much drift to tolerate. ## How does Fincanva handle it? - Between rebalances nothing is bought or sold on the strategy's own schedule, so drift accumulates until the next rebalance date. - At each rebalance the strategy trims what has grown past its target and tops up what has fallen below, returning the mix to plan. - The targets that drift are the weights the [allocation method](/docs/strategies/allocation-and-allocation-method) produced, so drift is always measured against that method's output rather than against a fixed mix. - One method treats drift as the point rather than the problem: [Floating](/docs/strategies/floating) leaves existing holdings where the market has moved them and resets them only at a realignment. - Rebalancing is scheduled by a cadence in months, not triggered by a drift threshold — how far weights may drift before they are reset follows from the cadence you choose. See [rebalance](/docs/backtesting/rebalance) and [how often your strategy rebalances](/docs/strategies/how-often-your-strategy-rebalances). ## What does it look like in practice? A strategy targets 60% in an equity ETP and 40% in a bond ETP, and starts a period with 60 and 40 on a total of 100. Over the period the equity sleeve rallies 30% while the bond sleeve slips 3%: the equity sleeve is now worth 78, the bond sleeve 38.8, and the total is 116.8. The actual weights are 78 ÷ 116.8 = 66.8% equity and 38.8 ÷ 116.8 = 33.2% bonds — the 60/40 strategy is now running roughly 67/33 without a single trade being placed. To restore the target at the next rebalance the strategy sells 7.9 of the equity sleeve (down to 60% of 116.8 = 70.1) and buys 7.9 of the bond sleeve (up to 46.7). Had the same rally happened under a slower cadence, the weights would have kept drifting past 67/33 before anything corrected them. *No drifted portfolio shown here is a recommendation to rebalance or to leave it alone.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/backtesting/withholding-tax # Withholding tax Withholding tax is tax deducted at source from a dividend before the cash ever reaches you. It is most common on foreign holdings, where the country the dividend is paid from takes its cut first, so the amount that lands in your account is the dividend **net** of the withheld portion. Fincanva applies this automatically in the simulation — you never enter a withholding rate yourself. That is what separates it from [dividend tax](/docs/backtesting/dividend-tax), the rate you *do* set: withholding happens at source before the cash arrives, dividend tax is applied to the income afterwards. **Also seen as:** dividend withholding, tax withheld at source ## How is withholding tax calculated? The dividend you receive is the gross dividend reduced by the withholding rate. $$ \text{Net dividend} = \text{Gross dividend} \times (1 - r) $$ where $r$ is the withholding rate applied at source. Because the deduction happens before you receive the cash, the simulation credits only the net amount, and the difference is the tax withheld. ## How does Fincanva handle it? - Withholding on dividends is applied automatically, based on your [tax residency](/docs/backtesting/tax-residency) and where the dividend is paid from. **There is no withholding-rate field anywhere in Fincanva** — no setting to enter one, and none to switch withholding off independently of the rest of the tax model. - The dividend credited in your results is already net of the withheld amount. - Withholding is part of the tax model, so it follows the [Taxes assumption](/docs/backtesting/taxes-toggle): with Taxes off, a dividend is credited in full, with nothing withheld. - Where [dividend tax](/docs/backtesting/dividend-tax) also applies, it is charged on the amount left after withholding, never on the gross dividend. - The withheld portion is visible per event in the positions drill-down, under "Dividends & splits", as the "Withholding tax rate" beside each dividend's gross and net figures. That panel is where you read the rate that was actually applied to a given dividend. ## What does it look like in practice? A holding pays a **100 gross dividend** from a foreign market that withholds tax at source. The withheld portion is taken before the cash reaches the simulated account, so instead of the full 100 the strategy is credited the net amount. Take an illustrative 15% withholding — a round number chosen to show the arithmetic, **not** the rate Fincanva applies to any particular holding: that is 85 received and 15 withheld. In the positions drill-down the event shows the gross dividend, the withholding, and the net that actually reached the strategy — read the rate off that panel rather than assuming one, because it depends on your residency and on where the dividend was paid from. *This describes what Fincanva models in a simulation, not tax advice for your own situation — see [Is this financial advice?](/docs/investing-theory/is-this-financial-advice#is-this-financial-advice).* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/changelog # A failed backtest can be re-run **2026-09-24** · backtesting · 2026.09 A strategy whose last backtest failed can now be sent to run again: press **Backtest** to try again, from the strategy page or the results popover, which says "The last run produced no results. Press Backtest to try again." If it still can't complete, Fincanva says so — "The run didn't restart: the engine still holds a failed result for these settings. Try again later, or change the strategy's settings" — instead of leaving the failed state as final. See [what a run's status means](/docs/backtesting/run-status). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/find-your-way-around-a-strategy-s-analysis-tabs # Find your way around a strategy's Analysis tabs A strategy's **Analysis** is split into ten tabs, each reading the same backtest from a different angle. Open a strategy, choose **Analysis**, and the tabs sit in a row under the page title. A tab your plan does not include is still there, marked beside its name with the level of the plan that includes it, drawn as bars, and opens to explain what it would show and which plan includes it. ## Before you start The strategy needs a completed backtest; before its first run, every tab explains that there are no results yet. Which tabs show your own figures depends on your plan (see below). ## Steps 1. Open the strategy, then choose **Analysis** among its sections. It opens on **Capital Growth**, the first tab. 2. Choose a tab in the row. Every tab reads the same backtest; only the angle changes. 3. To change what the figures assume, open **Simulation settings** at the top of the tab. Its **Simulation assumptions** hold the **Costs & interests**, **Taxes** and **Reinvest profits** switches. They apply to the tab you are on and are not carried to the next one: every tab opens with **Costs & interests** and **Taxes** off and **Reinvest profits** on. ## What you should see The tab you chose shows the strategy's latest backtest from its own angle, under the row of ten tabs. A tab your plan does not include carries the bars of the plan that includes it and opens on an explanation instead of figures — see [What does a tab outside my plan show?](#what-does-a-tab-outside-my-plan-show). ## What does each Analysis tab show? The ten tabs, in the order they appear, each with the page that explains it: | Tab | What it shows | Explained on | |---|---|---| | **Capital Growth** | how the invested capital grows over the whole backtest, against your benchmark | [capital chart](/docs/analysis/capital-chart), [final value](/docs/analysis/final-value) | | **Position History** | every position the strategy opened and closed — when, at what price, and why it left | [read the position history](/docs/analysis/read-a-strategy-s-position-history) | | **Performance Metrics** | return, volatility, drawdown and the rest of the performance record, year by year | [metrics explained](/docs/analysis/what-every-number-in-performance-metrics-means) | | **Monthly Returns** | month-by-month returns, so a bad stretch is a stretch and not a rumour | [monthly returns heatmap](/docs/analysis/reading-the-monthly-returns-heatmap) | | **Allocation History** | how the money was split between the strategies of a Combined, and how that split moved over time | [allocations chart](/docs/analysis/allocations-chart) | | **Components** | each strategy of a Combined judged on its own — what it contributed, and what it cost | [strategy analytics](/docs/analysis/strategy-analytics) | | **Correlations** | how the strategies of a Combined move with each other, with the Combined itself and with the big markets | [correlation matrix](/docs/analysis/correlation-matrix) | | **Start-Date Sensitivity** | the same strategy started on other days, to show how much of the result was timing | [start-date sensitivity](/docs/analysis/start-date-sensitivity) | | **Projection** | a cone of values the strategy could reach in one to five years, rebuilt from the days it has already lived — a range, not a forecast | [the Projection tab](/docs/analysis/see-where-a-strategy-could-go-with-the-projection-tab) | | **Robustness** | whether the result could be luck, and how the risk figures move under a stress scenario | [the Robustness tab](/docs/analysis/test-how-much-to-trust-a-backtest-with-the-robustness-tab) | **Allocation History** and **Components** read the parts of a [Combined](/docs/getting-started/combined), so they have something to say only on a Combined strategy. **Correlations** does both jobs: it compares the strategies of a Combined with each other, and it sets a strategy against the big markets — and that second part appears on a single strategy too. **Projection** and **Robustness** compute nothing until you ask: Projection and Robustness's backtest reliability panel each have a **Calculate** button, the stress-test panel an **Apply scenario** button, and each builds its result on request from the backtest the other tabs read. ## What does a tab outside my plan show? A tab your plan does not include **does not disappear**. It stays in the row and it still opens. Beside its name sits a small solid square with the level of the plan that includes it drawn as bars — one bar for Starter, two for Advanced, three for Ultimate; a screen reader announces it as "from Starter", or whichever plan it is. Where its charts would be, the page shows: - a small button carrying the plan that includes it: its level as bars, and its name. Pressing it opens a window headed "Unlocks with ·" followed by that plan, which says the tab is not in your plan, repeats what it shows, and offers a **Switch to** button followed by the plan's name, which opens your billing settings; - one sentence on what the tab shows — the tab's name is already on the tab, so the page repeats no title; - behind them, a faded **sample**, drawn from a demonstration strategy rather than from yours. None of your figures are hidden there: for a tab outside your plan, your strategy's figures for that tab are not computed at all. Nothing about the strategy changes, and the tab shows your own figures as soon as your plan includes it. ## Which tabs does my plan include? **Capital Growth**, **Performance Metrics**, **Monthly Returns** and **Projection** are included on every plan — Projection with a horizon and a number of scenarios your plan sets, stated on [the Projection tab](/docs/analysis/see-where-a-strategy-could-go-with-the-projection-tab). The other six depend on your plan, and each tab names the plan that includes it when you open it: **Position History** Included from Starter upwards. See [what each plan includes](/docs/account-security/what-each-plan-includes). **Start-Date Sensitivity** Included from Starter upwards. See [what each plan includes](/docs/account-security/what-each-plan-includes). **Allocation History** Included from Advanced upwards. See [what each plan includes](/docs/account-security/what-each-plan-includes). **Components** Included from Advanced upwards. See [what each plan includes](/docs/account-security/what-each-plan-includes). **Correlations** is gated by a limit Fincanva applies itself rather than by the plan matrix, so it cannot be stated here in the same form; its plan is named on the tab and on the [correlation matrix](/docs/analysis/correlation-matrix) page. **Robustness** opens on the plan that includes both of its checks, and is gated the same way; that plan is named on the tab and on the [backtest reliability](/docs/analysis/backtest-reliability) and [stress test](/docs/analysis/stress-test) pages. [What each plan includes](/docs/account-security/what-each-plan-includes) sets every plan difference side by side. ## Why do my figures say they are gross of costs? Because the **Costs & interests** or **Taxes** switch is off, and both are off by default: every tab opens with the figures gross of both, and says so beside them: "These figures are gross of trading costs and taxes." With only **Costs & interests** off the label reads "These figures are gross of trading costs.", and with only **Taxes** off "These figures are gross of taxes." Switch one on under **Simulation settings** to see the figures net of it, on that tab. The label appears whether you turned the switch off yourself or your plan does not include it; a switch your plan does not include is shown closed, marked with the name of the plan that includes it, and pressing it opens a window that names that plan. See [the costs switch](/docs/backtesting/costs-toggle) and [the taxes switch](/docs/backtesting/taxes-toggle). ## Common problems ### A strategy I own shows no figures on any tab If a strategy is outside what your plan allows — for example after a change of plan left you with more strategies than it covers — its Analysis shows why in place of the figures, on every tab, and that reason takes precedence over a single tab's plan note. See [plan compliance](/docs/backtesting/plan-compliance). ### A Public strategy shows figures on a tab my plan does not include That is expected. The plan check applies to strategies you own; a Public strategy's Analysis is not charged to your plan, so its pages show their figures whatever your plan. See [Mine and Public](/docs/getting-started/mine-public). The two exceptions are **Projection** and **Robustness**. They compute only when you ask — **Calculate**, or **Apply scenario** on the stress test — and that calculation is charged to whoever asks for it — so on a Public strategy too, their limits and the plan mark on their tab follow your plan. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/read-a-strategy-s-position-history # Read a strategy's position history The **Position History** tab of a strategy's Analysis lists everything its backtest traded, from the widest view to the narrowest: one row per symbol, then the positions taken in that symbol, then the trades that made up each position. Every level carries the same three money columns — **Gross**, **Costs** and **Net** — read the same way. ## Before you start - The strategy needs a completed backtest. - One convention to hold throughout: **Gross** is before costs, **Net** is after, and **Costs** is the difference, shown as a positive amount. See [gross vs net](/docs/analysis/gross-vs-net). **Position History** depends on your plan. If its tab shows a small square of bars beside its name, see [what a tab outside your plan shows](/docs/analysis/find-your-way-around-a-strategy-s-analysis-tabs). Included from Starter upwards. See [what each plan includes](/docs/account-security/what-each-plan-includes). ## Steps 1. Open the strategy, choose **Analysis**, then the **Position History** tab. 2. Read the four figures across the top: **Symbols traded**, **Profitable symbols**, **Best symbol**, and **Trading costs**. 3. Read the **By symbol** table: one row for every instrument the backtest ever held, with its **Gross**, **Costs**, **Net**, **Dividends** and **Total P&L** over the whole run. To find one instrument, type its ticker or name in **Search symbols…**; to rank the table differently, select a column heading. More rows load as you scroll. 4. Select a symbol's row to open it. It lists the positions taken in that symbol under **Positions** with a count, each with its **Start**, **End**, **Side** and **Max contracts** and the same money columns. 5. Select a position to open it. Its **Trade history** lists every fill, and **Dividends & splits** lists the events recorded while it was held. ## What you should see Three nested tables describing the same trades at three scales: the whole life of a symbol, one position in it, and one fill. The profit-and-loss columns — **Gross**, **Costs**, **Net**, **Dividends** and **Total P&L** — are in the currency the analysis is shown in at every level, so rows can be compared directly: your base currency on a strategy you own, and US dollars on a Public strategy, which is shown with default settings. Prices are not converted: a trade's **Actual execution price**, and the value and price of a dividend or split, are in the instrument's own currency. Each column is explained on the page that owns it: - the **By symbol** table and the four figures above it — [positions summary table](/docs/analysis/positions-summary-table); - the positions and trades inside a symbol — [positions detail drill-down](/docs/analysis/positions-detail-drill-down); - the last column, a symbol's whole result with dividends — [Total P&L](/docs/analysis/total-p-l); - why a closing trade happened, in its **Reason** column — [exit reason](/docs/strategies/exit-reason); - a position still open at the end of the run — [realized vs open P&L](/docs/analysis/realized-vs-open-p-l). ## Common problems ### Net is the same as Gross on every row The backtest charged no trading costs, which is the default. **Costs & interests** is off whenever the tab opens, so every Costs cell is zero, Net equals Gross, and the page says so: "These figures are gross of trading costs and taxes.", because **Taxes** is off by default too. Switch it on under **Simulation settings** to see costs deducted. See [the costs switch](/docs/backtesting/costs-toggle). ### Gross minus Costs is one unit away from Net Each cell is rounded on its own, so the three displayed figures can differ by one in the last digit. Nothing is missing; see [gross vs net](/docs/analysis/gross-vs-net#how-do-you-read-the-sign-of-the-costs-column). ### The table lists a company that no longer trades That is by design. A company that was delisted, acquired or taken private stays in the market data with the history it had, and a backtest can hold it for the period it actually traded — dropping it would leave only the survivors and flatter the result. See [delisted](/docs/data-methodology/delisted), and [what the data coverage figures count](/docs/data-methodology/what-fincanva-s-data-coverage-figures-count) for how such instruments are counted. ### The table reads "No symbols in this backtest." The run opened no positions at all, so there is nothing to list. Inside a symbol or a position the same situation reads "No positions for this symbol.", "No trades." or "No dividends or splits." ### Rows stop loading with "Couldn't load results." The next page of rows could not be fetched. Reload the tab to try again. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/reading-the-monthly-returns-heatmap # Reading the monthly returns heatmap The monthly returns heatmap, titled **Monthly returns**, is a grid of your strategy's return for every month, with a row per year and three summary columns — **Total**, **DD**, and **NP/DD** — on the right. This guide reads the grid, the summary columns, and the toggles that decide what the numbers include. ↗ See this in Fincanva — a strategy's Analysis, under Monthly Returns ## Before you start Run a backtest first — the heatmap fills in only after a strategy has been simulated. ## Steps 1. Open your strategy, go to **Analysis**, and select **Monthly Returns**. 2. Read one year across its row, or one calendar month down its column; the exact figure sits in each cell. 3. To change what the figures include, switch **Costs & interests**, **Taxes**, or **Reinvest profits** under **Simulation assumptions**. ## What you should see A grid of monthly returns laid out by year, shaded from weaker to stronger months, with a **Total**, **DD**, and **NP/DD** summary beside each year's row and the four period KPIs — **Avg month**, **Best month**, **Worst month**, and **Positive months** — nearby. Flipping a toggle re-labels the same grid with the pre-computed set it selects. ## How do you read the month grid? Each row is a year (**Year**) and each cell is that year-and-month's return, so you can scan a single year across or one calendar month down the columns. Four KPIs summarise the whole period alongside the grid: **Avg month**, **Best month**, **Worst month**, and **Positive months**. ## What do the Total, DD, and NP/DD columns mean? Three columns on the right summarise each year. - **Total** is the total return for the year. - **DD** is that year's maximum [drawdown](/docs/analysis/max-drawdown). - **NP/DD** is net profit divided by maximum drawdown. It is a plain, public ratio, the same figure the metrics table calls the return-to-drawdown ratio. See [return-to-drawdown ratio](/docs/analysis/return-to-drawdown-ratio). ## How do the Costs, Taxes, and Reinvest toggles change the numbers? Three toggles under **Simulation assumptions** — **Costs & interests**, **Taxes**, and **Reinvest profits** — decide what the figures include. By default **Costs & interests** is off, **Taxes** is off, and **Reinvest profits** is on. Turning one on or off switches the whole page to a version the engine pre-computed when the backtest ran; the page reads the matching set of results rather than recalculating on the spot, so the change is immediate. The current-state view of live holdings ignores these toggles — it always shows reinvested figures with costs and taxes off. ## Common problems ### The heatmap is empty or shows no months The grid needs a completed backtest with monthly results. Run the strategy first; a strategy that has never been simulated has no monthly series to plot. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/see-where-a-strategy-could-go-with-the-projection-tab # See where a strategy could go with the Projection tab The **Projection** tab of a strategy's Analysis draws a cone of values the strategy could reach over the next one to five years, starting from the last value of its backtest. Fincanva builds it by recombining the daily returns the strategy has already lived through into hundreds or thousands of possible paths, so the cone shows the spread of outcomes the strategy's own past makes plausible — never a forecast of the one that will happen. ## Before you start - The strategy needs a completed backtest. Nothing is computed when you open the tab: the projection runs only when you press **Calculate**. - A simulation stored before the Projection tab existed cannot be projected until you run the backtest again — see [Common problems](#common-problems). - The tab is on every plan; how far ahead you can project, and how many scenarios one calculation may draw, depend on your plan — see [How far ahead does my plan let me project?](#how-far-ahead-does-my-plan-let-me-project). ## Steps 1. Open the strategy, choose **Analysis**, then **Projection**. 2. Under **Horizon**, choose how far ahead to look: **1 year**, **2 years**, **3 years** or **5 years**. A year here is 252 trading days. 3. Under **Method**, choose how the paths are built: **Blocks of days**, **Single days** or **Gaussian**. **Blocks of days** is selected when the tab opens; the next section says what each one assumes. 4. Under **Scenarios**, choose how many paths to draw: 500, 1,000, 2,000 or 10,000. Beside the list, a note gives the most your plan allows. 5. Press **Calculate**. While it runs the button reads, for example, "Calculating 1,000 scenarios…"; it takes a few seconds. The result stays on screen until you change a control, or switch **Costs & interests**, **Taxes** or **Reinvest profits** under **Simulation settings**: the cone is always computed for the figures the tab is currently showing, so a change asks you to press **Calculate** again. ## What you should see Before the first calculation the chart area reads "Choose a horizon and a method, then calculate". After it, the chart continues the strategy's own curve, labelled **History**, past the line marked **today** into a fan: - the light band, **5–95%**, holds the middle 90% of the scenarios at every future day; - the darker band, **25–75%**, holds the middle half; - the line, **Median**, is the middle scenario: half end above it, half below. Above the chart the title gives the horizon ("In 3 years") and a summary ("Value today … · median …"). Under the chart a table reads the fan at the horizon, one row per percentile — the 5th, 25th, 50th, 75th and 95th — each as a **Value** and as a **Change** from today's value. Under the table the tab restates what the cone is: "This is not a forecast.", followed by how many past days it drew on and the date they run up to. One outcome in 20 lands below the light band and one in 20 above it. ## How is the projection cone built? The cone is a Monte Carlo projection: each scenario is one possible path, built by drawing daily returns from the strategy's own backtest, one day after another up to the horizon, and compounding them from today's value. Repeating that for every scenario gives a spread of end values, and at each future day the cone marks where the 5th, 25th, 50th, 75th and 95th percentiles of that spread fall. The same request on the same backtest always returns the same cone. The concept itself, and how to read its bands, is on [projection cone](/docs/analysis/projection-cone). With **Blocks of days** and **Single days**, every day in a path is a day the strategy has already lived, so no single day is worse than the worst day of the backtest — but a run of bad days can stack up into a fall deeper than any in the backtest, so the cone's lower edge is not capped by history. With **Gaussian**, days are drawn from a normal curve rather than from the history, so a single day can also be worse than any the strategy lived. Either way, a history that happened to be kind makes a cone that is kind too. The cone measures how widely the past could have played out, not what the future holds — which is why it reads "This is not a forecast." For how much of the backtest itself could have been luck, see [the Robustness tab](/docs/analysis/test-how-much-to-trust-a-backtest-with-the-robustness-tab). ## What does each projection method assume? The three methods answer "how is a future day drawn from the past?" differently, and each keeps a different property of the history. - **Blocks of days** draws runs of consecutive days rather than single days, so a calm stretch stays calm and a turbulent one stays turbulent. The tendency of markets to have volatile spells, rather than volatile days scattered at random, survives into the paths. In textbook terms it is a block bootstrap. - **Single days** draws each day independently from the history. Every day keeps its real size, but the order they came in is shuffled away, so spells of turbulence are broken up. It is the classic, independent (i.i.d.) bootstrap. - **Gaussian** draws each day from a normal distribution with the history's own average and volatility. It keeps those two numbers and nothing else: the normal curve makes very large days rarer than markets actually produce them, and knows nothing of the order the days came in. All three assume the future resembles the past; none of them can say whether it will. ## What does the number of scenarios change? More scenarios make the cone's edges steadier, not the projection truer. With few paths, the 5th and 95th percentiles rest on a handful of extreme scenarios and move noticeably if the draw changes; with many, they settle. The spread itself — how wide the cone is — comes from the strategy's history and the method, and does not grow or shrink because more paths were drawn. ## How far ahead does my plan let me project? The Projection tab is on every plan, and a plan sets two limits on it. The first is the longest horizon, counted in trading days — 252 of them make one year: Set by your plan: 252 on Free and Starter, 756 on Advanced and 1260 on Ultimate and Professional. See [what each plan includes](/docs/account-security/what-each-plan-includes). The second is the most scenarios one calculation may draw: Set by your plan: 500 on Free, 1000 on Starter, 2000 on Advanced and 10000 on Ultimate and Professional. See [what each plan includes](/docs/account-security/what-each-plan-includes). A horizon or a scenario count beyond your plan still appears in its list, marked with the plan that includes it. Choosing it sends no calculation: it opens a window that says how far your plan goes and what the next plan up allows. ## Common problems ### The tab says the projection isn't available The message reads "The projection isn't available for this simulation. If the backtest ran before the update, run it again to enable it." The projection draws on a record of daily returns that simulations stored before the tab existed do not have. Run the backtest again, then press **Calculate**. ### The cone changed after I switched costs or taxes It was recalculated for different figures. The cone starts from the value the tab is showing and draws on the daily returns behind it, so with **Costs & interests** or **Taxes** on it projects the net figures, and with them off the gross ones. See [simulation assumptions](/docs/backtesting/simulation-assumptions). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/test-how-much-to-trust-a-backtest-with-the-robustness-tab # Test how much to trust a backtest with the Robustness tab The **Robustness** tab of a strategy's Analysis holds two checks that question the backtest instead of reporting it. **Backtest reliability** resamples the strategy's history to ask whether a result this good could be luck, and how much its figures could have varied. **Stress test** replays the same history under a scenario you choose — a −20% year, doubled volatility — to show how the figures would move. Both run only when you ask, and both work on the days the strategy has already lived. ## Before you start - The strategy needs a completed backtest. A simulation stored before the tab existed has to be run again first — see [Common problems](#common-problems). - The tab and both of its checks depend on your plan: if the tab carries bars beside its name — the level of the plan that includes it — it opens to say which plan includes it. [Backtest reliability](/docs/analysis/backtest-reliability) and [the stress test](/docs/analysis/stress-test) each name the plan that includes them. ## Steps 1. Open the strategy, choose **Analysis**, then **Robustness**. The tab has two panels, **Backtest reliability** and **Stress test**; choose one. 2. For **Backtest reliability**: under **Method** choose **Blocks of days** or **Single days**, under **Resamples** choose 100 or 1,000, then press **Calculate**. While it runs the button reads, for example, "Calculating 1,000 resamples…". 3. For **Stress test**: pick one of the **Ready-made scenarios** — "A −20% year", "Double volatility", "A flat year" or "Crash: −40% and volatility ×2" — or set your own with the two sliders, **Assumed annual return** (from −50% to +50%, switched on with "Use an assumed annual return") and **Volatility multiplier** (from 0.5× to 3×; "Off = 1×"). At least one of the two must differ from normal. Then press **Apply scenario**. Each result stays until you change a control on its panel, or one of the **Simulation settings** switches; then calculate again. ## What you should see **Backtest reliability** opens on a verdict under the question "Could it be luck?" — "Probably not", "Uncertain" or "It could be luck" — with the number behind it and one sentence saying what that number means. Below it come **Years in profit**, a band showing how much the average annual return, the Sharpe and the maximum drawdown could have varied, and a **Year by year** table. The figures are explained on [backtest reliability](/docs/analysis/backtest-reliability). **Stress test** shows two gauges — **How far we bent history** and **Days that still count** — and a table, **On the strategy's historical days**, that sets the **Base** figures beside **With the scenario**: average annual return, annual volatility, and the daily VaR and CVaR at 95%. The gauges and the table are explained on [stress test](/docs/analysis/stress-test). ## How is the Robustness tab different from the Projection tab? The two tabs point in different directions. [Projection](/docs/analysis/see-where-a-strategy-could-go-with-the-projection-tab) looks forward: it builds possible futures out of the strategy's past days and shows their spread. Robustness looks back at the backtest itself: reliability asks how much of the result the same days could have produced by chance, and the stress test asks how the result depends on the kind of days the history happened to hold. Neither tab is a forecast. ## Why is the return here not the one on Performance Metrics? Because both panels report the **arithmetic** average annual return — the average daily return scaled to a year — while [Performance Metrics](/docs/analysis/what-every-number-in-performance-metrics-means) reports the compound growth rate, CAGR. The two answer different questions and differ most when returns swing widely; the app says so under the reliability band ("The return is arithmetic, so it does not match the one on the Metrics page."). In the stress test, the **Base** column is also computed differently from the Metrics page, which the table states beside it — compare **Base** with **With the scenario**, not with Performance Metrics. ## Common problems ### A panel says it isn't available for this simulation Reliability reads "Backtest reliability isn't available for this simulation. If the backtest ran before the update, run it again to enable it." Both checks draw on a record of daily returns that older simulations do not store. Run the backtest again, then calculate. ### The stress test says it couldn't calculate the scenario The message reads "We couldn't calculate this scenario." A scenario too far from anything in the strategy's history cannot be reached by reweighting its days. Try a less extreme scenario — the panel offers a button, "Soften to …", that brings the more extreme of the two settings halfway back to normal — or run the backtest again if the simulation predates the update. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/what-every-number-in-performance-metrics-means # What every number in Performance Metrics means **Performance Metrics** turns your backtest into a table of return, drawdown, volatility, worst-day and monthly-performance figures. This guide walks each row in the order the app shows it, states the convention Fincanva uses, and links to the full definition of each term. ↗ See this in Fincanva — a strategy's Analysis, under Performance Metrics ## Before you start Run a backtest first — the metrics fill in only after a strategy has been simulated. ## Steps 1. Open your strategy, go to **Analysis**, and select **Performance Metrics**. 2. Read the table one group at a time — each group has its own section below. ## What you should see The figures sit in a grouped table under the headings **Performance**, **Drawdown**, **Volatility and risk**, **Worst days · 95%**, **Monthly performance**, and **Averages**. Every group is shown on every plan. Every value is stored internally as a fraction (for example `0.153`) and formatted for display as a percentage ("15.3%"), while ratio rows such as **Sharpe** and **Return-to-drawdown ratio** are shown as plain numbers. Beside the table, a growth chart draws the strategy against its benchmark; on a strategy with an active risk condition, a band under that chart shows when it ran Risk-On and when Risk-Off — see [regime timeline](/docs/analysis/regime-timeline). ## What do the Performance rows show? The **Performance** group reports how much the strategy made and how fast. - **Total return (%)** is the whole-period return of the strategy over the backtest — the total gain or loss from the first simulated day to the last. See [total return](/docs/analysis/total-return). - **Years** is the number of calendar years between the first and last simulated date, carried to decimal months so partial years count. - **CAGR** is the compound (geometric) annual growth rate: `(1 + total return) ^ (1 / years) − 1`. It is the row shown when the **Reinvest profits** toggle is on. See [CAGR](/docs/analysis/cagr). - **AAGR** is the average (arithmetic) annual growth rate: `total return ÷ years`. CAGR and AAGR share one table slot — AAGR appears instead of CAGR when **Reinvest profits** is off. See [AAGR](/docs/analysis/aagr). ## What do the Drawdown rows show? The **Drawdown** group measures how far the strategy fell and how long it took to come back. - **Max drawdown** is the largest peak-to-trough decline of the capital curve over the period. See [drawdown](/docs/analysis/max-drawdown). - **Return-to-drawdown ratio** is the period return divided by the size of the max drawdown (`return ÷ |max drawdown|`). It is a plain, public ratio — the same figure the heatmap labels **NP/DD**. See [return-to-drawdown ratio](/docs/analysis/return-to-drawdown-ratio). - **Longest drawdown (months)** is the longest stretch, in months, the strategy stayed below a prior peak. See [longest drawdown](/docs/analysis/longest-drawdown). - **Longest recovery (months)** is the longest time, in months, it took to climb back to a prior peak after the trough. See [longest recovery](/docs/analysis/longest-recovery). ## What do the Volatility and risk rows show? The **Volatility and risk** group describes how bumpy the ride was and how the return compares to a risk-free baseline. - **Volatility** is the annualized standard deviation of returns, using the standard 252-trading-day convention (the daily figure is scaled by √252). The group heading and the KPI strip call this same quantity **Volatility**. See [volatility](/docs/analysis/volatility). - **Semideviation (downside only)** is the same measure computed on the losing days alone, annualized the same way: how much the strategy's losing days differed from one another. Between two strategies, the higher semideviation belongs to the one whose bad days were more uneven — some mild, some much worse. It is not the share of the movement that went down: because it measures the losing days around their own average, even a strategy whose ups and downs were perfectly symmetric shows a semideviation of about 0.6 times its volatility, so a figure near that is ordinary rather than a sign of mostly upward movement. It follows the same losing-days convention as the [Sortino ratio](/docs/analysis/sortino-ratio) on the **Components** tab. See [semideviation](/docs/analysis/semideviation). - **Risk-free rate** is a short-term reference interest rate drawn from real market data, matched to the period of your backtest; for any months of the window outside that data, a flat 2% a year stands in. The row shows the period average. See [risk-free rate](/docs/analysis/risk-free-rate). - **Sharpe** is the Sharpe ratio: `(annualized return − risk-free rate) ÷ annualized volatility`. The annualized-return term is CAGR when **Reinvest profits** is on and AAGR when it is off. Other views label the same figure **Sharpe ratio**. See [Sharpe ratio](/docs/analysis/sharpe-ratio). ## What do the worst-days rows show? The **Worst days · 95%** group reports how much the strategy lost on its bad days — the 5% of trading days with the worst returns. All three rows are **daily** losses written as positive numbers: "2.1%" means a loss of 2.1% in one day, and a larger number is a larger loss. - **Daily VaR · historical** is the value at risk at 95%, read straight off the backtest: on 95% of days the strategy lost less than this, and on the worst 5% it lost at least this much. - **Daily VaR · Gaussian** is the same threshold computed as if daily returns followed a normal distribution with the backtest's own average and volatility: $\text{VaR}_{95\%} = 1.645\,\sigma - \mu$, where $\sigma$ is the daily volatility, $\mu$ the average daily return, and 1.645 the number of standard deviations that leaves 5% of a normal distribution below it. See [value at risk](/docs/analysis/value-at-risk). - **Daily CVaR · historical** is the conditional value at risk, also called expected shortfall: the **average** loss across that worst 5% of days. It is never smaller than the historical VaR, because the VaR is where the worst days begin and the CVaR is how bad they are on average. See [conditional value at risk](/docs/analysis/conditional-value-at-risk). Read the two VaRs side by side: when the historical one is clearly larger than the Gaussian one, the strategy's bad days were worse than a normal distribution expects — its losses have fat tails, and the Gaussian figure understates them. A backtest with only a few hundred days rests its worst 5% on a handful of days, so these rows are rougher on a short history. ## What do the Monthly performance rows show? The **Monthly performance** group summarises the strategy month by month. - **Positive months (%)** is the share of months in the period that ended with a positive return. See [positive months](/docs/analysis/positive-months). - **Best month** and **Worst month** are the highest and lowest single-month returns over the period. See [best month and worst month](/docs/analysis/best-month-and-worst-month). ## What do the Averages rows show? The **Averages** group reports simple averages of the return series. **Monthly average** is the plain average of the monthly return series, and **Yearly average** is the plain average of the annual return series. See [monthly and yearly average](/docs/analysis/monthly-and-yearly-average). ## How are these numbers annualized? Every annualized figure on this page shares one basis: Fincanva scales volatility with the √252 trading-day convention and measures years as geometric calendar years carried to decimal months. Values are stored as fractions and formatted for display, and the risk-free baseline is a real, period-matched market series rather than a fixed value — except for months outside that series, where a flat 2% a year stands in. ## Metrics shown in other views Some figures live on other analysis surfaces rather than the main metrics table. On a Combined, the **Components** tab's **Each strategy, against the Combined** block adds a [Sortino ratio](/docs/analysis/sortino-ratio), [tracking error](/docs/analysis/tracking-error), and [information ratio](/docs/analysis/information-ratio) for each of its strategies. The start-date sensitivity view reports [average pain](/docs/analysis/average-pain). On a Combined, the same **Components** tab opens with [contribution analytics](/docs/analysis/contribution-analytics), which splits the Combined's return, volatility, Sharpe and daily VaR among its strategies. The [stress test](/docs/analysis/stress-test) on the **Robustness** tab recomputes the daily VaR and CVaR under a scenario, and [backtest reliability](/docs/analysis/backtest-reliability) shows how much the return, the Sharpe and the maximum drawdown could have varied. Two textbook risk measures are worth knowing even though Performance Metrics does not display them today: [beta](/docs/analysis/beta), which appears in the Beta Neutral allocation method rather than as a metric, and [alpha](/docs/analysis/alpha). The [Fincanva score](/docs/analysis/fincanva-score) summarises overall quality — see [What the Fincanva score is and how to read it](/docs/analysis/what-the-fincanva-score-is-and-how-to-read-it). ## Common problems ### The tab reads "No results yet" The strategy has no completed backtest, and the tab says so: "Backtest this strategy to generate its metrics." Select **Backtest** and the table fills in once the backtest finishes. ### The table shows AAGR where I expected CAGR **Reinvest profits** is off in the tab's **Simulation assumptions**. CAGR and AAGR share one row, and AAGR takes it while reinvesting is off — switch **Reinvest profits** on to read CAGR. The same switch decides which of the two the **Sharpe** row uses. ### The worst-days rows and Semideviation read "n/a" The simulation was computed before those rows existed, and it does not carry them. A value that could not be computed reads "n/a", never 0% — a 0% loss would claim a safety the figure does not show. When all four read "n/a" on a strategy you can run, a notice above the table says "Some metrics can't be computed for this simulation. If it ran before this update, rerun it to get them." with a **Rerun** button; press it, and the rows fill in when the new backtest finishes. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/what-the-fincanva-score-is-and-how-to-read-it # What the Fincanva score is and how to read it The Fincanva score is a single quality score that rates your strategy on a normalized scale, with its benchmark shown alongside for comparison. It appears in **Performance Metrics** as **"Fincanva score"**, carries a **Beta** badge, and is a research signal — not a rating of what will happen to your money. ## How does the Fincanva score work? The Fincanva score rates your backtest's overall quality as a single number derived from the strategy's own results — the benchmark is scored the same way and displayed next to it for comparison, but it is not subtracted from your score. Because the scale is normalized, it lets you weigh strategies of different lengths and styles on the same scale. Fincanva does not publish how the score is calculated — the dimensions are named below, but their weighting and the formula that combines them are deliberately not disclosed. For the one-line definition, see [Fincanva score](/docs/analysis/fincanva-score). ## How do you read the Fincanva score? The score is shown as a gauge on a 0–5 scale, labelled with the score and its maximum — for example "Fincanva score 3.2 out of 5" — with a quality tier of **Strong**, **Fair**, or **Weak**. The card also shows the benchmark's own score, so you can read the two side by side. A higher tier means the backtest scored better than a lower one. ## Which dimensions does the Fincanva score weigh? Six, each shown below the gauge with its own reading on the same 0–5 scale. The labels are the ones the card itself displays: | Dimension | What it looks at | |---|---| | **CAGR / AAGR** | the strategy's growth rate — see [CAGR](/docs/analysis/cagr) | | **Max DD** | the worst peak-to-trough fall — see [max drawdown](/docs/analysis/max-drawdown) | | **Std Dev** | how much the returns varied — see [volatility](/docs/analysis/volatility) | | **Sharpe** | return per unit of risk — see [Sharpe ratio](/docs/analysis/sharpe-ratio) | | **Pos Months** | the share of months that ended up rather than down | | **Recovery Speed** | how the strategy came back out of its drawdowns — see [longest recovery](/docs/analysis/longest-recovery) | Naming the six is as far as this goes: **how each dimension is turned into its 0–5 reading, how the six are weighted, and how they combine into the headline score are not published** (see below). Two dimensions are worth reading with their direction in mind — a *high* Max DD or Std Dev reading is a good result, because each dimension is scored so that higher is better, not so that higher is more of the raw metric. ## Why isn't the formula published? The dimensions above are named, but the exact way the Fincanva score is calculated from them is proprietary and intentionally left undocumented — not even support can share it. Reading the tier, the six dimensions and the benchmark comparison is enough to use it. A high score also does not tell you to buy, hold, or sell anything — it summarises historical quality, not a recommendation, and it does not guarantee any future result. ## Limits and edge cases The score is marked **Beta**, so its presentation may still change. The **Beta** badge here refers to the feature's beta status — it is unrelated to [beta](/docs/analysis/beta), the finance measure. Before a strategy has enough simulated history to score, the card shows "No score available yet" instead of a gauge. A strong score reflects past, simulated performance only; it is not a promise or forecast of future results. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/aagr # AAGR AAGR, the arithmetic annual growth rate, is a strategy's total return divided by the number of years in the backtest, with no compounding applied. It is the reinvest-off counterpart to [CAGR](/docs/analysis/cagr): the two share one row on the metrics view, and the **Reinvest profits** toggle decides which one is shown. Because AAGR ignores compounding, it usually reads higher than CAGR over multi-year gains. **Also seen as:** arithmetic annual growth rate, simple annualised return, non-compounded annual return ## How is AAGR calculated? AAGR spreads the whole-period return evenly across the years, as a simple average with no year-on-year compounding. $$ \text{AAGR} = \frac{\text{total return}}{\text{years}} $$ where: total return is the whole-period gain as a fraction, and years is the length of the backtest in calendar years. ## How does Fincanva handle it? - AAGR fills the annualised-return slot on the metrics view when **Reinvest profits** is off; with it on, the same slot shows CAGR. - It is a plain arithmetic mean — the same total return over the same length always gives the same AAGR, regardless of the path taken to get there. - It is expressed as a percentage and can be negative when a strategy loses money over the period. ## What does it look like in practice? Take the same run that grows 10,000 into 16,100 over 5 years — a total return of +61%. AAGR divides that evenly: 61% ÷ 5 = 12.2% per year. CAGR on the same run is about 10% per year. The gap — 12.2% versus 10% — is the effect of compounding: AAGR counts each year's gain against the original stake, while CAGR compounds it on the growing balance. *No annual growth rate is a rate you can expect to repeat.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/adjusted-beta # Adjusted beta Adjusted beta is a [beta](/docs/analysis/beta) estimate that has been pulled part of the way toward 1.0 before it is used. It measures the same thing as beta — how much one series moves for each unit move in a reference series — but because a beta fitted on a finite stretch of past returns is measured with error, and because betas far from 1 have historically drifted back toward 1 in later periods, the adjustment treats an extreme estimate as partly noise and shrinks it toward the market. An adjusted beta is therefore always closer to 1.0 than the raw estimate it came from, and never further away. Fincanva applies the standard **Blume adjustment**: 0.67 of the fitted beta plus 0.33 of 1.0. **Also seen as:** shrunk beta, shrinkage-adjusted beta, Blume beta ## Why is a raw beta estimate adjusted? A raw beta is adjusted because it is a *statistical estimate*, not a measured constant, and it carries two problems the adjustment addresses at once. The first is sampling error: fit a beta on a short window and the figure partly reflects which weeks happened to fall inside the window. The second is mean reversion: an instrument whose measured beta was 1.8 over one period has, on average, come in lower than 1.8 over the next — the market's beta is 1.0 by definition, and estimates far from it tend to move back toward it. Shrinkage handles both by taking a weighted blend of the fitted beta and 1.0: $$ \beta_{\text{adj}} = w \cdot \beta_{\text{raw}} + (1 - w) \cdot 1.0 $$ where: $\beta_{\text{raw}}$ is the beta fitted on historical returns, $w$ is a weight between 0 and 1 deciding how much of the fitted estimate is kept, and 1.0 is the market's beta by definition. A $w$ near 1 keeps almost all of the raw estimate; a smaller $w$ pulls harder toward the market. The shorter and noisier the estimation window, the stronger the case for a smaller $w$. ## Which adjustment does Fincanva use? Fincanva uses the **Blume adjustment** — the standard shrinkage that keeps 0.67 of the fitted beta and puts the remaining 0.33 on the market's 1.0. $$ \beta_{\text{adj}} = 0.67 \cdot \beta_{\text{raw}} + 0.33 \cdot 1.0 $$ It is named after Marshall Blume, who measured in the early 1970s that betas estimated in one period drifted toward 1 in the next, and proposed a fixed blend as the correction; Fincanva's weights are 0.67 on the fitted beta and 0.33 on 1.0. The weights are constants: they do not change with the instrument, the window, or how noisy the fit was. That is the trade the Blume adjustment makes — a fixed, predictable correction instead of one tuned per estimate. ## How does a raw beta of 1.6 become about 1.4? Suppose a strategy's returns, regressed on a reference market, give a raw beta of 1.6 — the strategy moved about 1.6% for each 1% move in the market over the window measured. Applying the 0.67/0.33 blend: $$ 0.67 \times 1.6 + 0.33 \times 1.0 \approx 1.4 $$ So a raw 1.6 becomes an adjusted 1.4. Note what the adjustment does and does not change: the ranking survives (a raw 1.6 still ends up above a raw 1.1, which becomes about 1.07), but the spread narrows — every estimate moves toward the middle, and the most extreme ones move most. A raw beta already at 1.0 is unchanged. {/* VISUAL: svg-diagram — number line from 0 to 2 with a tick at 1.0 labelled "market", raw beta estimates as open dots and adjusted positions as filled dots, arrows showing every dot move toward 1.0 and the extreme ones move furthest, each arrow covering 0.33 of the distance — tracked in VISUAL_BACKLOG */} ## Where does adjusted beta appear in Fincanva? Adjusted beta appears in Fincanva as a toggle on the **Beta Neutral** allocation method, labelled **Adjusted beta** (and **Use Adjusted Beta** in the editor's compact layout), and it is on by default. Its hint states that it "Shrinks the OLS beta estimate toward 1.0" and "Stabilises estimates on short windows" — OLS being ordinary least squares, the standard regression fit. With the toggle on, the method works from adjusted betas; with it off, it works from the raw fitted betas. The same pull has a cost, and the hint names it: because every beta is pulled toward 1.0, a genuinely negative or near-zero beta — an inverse ETF, or gold in some periods — can come out positive, so the hint says to turn the toggle off for instruments like those. That matters because Beta Neutral builds its book against a **Target beta** you set — its hint reads "0.00 = market-neutral. Positive = net long exposure; negative = net short exposure." — measured with a **Benchmark instrument** whose hint reads "The portfolio's beta is computed against this instrument." The toggle decides which beta estimates that comparison rests on, adjusted or raw, so turning it off can change the allocation the method produces from the same instruments and the same target. Fincanva does not display the individual beta figures involved, only the resulting allocation. The term also belongs to the [correlation matrix](/docs/analysis/correlation-matrix), where an adjusted beta sits beside each pair of series — though Fincanva does not ship a correlation view today, so that is where the concept applies rather than a surface you can open. ## How do you read an adjusted beta? Read an adjusted beta the same way as a beta — above 1.0 means amplified moves relative to the reference, below 1.0 means dampened, negative means moving the other way — but read it as a *deliberately conservative* version of the raw figure. Two consequences follow. Extreme readings are rarer, so an adjusted beta of 1.5 implies a raw estimate that was higher still. And two instruments whose raw betas differed sharply look more alike after adjustment, so an adjusted beta is a weaker tool for separating a very high-beta holding from a merely high-beta one. Neither figure is a forecast: both describe a past window, and both change with the window and the reference series chosen. Fincanva does not tell you what beta to hold — see [Is this financial advice?](/docs/investing-theory/is-this-financial-advice). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/allocations-chart # Allocations chart The allocations chart is the view on a [Combined](/docs/getting-started/combined)'s **Allocation History** page that plots one series per strategy inside that Combined across the whole simulated period, so you can see how the capital was divided and which strategy produced which part of the result. It answers "which strategy carried the year?" — a question the Combined's single equity curve deliberately hides, because that curve is the total. **Also seen as:** allocation history, the allocations view Each piece inside a Combined is a **strategy**; the app's table column for them is headed **Strategy**. ## What do the three views show? One segmented control switches between three readings of the same already-computed data. The chart's title changes to match the active view. - **Capital** stacks each strategy's capital in your base currency, so the stack's outline is the Combined's own value and each band inside it is one strategy's share of that money. The axis is titled **Capital**. This is the "where is my money" reading. - **Weights** stacks each strategy's target weight as a percentage, normalised so the stack always fills 100%. The axis is titled **Weight (%)**. It is drawn as steps rather than a smooth line, because a weight holds flat between rebalances and then snaps to its new value on the [rebalance](/docs/backtesting/rebalance) date — the step edges are the rebalances. Before the first rebalance the weights are zero, so the area starts empty. - **Net profit** drops the stacking and draws one line per strategy of its cumulative net profit, with the Combined's own profit line — labelled **Combined** — overlaid on top. The axis is titled **Net profit**. This is the "who earned it" reading. Because **Weights** is normalised to 100% it shows *shape* and says nothing about size: a Combined that halved in value looks identical in **Weights** and very different in **Capital**. Read the two together, or read **Capital** when the question involves amounts. ## What is the Current allocation panel? Beside the chart sits a table titled **Current allocation** — the latest state rather than the history — with a row per [strategy inside the Combined](/docs/getting-started/strategy-in-a-combined) and four columns: **Strategy**, **Weight**, **Capital** and **Profit**. Each row carries a small colour square matching that strategy's series in the chart, and hovering a row lights up its series while dimming the others; hovering a series in the chart lights up its table row the same way. The **Profit** column is coloured by sign and is a money figure, in the same sense as [total P&L](/docs/analysis/total-p-l) on the positions tables. Four KPIs sit above: **Combined value**, **Net profit**, **Largest allocation** — which names the strategy and its weight — and **Last rebalance**. ## How does Fincanva handle it? - **The allocation history page is included from the Advanced plan.** It reads a Combined, and Combined strategies themselves start at Advanced, so Free and Starter never reach it; Advanced, Ultimate and Professional include it. See [what each plan includes](/docs/account-security/what-each-plan-includes). - The view opens on **Capital**, and switching view is a display change over data already fetched: it does not re-run anything. - Series colours are fixed per strategy and shared with the table's swatches, so a strategy keeps the same colour across all three views. - A period selector above the chart narrows the visible date range. - The three simulation assumptions — **Costs & interests**, **Taxes** and **Reinvest profits** — change which set of figures the page reads. - The page fills in only after a completed run; before that it reads "No results yet" and "Backtest this strategy to generate its allocation history." ## What does it look like in practice? A Combined holds three strategies, each targeting a third of the capital. Open **Weights** and the three bands sit at roughly 33% each, each band's edge stepping slightly at every rebalance date as the weights are pulled back to target after drifting. Now switch to **Net profit** to find out which one carried the year. The **Combined** line ends at +42,000 for the period. Below it, one strategy's line ends at +38,000, the second at +9,000, and the third at −5,000. So nearly all of the Combined's profit came from a single strategy, while another lost money — a fact that is completely invisible in **Weights**, where all three look nearly identical, and invisible again on the Combined's own equity curve, which only shows the +42,000. Finally check **Capital**: because the Combined rebalances back to equal thirds, the winning strategy's band is *not* three times the size of the others at the end. Rebalancing keeps taking money out of the strategy that grew and putting it into the ones that did not, which is why weight and profit tell two different stories. ## What counts as a good split? The chart reports what the Combined's own allocation rules produced; it does not rank the strategies inside it. A strategy contributing most of the profit is not thereby the "right" one to hold more of, and one contributing a loss is not thereby the wrong one — a Combined is assembled so that its pieces behave differently from each other, so a piece that lags in one period is often the piece that behaves differently in another. What the chart does tell you cleanly is **concentration of outcome**: whether a result rested on one strategy or was spread across them. A result that came from one strategy is a result whose repeat depends on that strategy alone. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/alpha # Alpha Alpha is the part of a strategy's return that its market exposure does not explain: what is left after subtracting the return the strategy's [beta](/docs/analysis/beta) alone would be expected to produce in the market that period. Positive alpha means the strategy returned more than its market exposure accounts for; negative alpha means less. **Fincanva does not currently display an alpha metric anywhere in the app** — the term is documented here as standard finance vocabulary you may meet elsewhere, not as a number you can read off a Fincanva result. **Also seen as:** Jensen's alpha, risk-adjusted outperformance ## How is alpha calculated? Alpha is a strategy's realised return minus the return its beta and the market's return imply it should have earned. $$ \alpha = R_p - \left[\, R_f + \beta \cdot (R_m - R_f) \,\right] $$ where: $R_p$ is the strategy's return over the period, $R_f$ is the [risk-free rate](/docs/analysis/risk-free-rate) over the same period, $R_m$ is the market's (or [benchmark's](/docs/getting-started/benchmark)) return, and $\beta$ is the strategy's beta measured against that market. The bracket is the *expected* return given the exposure taken; alpha is the residual. Every input is an estimate over a chosen window, so alpha inherits the sensitivity of all of them — most of all beta's. ## How is alpha different from excess return? Alpha subtracts a *beta-scaled* benchmark return; [excess return](/docs/analysis/excess-return) subtracts the benchmark return itself. That difference matters whenever a strategy's market exposure is not one-for-one with its benchmark. Take a strategy with a beta of 1.5 in a year when the market returned +10% and the risk-free rate was 0%: its exposure alone implies +15%. If it returned +13%, its excess return is +3pp — it beat the benchmark — while its alpha is −2pp, because it beat the benchmark by less than its extra market exposure accounts for. Excess return asks "did it beat the benchmark?"; alpha asks "did it beat what its exposure explains?". {/* VISUAL: chart — scatter of strategy return against market return with the beta slope drawn through it and one point's vertical distance from the line annotated as alpha; visibly illustrative, not a product screenshot — tracked in VISUAL_BACKLOG */} ## What counts as a good value? Positive alpha over a period means the strategy's return exceeded what its market exposure explains for that period, on that benchmark, with beta estimated over that window — and every one of those qualifiers can flip the sign. Change the benchmark and alpha changes; measure beta over a different window and it changes again; a stretch long enough to look convincing can still be chance, since alpha carries all the estimation error of the inputs it is built from. Alpha describes a past window and is not a forecast of a future one. Fincanva does not tell you whether a strategy's figures are good enough to act on — see [Is this financial advice?](/docs/investing-theory/is-this-financial-advice). ## Does Fincanva show alpha? No. Fincanva does not report alpha in **Performance Metrics**, in a strategy's list row, or anywhere else in the app today. The comparison-to-benchmark figures Fincanva does report are [excess return](/docs/analysis/excess-return) (the plain difference in returns) and, for a strategy inside a Combined, [tracking error](/docs/analysis/tracking-error) and [information ratio](/docs/analysis/information-ratio) against its parent Combined. See [What every number in Performance Metrics means](/docs/analysis/what-every-number-in-performance-metrics-means) for the metrics that do exist. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/annualization # Annualization Annualization converts a return earned over a whole period into an equivalent per-year rate, so results measured over different lengths of time can be compared on one yearly scale. A +30% gain means very different things over one year versus over ten; annualizing restates each as "per year" so the two are directly comparable. This page covers the *operation* and the conventions Fincanva applies to it, including how volatility is annualized; the annualized return figure it produces for a strategy is [CAGR](/docs/analysis/cagr), or [AAGR](/docs/analysis/aagr) when profits are not reinvested. **Also seen as:** annualisation ## How is a return annualized? The standard method is geometric: find the constant yearly rate that, compounded over the number of years in the period, reproduces the whole-period return. $$ \text{annualized rate} = (1 + \text{total return})^{1/\text{years}} - 1 $$ where: [total return](/docs/analysis/total-return) is the whole-period gain as a fraction, and years is that period's length in calendar years. ## How does Fincanva handle it? - Fincanva annualizes a strategy's return geometrically over the calendar years of the backtest — this is the [CAGR](/docs/analysis/cagr) figure. - With **Reinvest profits** off, the annualised-return slot instead uses the simple arithmetic form, total return ÷ years — the [AAGR](/docs/analysis/aagr). - Volatility is annualized separately, using the standard 252-trading-day convention (×√252), so a per-period dispersion becomes a per-year figure. ## What does it look like in practice? A strategy gains +10% over 18 months. Because 18 months is 1.5 years, the annualized rate is (1 + 0.10)^(1/1.5) − 1 ≈ 0.066, or about 6.6% per year. Compounding 6.6% a year for a year and a half does produce roughly the same +10%, which is what annualization restates as a comparable yearly number. *A per-year rate is not a rate you can expect to repeat.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/average-pain # Average pain Average pain is the average, across the start months a strategy is tested from, of the deepest it fell below the value it had on each start date. Where [drawdown](/docs/analysis/max-drawdown) measures the drop from a running peak, pain is anchored to the day you began — how far underwater the strategy went relative to the value it started that run with. Averaging that across every start month tested gives a single figure for the typical worst pain a start date put you through. **Also seen as:** Avg pain ## How is average pain calculated? For one start month, its pain is the deepest fall from the value the strategy held on that start date to the lowest value it reached before the holding window ended. $$ \text{pain} = \frac{\text{lowest value in the window} - \text{value at the start date}}{\text{value at the start date}} $$ where: the lowest value is the deepest point reached between the start date and the end of that holding window, and the figure is zero when the strategy never closed below where it began. Average pain is the mean of this figure across every start month tested for a given window length. ## What counts as a good value? A pain closer to zero is generally preferable: it means a typical start date left the strategy less far below the value it began with. It describes the depth of the worst dip per start date, not how long the strategy stayed underwater, so read it next to a duration measure such as [longest drawdown](/docs/analysis/longest-drawdown) for the fuller picture. ## How does Fincanva handle it? - Average pain appears on the [start-date sensitivity](/docs/analysis/start-date-sensitivity) view as the **Avg pain** row of the summary-statistics table, alongside the CAGR rows for the same set of start months, one column per holding window. - It is anchored to the value the strategy held on each start date, so unlike [max drawdown](/docs/analysis/max-drawdown) — which is measured from a running peak — the two figures are not comparable. - It is reported as a negative percentage, and it is zero only when no start month ever closed below where it began. - It is a depth measure only — it says nothing about how long the strategy stayed below its start value. ## What does it look like in practice? A strategy is started at the beginning of one month and, before that holding window ends, its value falls as low as 28% below where it began. That start month's pain is −28%. Average pain takes that start-anchored figure for every start month tested at the same window length and averages them, so one unlucky start's deep dip is balanced against the shallow dips of the others. *No pain figure is a limit on future losses.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/backtest-reliability # Backtest reliability Backtest reliability is the panel of a strategy's **Robustness** tab that asks how much of a backtest's result could be chance. It resamples the strategy's own daily returns a hundred or a thousand times, depending on the plan, and reports three things: how often a strategy with no edge over cash would look as good as this one (the "Could it be luck?" verdict), how widely the average annual return, the Sharpe and the maximum drawdown could have come out, and how many individual years were in profit. It is a statement about the past the backtest covers, never about what the strategy will do next. **Also seen as:** bootstrap test, p-value, backtest significance, bootstrap confidence interval ## What does "Could it be luck?" measure? The verdict answers one question: if this strategy had no edge at all over cash, how often would its history still produce a [Sharpe ratio](/docs/analysis/sharpe-ratio) as high as the one the backtest shows? That share is a p-value, printed as "p = …", and the sentence under it says it in words: "A strategy with no edge over cash and the same volatility would look this good in … of cases." The verdict reads that share on three rungs: | Share of no-edge histories that look this good | Verdict | |---|---| | below 5% | **Probably not** | | 5–20% | **Uncertain** | | 20% and above | **It could be luck** | In prose: a low share means a no-edge strategy rarely matches this result, so luck is an unlikely explanation; a high share means an edgeless strategy often does, so the result proves little. The p-value is never exactly zero. ## What does the verdict leave out? It tests **one** strategy, as if it were the only one you ever tried. Tried twenty variants and kept the best? Among twenty strategies with no edge, one will often clear the 5% rung by chance alone, and this verdict cannot see the other nineteen — the app says so under it: "It speaks about the past, not about what the strategy will do, and it does not account for how many variants you tried before this one." That is [data-snooping bias](/docs/investing-theory/data-snooping-bias), and its cousin [overfitting](/docs/investing-theory/overfitting) is the reason a strong verdict on a heavily tuned strategy deserves less weight than the same verdict on a strategy set up once. ## How does resampling show how much the figures could have varied? Resampling rebuilds the backtest's history many times by drawing its own days again, with replacement, and recomputes the figures on each rebuilt history. The spread of those recomputed figures is what the panel draws under **How much they could have varied · 5–95% band**: for **Average annual return (arithmetic)**, **Sharpe** and **Maximum drawdown**, a band from the 5th to the 95th percentile of the resampled values, with a dot for the backtest's own value. This is the textbook bootstrap confidence interval. The dot can fall outside the band — the app notes it — and does so most often for the maximum drawdown, because drawing days again breaks up the long losing runs a drawdown is made of. The return is the **arithmetic** average annual return, the average daily return scaled to a year, so it does not match the compound growth rate, [CAGR](/docs/analysis/cagr), on Performance Metrics. Two methods decide how days are drawn: **Blocks of days** draws runs of consecutive days, keeping calm and turbulent spells together; **Single days** draws each day on its own. More resamples make the band's edges steadier; they do not make the backtest more trustworthy. ## What is the average annual return (arithmetic)? The **Average annual return (arithmetic)** is the average daily return of the strategy multiplied by 252, the trading days in a year. It is the return the Robustness tab and contribution analytics use, and it is a different figure from both the compound growth rate, [CAGR](/docs/analysis/cagr), and the [AAGR](/docs/analysis/aagr) on Performance Metrics. $$ \text{average annual return (arithmetic)} = 252 \times \text{average daily return} $$ where the average is the plain mean of the backtest's daily returns. Because it averages returns instead of compounding them, it ignores the drag volatility puts on growth: a day at −10% followed by a day at +10% averages to 0%, yet leaves the capital 1% lower. The higher the volatility, the wider that gap, so on a very volatile strategy the arithmetic figure can be **positive while the strategy lost money** over the period. Read it as the strength of the average day, not as what the capital did. ## How does Fincanva handle it? - It runs on request, from the **Robustness** tab: choose a method and a number of resamples — 100 or 1,000 — and press **Calculate**. Nothing is computed before that. - **Years in profit** counts how many of the years in the **Year by year** table had an average daily return, scaled to a year, above zero — "7 of 10", say. In a very volatile year that can disagree with the sign the same year shows on Monthly Returns, which compounds. - The **Year by year** table gives each calendar year's days, average annual return, Sharpe and maximum drawdown. Each year's Sharpe uses that year's own [risk-free rate](/docs/analysis/risk-free-rate). A year needs at least 40 trading days to appear; if none has, the table is replaced by a note saying so. - The figures follow the tab's **Simulation settings**: with **Costs & interests** or **Taxes** on, the check runs on the net returns. - A simulation stored before the panel existed has to be run again first; until then the panel says it isn't available. - The same request on the same backtest always returns the same result. How many resamples one calculation may use is set by your plan, and a plan that allows none does not include the panel: Set by your plan: 0 on Free and Starter, 100 on Advanced and 1000 on Ultimate and Professional. See [what each plan includes](/docs/account-security/what-each-plan-includes). A number of resamples beyond your plan stays in the list, marked with the plan that includes it, and choosing it opens a window instead of calculating. ## What does it look like in practice? A strategy's backtest shows a Sharpe of 0.9 over twelve years. The panel returns p = 0.03 — "Probably not": only 3 in 100 no-edge histories reach a Sharpe of 0.9. The band for the average annual return runs from 4% to 14% around a backtest value of 9%, and **Years in profit** reads 9 of 12. Read together: the result is unlikely to be pure chance, but the same days could plausibly have produced anything from a modest 4% to a strong 14% a year. Now suppose the strategy was the best of thirty variants: the 3% no longer means much, because among thirty edgeless tries it is more likely than not that at least one lands at 3% or below. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/best-month-and-worst-month # Best month and worst month Best month and worst month are the highest and lowest single-month returns a strategy recorded over the backtest period. The [metrics table](/docs/analysis/metrics-table) lists them as two separate rows, "Best month" and "Worst month", in the **Monthly performance** group. Each is one month out of the run — the single strongest and the single weakest — so together they mark the extremes of the monthly return series without you having to scan every month. **Also seen as:** biggest monthly gain, biggest monthly loss, monthly extremes ## How are best month and worst month measured? Both are read off the same month-by-month return series: best month is the largest value in that series and worst month is the smallest. No averaging or smoothing is involved, and neither figure is combined with its neighbours — a month that gained 12% is the best month even if the months either side of it lost ground. ## Is the worst month the same as max drawdown? No — the worst month is one calendar month's return, while [max drawdown](/docs/analysis/max-drawdown) is the largest peak-to-trough fall of the capital curve. A drawdown can start mid-month, run across several months, and end mid-month, so it is usually deeper than the worst single month and always measured from a peak rather than from a month boundary. A strategy can have a mild worst month and a severe max drawdown if the losses were spread out; how long such a decline lasted is [longest drawdown](/docs/analysis/longest-drawdown). ## What counts as a good value? The pair is read as a range rather than as two separate scores: a narrow gap between best and worst means month-to-month outcomes clustered together, and a wide gap means they were spread far apart, which is the same behaviour [volatility](/docs/analysis/volatility) puts into a single annualized number. A high best month is not evidence of a better strategy on its own — a single outsized month can lift a whole run's [total return](/docs/analysis/total-return) while the other months contributed little, and the [monthly average](/docs/analysis/monthly-and-yearly-average) beside it is what shows whether the rest of the period pulled its weight. ## How does Fincanva handle it? - Both appear as rows in the **Monthly performance** group of the metrics table, labelled "Best month" and "Worst month", as percentages to one decimal place and coloured by sign. - The monthly returns view repeats them as KPIs using the same two labels. - They come from the same month-by-month series the [monthly returns heatmap](/docs/analysis/reading-the-monthly-returns-heatmap) displays, so you can find the two months on the grid. - Each is a single calendar month of the simulated period — never a rolling 30-day window and never a run of consecutive months. ## What does it look like in practice? A ten-year backtest reports Best month +12.0% and Worst month −18.0%. Those are two individual months out of roughly 120, and the 30-percentage-point spread between them tells you monthly outcomes ranged widely. The −18.0% month is not the run's max drawdown: if the strategy also fell in the month before and the month after, the peak-to-trough decline around that month is deeper than 18%. Equally, the +12.0% month may be the reason the run's total return looks strong, which is why the monthly average is worth reading next to it. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/beta # Beta Beta measures how strongly an instrument or a strategy moves relative to the overall market: a beta of 1 moves in line with the market, a beta above 1 amplifies the market's swings, and a beta below 1 dampens them. Beta describes **exposure**, not quality — it says how much of the market's movement you carry, never whether the outcome was good. A negative beta means the instrument tends to move in the opposite direction to the market. The risk beta measures is called systematic risk, or market risk. **Also seen as:** market beta ## Why does Fincanva show two different things called "Beta"? Two unrelated meanings share the word "Beta" in the app, and telling them apart is the first thing to get right. - **Beta the metric** — the market-sensitivity number described on this page. It appears as the **Beta** column in screener results and as the quantity the **Beta Neutral** allocation method targets. - **The "Beta" badge** — a small badge reading "Beta" sitting next to the **Fincanva score** card title. It marks that feature as being at a beta stage of development. It is a maturity label, not a number, and it carries no beta value at all. See [Fincanva score](/docs/analysis/fincanva-score). There is no standalone beta row in the metrics table: **Performance Metrics** reports volatility and drawdown-based risk measures instead, and beta lives on the screener, on the allocation methods, and on a Combined's correlation tables. See [what every number in Performance Metrics means](/docs/analysis/what-every-number-in-performance-metrics-means) for what that table does report. ## How is beta calculated? Beta is the covariance between the asset's returns and the market's returns, divided by the variance of the market's returns. $$ \beta = \frac{\operatorname{Cov}(r_a,\; r_m)}{\operatorname{Var}(r_m)} $$ where: $r_a$ is the asset's (or strategy's) return over each period, $r_m$ is the market's return over the same periods, $\operatorname{Cov}$ is covariance and $\operatorname{Var}$ is variance. Equivalently, beta is the slope of a regression line fitted to the asset's returns against the market's returns — which is why a beta of 1.5 reads as "1.5 units of movement for every 1 unit of market movement". Because beta is a slope and not a spread, it is a different measure from [volatility](/docs/analysis/volatility): volatility says how much something moves, beta says how much of that movement tracks the market. ## Where does Fincanva use beta? - **Screener results** carry a **Beta** column, so you can sort or read a candidate instrument's market sensitivity alongside its other figures. - **Beta Neutral** is an allocation method whose description reads "Long + short legs sized to target a portfolio beta". Its **Target beta** field carries the hint "0.00 = market-neutral. Positive = net long exposure; negative = net short exposure." — so the method uses beta as an input you set, not as a result it reports. See [Beta Neutral](/docs/strategies/beta-neutral). - Beta is measured against a **Benchmark instrument** you choose rather than a fixed index. That field's hint reads "The portfolio's beta is computed against this instrument." - A **Use Adjusted Beta** switch is available on the same method, with the hint "Shrinks the OLS beta estimate toward 1.0 (Blume adjustment — Bloomberg's \"Adjusted Beta\"). Stabilises estimates on short windows, but pulls every beta toward 1.0, so a negative or near-zero beta can turn positive — turn it off for inverse ETFs or gold." [Adjusted beta](/docs/analysis/adjusted-beta) is also the second reading offered beside a Combined's [correlation matrix](/docs/analysis/correlation-matrix), where each strategy carries one against each market factor. - The **In-sample** field, in the **Leverage & calculation window** section, sets how much history the estimate reads. Its hint reads "Historical window used by the active method for volatility, correlation, beta, and similar calculations. Default 12." ## How does Fincanva handle it? - Beta is always relative to something, and what it is relative to depends on the surface: the reference instrument the allocation method is pointed at, or the market factor whose column you are reading in a correlation table — never a universal "the market". - The screener's **Beta** column is a per-instrument figure, not a figure for your strategy. - The metrics table has no beta row today: a strategy-level beta is not a performance metric. It is reported elsewhere — the tables beside a Combined's [correlation matrix](/docs/analysis/correlation-matrix) carry an [adjusted beta](/docs/analysis/adjusted-beta) for each strategy, and for the Combined itself, against each market factor. - [Adjusted beta](/docs/analysis/adjusted-beta) is a separate variant — an estimate pulled toward 1.0 to steady it on short histories — and on the Beta Neutral method its toggle is on by default; turn it off to work from the raw fitted beta. ## What does it look like in practice? Take an instrument with a beta of 1.5 against its reference. On a day the market rises 1%, the instrument would be expected to rise roughly 1.5%; on a day the market falls 1%, it would be expected to fall roughly 1.5%. Across a −20% market fall, a beta of 1.5 points to roughly −30%. Now compare an instrument with a beta of 0.5: the same −20% market fall points to roughly −10%. Both figures are averages fitted over past returns, not per-day promises — a high-beta instrument can rise on a day the market drops, and beta says nothing at all about the part of the return that is unrelated to the market, which is what [alpha](/docs/analysis/alpha) describes. ## What counts as a good value? There is no good or bad beta, because beta is not a score. A beta near 1 means the position essentially rides the market; well above 1 means market moves reach you magnified in both directions; well below 1, or negative, means you are less exposed to the market's direction and more exposed to whatever else drives that instrument. What beta does tell you is where a result came from: a strategy with high market exposure that gained in a rising market got much of that gain from the market itself, which is why beta is usually read next to a [benchmark](/docs/getting-started/benchmark) comparison rather than on its own. *Beta is estimated from historical returns and describes past sensitivity, not future movement.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/cagr # CAGR CAGR, the compound annual growth rate, is the single constant yearly rate that would grow a strategy from its starting value to its final value over the backtest period. It expresses a whole run's return as one annualised percentage, so runs of different lengths can be compared on the same yearly scale. CAGR is the *compounded* view of annualised return — it accounts for growth building on growth, unlike [AAGR](/docs/analysis/aagr), which averages yearly returns as if each restarted from scratch. Because it is a ratio, CAGR does not depend on how much starting capital you used. **Also seen as:** compound annual growth rate, annualised return, geometric return ## How is CAGR calculated? CAGR takes the whole-period return and finds the constant yearly rate that, compounded over the number of years in the period, reproduces it. $$ \text{CAGR} = (1 + \text{total return})^{1/\text{years}} - 1 $$ where: total return is the whole-period gain as a fraction, and years is the length of the backtest in calendar years. ## What does CAGR mean on my result? The CAGR on a result is the single yearly rate that would have carried that run from its starting value to its final value — it restates the whole backtest as one annualised percentage. It is a summary of the period, not a rate any individual year achieved: a run that gained 40% one year and lost 15% the next still reports one CAGR, and no year in it looked like that number. It also says nothing about the path — two runs with the same CAGR can have had very different [drawdowns](/docs/analysis/max-drawdown) along the way, which is why the metrics view shows both. Compare CAGRs only across runs of comparable length and over the same period; a 3-year run and a 20-year run annualise very different amounts of market history. ## How does Fincanva handle it? - Fincanva computes CAGR geometrically over the calendar years of the backtest, carried to decimal months. - CAGR fills the annualised-return slot on the metrics view when **Reinvest profits** is on; with it off, the same slot shows [AAGR](/docs/analysis/aagr), the arithmetic version. - It is expressed as a percentage and can be negative when a strategy loses money over the period. ## What does it look like in practice? A strategy grows 10,000 into 16,100 over 5 years — a total return of +61%. Its CAGR is the yearly rate that compounds to that gain: (1 + 0.61)^(1/5) − 1 ≈ 0.10, or about 10% per year. Growing at a steady 10% a year for five years does turn 10,000 into roughly 16,100, which is exactly what CAGR states in one number. *No CAGR is a rate you can expect to repeat.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/capital-chart # Capital chart The capital chart is the money view of a backtest on a strategy's **Capital Growth** page: a chart titled **Growth** that plots the strategy's total value over the whole simulated period, with the part sitting in cash drawn inside it, the benchmark behind it, and a drawdown panel below. Where a percentage return tells you how much a strategy made, the capital chart tells you what it was holding while it made it. **Also seen as:** the Growth chart, the capital growth view. ## What are the series on the capital chart? Read in money, the **Growth** chart carries four series and two vertical axes. - **Total value** is the filled area covering everything the strategy is worth on that date — positions plus cash together. Its axis is titled **Value**. - **Cash capital** is a second area drawn inside the first, showing the part of that total which is *not* in positions. The distance between the two areas is therefore the invested part, so the split reads off the gap rather than off a separate line. - **Benchmark** is a dashed line on the same axis, the [benchmark's](/docs/getting-started/benchmark) own money curve over the same dates from the same starting capital. - **Drawdown** is the shorter panel underneath, on its own **Drawdown** axis: an area hanging down from zero showing how far below its previous peak the strategy was on each date. See [max drawdown](/docs/analysis/max-drawdown). A toggle in the chart header switches the whole chart between money — labelled with your account's base-currency code — and **%**, which redraws the same result as cumulative return. In the **%** reading the single line is **Growth** and there is no cash series, because a share of a total has no cash component; the **Drawdown** panel stays. See [equity curve](/docs/analysis/equity-curve) for how to read the curve itself. ## Why does the cash band matter? Because the gap between **Total value** and **Cash capital** is the plainest available answer to "how much of my capital was actually working?". A strategy that holds a cash reserve, or that stops holding positions for a stretch, shows that as a thicker cash band in exactly the dates it happened — which is something no single metric in **Performance Metrics** reports. The Holdings view reports the same split for a single date, as [Cash % and capital invested](/docs/portfolio-holdings/cash-and-capital-invested). Two settings move that band. A strategy's invested share decides how much capital is put to work in the first place, with the remainder held as a cash reserve; see [invested capital and the cash reserve](/docs/strategies/invested-capital-and-cash-reserve). And a [risk condition](/docs/strategies/risk-conditions) switches the strategy to its [Risk-Off](/docs/strategies/risk-on-and-risk-off) allocation profile, which typically holds a lower invested share — so on the chart a Risk-Off stretch reads as the cash band widening. ## What else is on the Capital Growth page? - A **Summary** card beside the chart: **Current value** as its headline, then **Invested** and **Profit**, plus the CAGR and max drawdown, closing with the dated span of the run. **Invested** here means the capital that was put in at the start of the run — not the amount currently in positions, which is what the chart's cash band describes. - A **P&L breakdown** chart, which splits the same result into its gain and cost components. See [P&L breakdown](/docs/analysis/p-l-breakdown). - A KPI strip above them: **Final value**, **Vs benchmark**, **Max drawdown** and **CAGR**. ## How does Fincanva handle it? - **Total value** and **Cash capital** are money figures in your account's base currency; **Growth** and **Drawdown** are percentages. - The chart, the **P&L breakdown** and the range selector share one date range, so narrowing the period narrows all of them together. - Three display switches — **Inflation-adj.**, **Benchmark** and **Log scale** — change how the chart is drawn without re-running the backtest. See [chart toggles](/docs/analysis/chart-toggles). - The chart appears only after a completed run; before that the page reads "No results yet" and "Backtest this strategy to generate its capital analysis." ## What does it look like in practice? A strategy starts with 100,000 and is set to invest 90% of it, so from the first date the chart shows a **Total value** area of 100,000 with a **Cash capital** band of 10,000 held underneath — the strategy is running with 90,000 at work. Three years in, the strategy's risk condition turns on and it switches to a Risk-Off allocation that invests only 40%. On the chart the **Cash capital** band jumps from roughly a tenth of the total to well over half of it, and stays there for as long as the condition is active. The **Total value** area barely moves in that moment, because switching to cash does not by itself gain or lose money — it changes the exposure, not the value. What you then see is the **Total value** line flattening out while the market moves, and the **Drawdown** panel below staying shallower than it would have been fully invested. When the condition clears, the cash band narrows again and the total resumes tracking the market. That whole sequence is invisible on a percentage-return chart, which would only show a flat stretch with no explanation for it. ## What should the cash band look like? There is no shape it should have — the band simply reports what the strategy's own rules produced. A permanently thick band means most of the capital sat idle for the period, and a band that appears only in specific stretches means something in the strategy moved it there on those dates. A wide band is neither a gain nor a loss in itself; it is exposure you did not take, in both directions — what the reserve itself earns while it sits there is a separate matter, covered on [interest received and paid](/docs/analysis/interest-received-and-paid). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/chart-toggles # Chart toggles Chart toggles are the three display switches above the **Growth** chart on a strategy's **Capital Growth** page — **Inflation-adj.**, **Benchmark** and **Log scale** — which change how an already-computed backtest is drawn without changing the backtest itself. They are a different kind of control from the simulation assumptions: **Costs & interests**, **Taxes** and **Reinvest profits** change *which figures* a page shows, while chart toggles change only *how the same figures are plotted*. See [simulation assumptions](/docs/backtesting/simulation-assumptions). **Also seen as:** display toggles, chart display switches. ## What does Inflation-adj. do? **Inflation-adj.** redraws the curve in *real* terms instead of nominal ones — the value restated in the purchasing power of the start of the period, so a rise on the chart means the strategy grew faster than prices rose rather than simply that the number got bigger. The adjustment uses a real historical monthly inflation series rather than a fixed assumption, so the correction is larger across high-inflation stretches and small across quiet ones. Where a requested date falls outside that series — before it begins or after its last reading — a fixed fallback assumption stands in for it; see [special data series](/docs/data-methodology/special-data-series). Because both series are pre-computed when the backtest runs, flipping the switch is immediate and nothing is re-simulated. The switch applies to both readings of the **Growth** chart — the money one and the **%** one — at the same time. ## What does the Benchmark toggle do? **Benchmark** shows or hides the dashed [benchmark](/docs/getting-started/benchmark) line on the chart. It is on by default and is purely visual: hiding the line does not remove the benchmark from the run, and the metrics table's **Benchmark** column keeps reporting it either way. ## What does Log scale do, and why is it sometimes greyed out? **Log scale** replaces the chart's linear value axis with a logarithmic one, so **equal vertical distances mean equal percentage changes** instead of equal amounts of money. On a linear axis, a curve that compounds looks like it accelerates — the later years are drawn far taller than the early ones purely because the amounts are larger. On a log axis, a constant growth rate is a straight line, which makes it possible to compare the pace of an early stretch against a late one by eye. **Log scale switches itself off and becomes unavailable when the chart contains values that a logarithmic axis cannot plot.** A log axis has no position for zero or for a negative number, so the toggle is only offered when the whole visible history stays above zero: every date's total value must be positive, and the benchmark's curve must be positive too. If either fails anywhere in the run, the switch appears off and greyed out rather than silently dropping the offending points. Turning **Inflation-adj.** on or off is re-checked the same way, because the two series can differ — a run can be log-capable in nominal terms and not in real terms. One more behaviour follows from the same rule: if the total value is positive throughout but the **Cash capital** series touches zero at some point — which happens whenever a strategy is fully invested — then **Log scale** stays available and the **Cash capital** band is hidden while log is active, because zero cash has no place on a log axis. Switch log back off and the cash band returns. **Log scale** applies to the money reading of the **Growth** chart. The **%** reading is drawn on a linear axis, since it is already a percentage. ## How does Fincanva handle it? - All three toggles start in the same state on every visit: **Inflation-adj.** off, **Benchmark** on, **Log scale** off. They are not saved with the strategy. - No toggle re-runs the backtest. The metrics table has no equivalent controls of its own, and nothing you switch here changes a figure in it. - The toggles live on the **Capital Growth** page's **Growth** chart. The other analysis pages have their own controls, not these. - The period buttons and zoom bar beside them narrow the visible date range; they are also display-only. ## What does it look like in practice? A strategy runs 20 years, from 10,000 to 40,000 — a nominal total return of +300%. Leave every toggle off and the curve rises fourfold, steepening towards the right because each later year adds more money than an early one did. Turn **Log scale** on and the same curve straightens out: the four-fold rise now reads as a roughly even climb, and you can see that the strategy grew at a similar percentage pace early and late. Nothing about the result changed — only the axis. Now turn **Inflation-adj.** on. Across those 20 years prices roughly doubled, so the real ending value is around 20,000 in start-of-period money and the real total return is closer to +100% than +300%. The final figure on the chart drops by half even though the strategy's nominal result is untouched: the nominal number is what the account held, the real number is what it could buy. The gap between the two readings is one of the largest single differences a long backtest can show, which is why the toggle exists. ## What should you read on which setting? Each setting answers a different question, so there is no "correct" one to leave on. Nominal is what the account balance actually was, and it is the basis of every figure in the metrics table. Real answers what the result was worth, which matters most over long windows and much less over short ones. A linear axis shows amounts of money; a log axis shows rates of change and is the setting on which a long compounding curve is honest about its early years. The one thing to avoid is comparing two curves drawn on different settings — a real curve and a nominal curve of the same strategy are not the same chart, and neither figure is more "true" than the other. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/conditional-value-at-risk # Conditional Value at Risk Conditional Value at Risk (CVaR) is the average loss across a strategy's worst days: at the 95% level Fincanva uses, it is the mean daily loss over the worst 5% of trading days. Where [Value at Risk](/docs/analysis/value-at-risk) marks the threshold those days start from, CVaR measures how deep they go once past it, so two strategies with the same VaR can have very different CVaRs when one of them has rare, much deeper falls. **Also seen as:** CVaR, expected shortfall, ES, CVaR 95%, tail loss ## How is Conditional Value at Risk calculated? CVaR averages every loss at or beyond the VaR: $$ \text{CVaR}_{95\%} = \mathbb{E}\left[\,L \mid L \ge \text{VaR}_{95\%}\,\right] $$ where: $L$ is the strategy's loss on one day and $\text{VaR}_{95\%}$ is the loss that only the worst 5% of days reach. In words: line up every day of the backtest from worst to best, keep the worst 5%, and average their losses. Because it is an average of the days beyond the VaR, it can never be smaller than the VaR itself. ## How is CVaR different from VaR? VaR answers "where do the bad days begin?" and CVaR answers "how bad are they on average?". VaR is blind to what happens past its threshold: a strategy whose worst days are all just past the VaR and one whose worst days include a collapse can share the same VaR. CVaR sees the difference, because the collapse pulls its average down. That sensitivity to the far tail is why CVaR is the measure risk managers prefer when losses have fat tails, and why the [Minimum CVaR](/docs/strategies/minimum-cvar) allocation method uses it as its objective. ## How does Fincanva handle it? - **Daily, at 95%, historical.** The CVaR in Performance Metrics is read straight off the backtest's daily returns and written as a positive loss: "3.0%" is an average loss of 3.0% on the worst days. - **Performance Metrics** shows it in the **Worst days · 95%** group as **Daily CVaR · historical** — see [what every number in Performance Metrics means](/docs/analysis/what-every-number-in-performance-metrics-means). - The **Stress test** sets the **Daily CVaR 95%** of the strategy's historical days beside the same figure under the scenario. When the worst 5% of days shrinks to a single day, the row is marked "· a single day": the VaR and the CVaR are then equal and say little — see [stress test](/docs/analysis/stress-test). - A simulation computed before the row existed shows "n/a", never 0%. ## What does it look like in practice? Two strategies both read **Daily VaR · historical** 2.0%. The first reads **Daily CVaR · historical** 2.6%: past the threshold its bad days stay close to it. The second reads 4.1%: among its worst days are a few very deep ones, and they drag the average far past the threshold. The VaR alone would call them equally risky on a bad day; the CVaR shows the second one's tail is much heavier. ## What counts as a good value? Lower means shallower bad days. The gap between CVaR and VaR is often more telling than either figure: a CVaR only a little above the VaR means the tail is thin, a CVaR far above it means the worst days hide much deeper ones. Like VaR, it describes the history that was tested — a period with a crash in it carries a higher CVaR than one without — and it is not a cap on what a future day can lose. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/contribution-analytics # Contribution analytics Contribution analytics is the card at the top of a [Combined](/docs/getting-started/combined)'s **Components** tab, titled "Strategies: where the result comes from", that splits the Combined's result among the strategies inside it. For each strategy it gives the share of the Combined's return, of its risk, of its Sharpe and of its daily VaR that the strategy accounts for, and a **Residual** row holds what belongs to no strategy — interest on cash, costs, taxes. Every column adds up to the Combined's own figure, so the parts explain the whole with nothing left over. **Also seen as:** return attribution, risk attribution, risk contribution, performance attribution ## What does each column of contribution analytics show? One row per strategy, then **Residual**, and the Combined's totals in the header above the table. | Column | What it says about the strategy | |---|---| | **Average weight** | the share of the Combined's capital it held, on average over the period | | **Return contribution** | how much of the Combined's average annual return it produced | | **Risk share** | how much of the Combined's volatility it is responsible for, shown as a bar | | **Sharpe contribution** | how much of the Combined's Sharpe it accounts for, in Sharpe points | | **VaR 95% contribution** | how much of the Combined's daily VaR at 95% it accounts for | In prose: the first column is how big each piece was, and the other four are how much of the result it made. The header gives the totals the columns add up to — **Average annual return (arithmetic)**, **Annual volatility**, **Sharpe** with the risk-free rate it used, and **Daily VaR 95% · Gaussian**. ## How can the parts add up exactly to the whole? Because each column splits the Combined's own figure rather than measuring the strategies one by one. A strategy's return contribution is its weight times its return, day by day, averaged and scaled to a year, and those add up to the Combined's return. Risk is less obvious, since volatilities do not add: two strategies of 10% volatility make less than 20% together when they do not move in step. The risk share solves that the standard way, known as Euler allocation — each strategy is charged its weight times how much the Combined's volatility would rise if that weight grew a little. Charged that way, the shares always add up to 100%, and a strategy that moves against the others can take a **negative** share: it lowers the Combined's risk. The other two columns add up as well, each split its own way. **VaR 95% contribution** follows the risk share: the Combined's daily Gaussian VaR is its volatility term less its average return, and each strategy is charged its risk share of the first and its return contribution of the second. **Sharpe contribution** is each strategy's return contribution above the risk-free rate, divided by the Combined's volatility — with the risk-free rate charged to each row in proportion to its average weight — so the rows sum to the Combined's Sharpe. The table is rounded to four decimals, so a column can miss its total by a hair; the whole is still exact. ## What is the Residual row? **Residual** holds everything in the Combined's result that belongs to no single strategy: interest on the cash the Combined held, its costs, and its taxes — the app's own note under it reads "interest on cash, costs, taxes". It is what makes every column add up, so it is always shown, never hidden. Its **Average weight** is the average share of the Combined held in no strategy at all, which is cash. It can be **negative**: a Combined investing more than its capital, with [leverage](/docs/backtesting/leverage), holds less than no cash — it has borrowed. ## How does Fincanva handle it? - The card is for a Combined only: a single strategy has one part, and nothing to split. It sits above the rest of [strategy analytics](/docs/analysis/strategy-analytics) on the **Components** tab and needs no plan of its own — it is included wherever that tab is. - The return here is the [**arithmetic** average annual return](/docs/analysis/backtest-reliability#what-is-the-average-annual-return-arithmetic) — the average daily return scaled to a year — so it does not match the compound growth rate, CAGR, on Performance Metrics; the card says so beside it ("different from Metrics' CAGR"). - The daily VaR is the Gaussian one: it assumes daily returns follow a normal distribution with the period's own average and volatility. The historical VaR on [Performance Metrics](/docs/analysis/what-every-number-in-performance-metrics-means) makes no such assumption, so the two can differ. - A period selector narrows the card to one calendar year. If a year has too few trading days to split, the card says so and shows the whole period. - It follows the tab's **Simulation settings**: switching **Costs & interests**, **Taxes** or **Reinvest profits** recomputes it, and brings the period back to the whole backtest. ## What does it look like in practice? A Combined holds two strategies, an equity strategy at 60% of the capital and a bond strategy at 40%, and returns 7.0% a year with 10% volatility. The equity strategy's row shows a return contribution of 5.8% and a risk share of 94%; the bond strategy's shows 1.5% and 6%; **Residual** shows −0.3% of return — costs outweighing cash interest — and no share of the risk. Return: 5.8 + 1.5 − 0.3 = 7.0%. Risk: 94 + 6 = 100%. Read the risk column and the picture is clear: the bonds hold 40% of the money and account for about a sixteenth of the risk, and nearly all of the Combined's ups and downs come from the equities. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/correlation-matrix # Correlation matrix A correlation matrix is a pair-by-pair table of how closely two return series moved together over a period: each cell holds a correlation coefficient between −1 and +1, where +1 means the two moved in lockstep, 0 means no linear relationship, and −1 means they moved in opposite directions. Applied to a [Combined](/docs/getting-started/strategy-in-a-combined), the matrix pairs each strategy it holds with the others and with the Combined itself, and the same series are set against a handful of market factors beside it; each pair is conventionally reported alongside two companions, **r²** and an **adjusted beta** in each direction. Fincanva shows such a matrix for a Combined, computed on daily returns, on the **Correlations** page of its analysis. **Also seen as:** correlation table; pairwise correlations. ## How is correlation calculated? Correlation is the covariance of two return series divided by the product of their standard deviations, which rescales the relationship into the fixed −1 to +1 range so any two pairs can be compared. $$ \rho_{AB} = \frac{\operatorname{Cov}(A, B)}{\sigma_A \, \sigma_B} \qquad\qquad r^2 = \rho_{AB}^{\,2} $$ where $\operatorname{Cov}(A, B)$ is the covariance of the two return series, $\sigma_A$ and $\sigma_B$ are their standard deviations, $\rho_{AB}$ is the correlation coefficient, and $r^2$ is simply that coefficient squared. ## What does r² add to a correlation? r² is the correlation squared, and it says how much of one series' variation is explained by the other. A correlation of 0.9 gives an r² of 0.81 — a strong shared story; a correlation of 0.3 gives an r² of 0.09, so roughly nine tenths of the movement is unexplained by the pair. Its practical job in a matrix is to flag which cells deserve attention: a low r² means the pair's relationship is weak, so any [beta](/docs/analysis/beta)-style figure reported beside it would rest on that weak relationship and should be read as noise rather than as a reliable sensitivity. In a matrix that carries them, [adjusted beta](/docs/analysis/adjusted-beta) figures run in both directions — A on B and B on A — because a sensitivity is not symmetric even though the correlation is. How that adjustment is defined is documented on its own page. ## How do you read a correlation matrix? A matrix is read as a grid of pairs, and three habits make it useful: - **The diagonal is always 1** — every series is perfectly correlated with itself, so those cells carry no information. - **The matrix is symmetric**, so each pair appears once: the cell for A-and-B is the cell for B-and-A. - **Where the cells are colour-graded, the intensity tracks the size of the correlation**, not its usefulness — a block of deeply-shaded cells is a cluster of things that move together, and the faint cells, easy to skip past, are the ones that behave independently. ## What counts as a good value? Low correlation is what makes a group of holdings behave differently from each other; high correlation means they are, in effect, expressing the same bet in different clothing. Two cautions come with reading the number: correlation only captures the *linear* relationship between two series, and it is not stable — pairs that look independent in calm periods often move together in a market shock, which is precisely when their independence was supposed to help — see [rolling correlation](/docs/analysis/rolling-correlation) for the through-time reading of the same pair. ## Does Fincanva show a correlation matrix? Yes — a Combined's analysis has a **Correlations** page, and the matrix is the table it opens with, **How they move together**: the lower triangle of every strategy-against-strategy pair, plus a column for each strategy against the Combined itself, all computed on daily returns. Only the lower triangle is drawn, because the upper half repeats every cell and the diagonal is 1 by definition, so neither is data. Beside it, **Against the big markets** sets each strategy — and the Combined — against six of the [factor roster](/docs/analysis/factor-roster), switching between two readings of the same pair, **Correlation** and **Adjusted beta** — the second of which is the [adjusted beta](/docs/analysis/adjusted-beta). A period selector above both scopes them to the whole run or to a single calendar year; a year the engine has no correlations for falls back to the whole period rather than emptying the tables. **r² is deliberately not a column.** On Fincanva's figures r² is exactly the square of the correlation printed beside it, so a column of it would restate its neighbour rather than add anything — the reading in the section above is done from the correlation itself. A [rolling correlation](/docs/analysis/rolling-correlation), the through-time form of the same measure, is not shown either. The page is included from the Advanced plan, the same plan level as [Strategy analytics](/docs/analysis/strategy-analytics): Free and Starter meet a refusal drawn over a sample strategy rather than their own figures. See [what each plan includes](/docs/account-security/what-each-plan-includes). [Strategy analytics](/docs/analysis/strategy-analytics) answers a neighbouring question one strategy at a time: [tracking error](/docs/analysis/tracking-error) says how differently a strategy moved from its parent Combined, where the matrix says how differently the strategies moved from *each other*. The **Correlation matrix** setting of [Min Correlation](/docs/strategies/min-correlation#which-correlation-estimate-does-min-correlation-use) is a different thing: it chooses how that allocation method estimates the correlations it weighs on inside a single strategy, and it does not change this page. ## What does it look like in practice? A Combined holds three strategies. Strategies A and B show a correlation of 0.9: an r² of 0.81, so most of what one did the other did too — holding both bought roughly one exposure twice, and the Combined's risk is more concentrated than the count of strategies suggests. Strategy C pairs with A at 0.2, an r² of 0.04: their paths are almost unrelated, so C is the strategy actually doing something different inside the Combined. Then read the same row for a market factor: if A also correlates 0.9 with the broad market, most of A's story is the market's story, not A's. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/dividends-and-splits # Dividends and splits Dividends and splits are the two corporate events a backtest records against a position it holds: a **dividend** is a cash payment the company makes per share held, and a **split** is a change in the number of shares outstanding that rescales both the share count and the price per share. Both are recorded event by event with their date, so a position's history shows not just its trades but everything the instrument itself did while it was held. **Also seen as:** corporate actions; distributions; stock splits. ## What does a dividend event record? A dividend event records how much cash the company paid per share and what that came to for the position. The event carries the **dividend per share** in the instrument's own currency, the number of shares held at the time, the price at that date, the **gross gain** the payment produced in the account's base currency, the **withholding tax rate** applied, and the **realized gain** left after that [withholding tax](/docs/backtesting/withholding-tax). Gross gain is the dividend per share multiplied by the shares held; realized gain is what the position actually kept. On a short position the same event runs the other way — the position owes the dividend instead of receiving it — which is why it can appear as a [negative dividend](/docs/analysis/negative-dividends). ## What does a split do to a position? A split rescales the position without changing what it is worth. The **split ratio** says by how much: a 2:1 split (ratio 2) turns every share into two and halves the price per share, so a position that held 100 shares at 80 holds 200 shares at 40 afterwards. **The position's value is unchanged** — that is the whole point of a split. It moves no cash, produces no gain or loss, and is recorded purely so the [share count](/docs/strategies/contracts) and price before and after the event make sense together. A reverse split works the same way in the other direction: fewer shares, a higher price per share, the same value. ## How does Fincanva handle it? - Dividends and splits are shown as one merged event stream per position, newest first, under the heading "Dividends & splits", with an "Event" badge marking each row as a "Dividend" or a "Split". - One "Value" column carries both meanings: on a dividend row it is the dividend per share; on a split row it is the split ratio. - A split row leaves the money columns empty — a dash — because a split settles no cash: there is no gross gain, no withholding, and no realized gain to show. - The "Side" column on a dividend or split row shows the **position's** side, not a side belonging to the event itself. - Dividend per share and the price are in the instrument's own currency; gross gain and realized gain are in the account's base currency, so one row can legitimately mix two currencies. - Dividends are counted separately from trading results: a position's dividend income has its own column and its own band on the [P&L breakdown](/docs/analysis/p-l-breakdown), rather than being folded into its trading profit. ## What does it look like in practice? A position holds 100 shares of a stock trading at 80 — a value of 8,000. The stock splits 2:1, so the split row records a ratio of 2: the position now holds 200 shares at 40, and its value is still **8,000**. Nothing was gained or lost; only the units changed. A month later the company pays a dividend of 0.50 per share. With 200 shares held, the gross gain is 200 × 0.50 = **100**. Take an illustrative 15% [withholding tax](/docs/backtesting/withholding-tax): the realized gain is 100 − 15 = **85**, the cash the position actually kept from the payment. The rate that actually applies depends on your tax residency and on where the dividend was paid from, so read it off the event's own "Withholding tax rate" rather than assuming one. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/equity-curve # Equity curve An equity curve is the line that plots a strategy's value at every date of its backtest, from the first simulated day to the last, so you can read the whole path a result took rather than only the number it ended on. Two strategies can finish at exactly the same value while their curves look nothing alike — one climbing steadily, the other spiking and collapsing — and the curve is where that difference becomes visible. **Also seen as:** growth chart, capital curve ## What does the Growth chart actually show? Fincanva titles this chart **Growth**, on the **Capital Growth** page of a strategy's analysis. The **Growth** chart draws one curve for your strategy across the whole simulated period, with a dashed **Benchmark** line behind it and a shorter **Drawdown** panel stacked underneath sharing the same dates. A toggle in the chart header switches the curve between two readings of the same result: your account's base-currency code shows it as money, and **%** shows it as cumulative return. In the money reading, the filled area is **Total value** — everything the strategy is worth on that date — with a second **Cash capital** area inside it for the part sitting in cash; the vertical axis is titled **Value**. In the **%** reading the single line is **Growth**, the return accumulated since the start, and the axis is titled **Return**. The lower panel is the same in both: an area titled **Drawdown**, hanging down from zero, showing how far below its previous peak the strategy was on each date. Above the chart sit the period buttons and a zoom bar that narrow the visible date range, and three display switches — **Inflation-adj.**, **Benchmark** and **Log scale** — which change how the same curve is drawn without re-running anything. See [chart toggles](/docs/analysis/chart-toggles) for what each one does. The **Performance Metrics** page carries a second, simpler version of the curve: the strategy's return as a soft filled area behind a headline reading **Overall return**, with the benchmark as a dashed line. It is the same series, presented as a summary rather than as a chart you interrogate. ## How do you read one equity curve? Read it in four places, left to right. 1. **The left edge** is the starting capital — where every curve begins, so the strategy and its benchmark start from the same amount and stay directly comparable. 2. **The slope** is the pace. A steep stretch is a period of fast gains; a flat stretch is a period where the strategy went nowhere, which costs nothing but time. 3. **The dips** are the falls from a previous high. The deepest one over the whole period is the [max drawdown](/docs/analysis/max-drawdown), and it is exactly the deepest point of the **Drawdown** panel below. 4. **The right edge** is the final value, and the gap between it and the left edge is the [total return](/docs/analysis/total-return). The [CAGR](/docs/analysis/cagr) is that same gap expressed as a yearly pace. The distance between your curve and the [benchmark](/docs/getting-started/benchmark) line at any date is how far ahead or behind the strategy was at that point — and the shared crosshair labels it "Ahead" or "Behind" as you hover. Because the benchmark is run as its own full simulation over the same dates and the same starting capital, the two lines are always on the same footing. ## How does Fincanva handle it? - The curve covers the full simulated period by default; the period buttons and zoom bar change what you see, never what was computed. - The **Benchmark** line is shown unless you switch it off. - The money reading and the **%** reading are the same underlying result — the toggle changes the unit, not the run. - The curve only exists after a backtest has completed. Before that the page reads "No results yet" and "Backtest this strategy to generate its capital analysis." ## What does it look like in practice? A strategy starts a ten-year backtest with 10,000 and ends at 24,000. The **%** reading of that same curve ends at +140%, its [total return](/docs/analysis/total-return); the [CAGR](/docs/analysis/cagr) works out near 9.1% a year. But the path matters. Suppose the curve climbs to 18,000 in year six, falls back to 12,600 during year seven, and only regains 18,000 in year nine before finishing at 24,000. The fall from 18,000 to 12,600 is −30%, so the **Drawdown** panel dips to −30% at that point and the metrics table reports −30% as the max drawdown. Reading only the ending — 24,000, +140% — hides two years spent below a level the strategy had already reached. That is the whole reason the curve is shown next to the numbers instead of behind them. ## What does the shape of a curve tell you? The shape tells you how a result was produced, not whether it is worth having. A curve that rises in small steady steps and one that jumps in a few large bursts can end at the same value while having behaved completely differently along the way, and the second one's outcome depended much more heavily on the particular window the backtest covered. A curve whose gains all arrive in one stretch is one worth checking against [start-date sensitivity](/docs/analysis/start-date-sensitivity), which re-runs the same strategy from many different starting months. A curve also cannot be read as a forecast in any form: it is one path through one set of historical dates, and its slope has no predictive claim on the dates after it. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/excess-return # Excess return Excess return is how much a strategy's return beats or trails its [benchmark's](/docs/getting-started/benchmark) return over the same period, measured in percentage points (pp). A positive excess return means the strategy outperformed its benchmark; a negative one means it lagged. It is the *plain* difference between the two returns, with no adjustment for how much market exposure the strategy carried — that adjustment is what [alpha](/docs/analysis/alpha) adds, and it is why the two can disagree about the same result. **Also seen as:** active return, outperformance ## How is excess return calculated? Excess return is simply the strategy's return minus the benchmark's return over the identical period. $$ \text{excess return} = \text{strategy return} - \text{benchmark return} $$ where: both returns cover the same dates, and the result is stated in percentage points (pp) — the plain difference between two percentages. ## What counts as a good value? A positive excess return means the strategy earned more than its benchmark over the period, which is the usual goal of an active strategy. It does not, on its own, say whether that extra return was worth the risk taken — a strategy can beat its benchmark while swinging far more along the way, so read it alongside a risk measure such as [max drawdown](/docs/analysis/max-drawdown). ## How does Fincanva handle it? - Excess return is a difference between two percentages, so it is reported in percentage points (pp), not as a relative percentage. - Both sides use the same starting capital and date range, because the benchmark is run as its own full backtest over the strategy's period. - It can be positive or negative, and it changes if you switch the benchmark the strategy is compared against. ## What does it look like in practice? Over the same period a strategy returns +12% while its benchmark returns +9%. The excess return is 12% − 9% = +3pp. Note that this is 3 percentage points, not "3% more": the strategy's return was three points of return above the benchmark's, a gap you read directly off the two figures. *Beating a benchmark once is not a reason to expect it again.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/factor-roster # Factor roster The factor roster is the fixed set of reference market series a strategy's returns can be compared against — 14 of them in Fincanva, covering the broad equity market, size and style tilts, government and corporate bonds, gold, real estate, and volatility indices. A factor is not something you invest in and not a [benchmark](/docs/getting-started/benchmark) you are scored against; it is a yardstick for a different question — *what has this strategy actually behaved like?* A strategy that correlates strongly with Gold has behaved like a gold position over the period measured, whatever tickers it held and whatever its rules were designed to do. **Also seen as:** factors, reference factors, factor set ## Which factors are in the roster? All 14 factors are active, so any of them can appear in a comparison. | Factor | What it stands for | |---|---| | Market (S&P 500) | the broad US large-cap equity market | | Small Cap | smaller-company US equity | | Mid Cap | mid-sized-company US equity | | Large Cap | large-company US equity | | Value | the value style tilt | | Growth | the growth style tilt | | 10y Treasury | ten-year US government bonds | | 3m T-Bill | three-month US government bills, the cash-like short end | | Investment Grade Corporates | investment-grade corporate bonds | | Gold | gold | | Real Estate (REIT) | listed real estate | | VIX | implied volatility of S&P 500 options — the "fear index" | | VIX 1M-3M Spread | the gap between one-month and three-month implied volatility, a measure of how front-loaded market stress is | | MOVE | implied volatility of US Treasury options — the bond-market equivalent of VIX | The factor series are built from market data supplied by multiple established data providers. Fincanva does not publish which instrument or series stands behind each factor. Like the [special data series](/docs/data-methodology/special-data-series), factors are reference series rather than instruments a strategy can hold; the roster is a separate, fixed set kept for comparison. One caveat belongs with the roster itself: **Market (S&P 500)** and **Large Cap** overlap heavily, because the S&P 500 is predominantly large-cap companies. Treat the two as closely related readings of the same thing rather than two independent ones. ## What does a factor correlation tell me? A factor correlation tells you how closely a strategy's period-to-period returns tracked that factor's, on a scale from −1 to +1 — the same scale a [correlation matrix](/docs/analysis/correlation-matrix) reports pair by pair. Read "vs Gold" as an example. A correlation of +0.7 with Gold means the strategy tended to rise in the periods gold rose and fall when it fell — worth knowing even if the strategy holds no gold, because it implies whatever it does hold responds to the same forces. A correlation near 0 means the strategy's moves and gold's were largely unrelated over the period. A correlation of −0.6 means it tended to move opposite to gold. Three limits keep that reading honest. Correlation is about *direction, not size*: a +0.9 with the Market says the strategy moved with the market almost every period, but not by how much — that is what [beta](/docs/analysis/beta) and [adjusted beta](/docs/analysis/adjusted-beta) measure. Correlation is not causation: a strategy can correlate with Gold because it holds miners, because it holds nothing but reacts to the same interest-rate news, or by coincidence over a short window. And a correlation is only as stable as the period it was measured over, which is why a [rolling correlation](/docs/analysis/rolling-correlation) says more than a single figure. {/* VISUAL: svg-diagram — the 14 factors as labelled cells in four groups (equity, fixed income, real assets, volatility), the three volatility cells marked as read on level changes rather than returns — tracked in VISUAL_BACKLOG */} ## Why do the volatility factors read differently? The three volatility factors — VIX, the VIX 1M-3M spread, and MOVE — are index *levels* rather than prices, so a comparison against them reads changes in the level rather than percentage returns. That is a reporting distinction with a practical consequence: a strategy whose returns correlate negatively with changes in VIX is one that tended to lose ground in the periods when market fear rose, which is the ordinary behavior of a long risk position. The other eleven factors are price-like series and are compared on returns in the normal way. It is also why the comparison table shows no [beta](/docs/analysis/beta) against a volatility factor: a beta measured on a change in a level has no unit anybody can read, so those cells stay empty while the correlation beside them is still reported. ## Does Fincanva show factor correlations? Yes, for a Combined: its analysis includes a correlations page whose second table sets each strategy, and the Combined itself, against six of the fourteen factors — Market (S&P 500), 10y Treasury, Investment Grade Corporates, Gold, Real Estate (REIT) and VIX. The six are the ones that disagree with each other. The other eight are left out because over a portfolio they largely repeat one of the six: the size and style factors move closely with Market, the 3m T-Bill is cash-like and sits near zero against everything, and MOVE and the VIX 1M-3M Spread are second-order volatility gauges standing next to the VIX itself. The roster is what such a comparison is read against, and it answers a question a strategy's own [instrument](/docs/getting-started/instrument) list often answers badly — *which factor does this strategy actually resemble?* That table reports two readings of the same pair — the correlation, and the [adjusted beta](/docs/analysis/adjusted-beta) where one can be read — and it is scoped by the same period selector as the [correlation matrix](/docs/analysis/correlation-matrix) beside it, which is where the page's shape and the plan level that includes it are documented. Fincanva does not tell you which factor exposures to hold or avoid — see [Is this financial advice?](/docs/investing-theory/is-this-financial-advice). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/final-value # Final value Final value is what a strategy's capital is worth on the last date of its backtest: the value of every position it holds plus the cash it holds, in the currency the analysis is shown in — your base currency on a strategy you own, US dollars on a Public strategy, which is shown with default settings. It is the point where the [capital chart](/docs/analysis/capital-chart)'s total-value curve ends, and it answers the plainest question a backtest can answer — "starting from my capital, what would I have ended up with?" **Also seen as:** ending value, terminal value. ## How is final value related to profit and total return? Final value is the capital you started with plus everything the run gained or lost on the way: $$ \text{Final value} = \text{Invested} + \text{Profit} $$ where **Invested** is the capital the run started with — positions plus cash on its first date — and **Profit** is the money gained or lost over the whole run, which can be negative. Dividing the profit by what was invested gives the [total return](/docs/analysis/total-return), so final value in money and total return in percent are two readings of one result. In words: a final value above the starting capital is a gain, one below it is a loss, and the gap between the two is the profit. ## What does "Vs benchmark" compare? **Vs benchmark** is final value minus the [benchmark](/docs/getting-started/benchmark)'s own final value, shown as a signed amount of money. The benchmark's money curve starts from the same capital on the same date, so the difference is a like-for-like verdict: a positive figure means the strategy ended with more money than the benchmark would have, a negative one means less. The percentage version of the same comparison is [excess return](/docs/analysis/excess-return). ## What is Combined value on Allocation History? **Combined value** is the figure the **Allocation History** page of a [Combined](/docs/getting-started/combined) opens with: the Combined's total worth on the last date of the run, across all the strategies it holds. It answers the same question final value answers, on the page that splits that worth between the strategies — see the [allocations chart](/docs/analysis/allocations-chart) for how the split is read. ## How does Fincanva handle it? - Final value is the first figure on the **Capital Growth** page, and the same figure heads the page's **Summary** card as **Current value**, with the run's total return beside it. The card's **Invested** and **Profit** are the two terms of the relation above. - It is shown in whole units of that currency. - The last date of the run is the latest market close the data holds, not today's calendar date — see [data freshness and frontier](/docs/backtesting/data-freshness-and-frontier). A result that is refreshed later can therefore end on a later date and show a different final value. - It follows the **Simulation assumptions** switches, and **Costs & interests** and **Taxes** are both off by default. With them off, final value is gross of both and the page says so: "These figures are gross of trading costs and taxes." Switching one of them on changes the label to name only the other. See [the costs switch](/docs/backtesting/costs-toggle) and [the taxes switch](/docs/backtesting/taxes-toggle). ## What does it look like in practice? A strategy starts with 100,000 in your base currency. On the last date of the run its positions are worth 131,400 and it holds 6,600 in cash, so its final value is 131,400 + 6,600 = **138,000**. The **Summary** card reads the same 138,000 as **Current value**, with **Invested** 100,000 and **Profit** 38,000 — a total return of 38,000 ÷ 100,000 = 38%. The benchmark, started from the same 100,000, ends at 129,500. **Vs benchmark** therefore reads **+8,500**: the strategy ended with 8,500 more than the benchmark would have. ## What counts as a good final value? There is no good final value on its own, because it depends on how much you started with and how long the run lasted. Two strategies with the same final value over ten years and over thirty years have very different results. To compare runs, read the rate — [CAGR](/docs/analysis/cagr) — and set it against the benchmark; to judge what the ride cost, read the drawdown beside it. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/fincanva-score # Fincanva score The Fincanva score is a single 0–5 quality score that summarises a strategy across several performance dimensions, so you can gauge its overall quality at a glance instead of reading every metric one by one. It is shown with a Strong, Fair or Weak tier — higher is better — and marked "Beta" while the feature is still being refined. The six dimensions it weighs are named on [What the Fincanva score is and how to read it](/docs/analysis/what-the-fincanva-score-is-and-how-to-read-it); their weights and the formula that combines them are proprietary and are published on no page. ## What the Strong, Fair and Weak tiers mean The 0–5 score maps to three tiers so you can read it at a glance: **Strong** (3.4 and above), **Fair** (2.0 up to 3.4), and **Weak** (below 2.0). A higher score is better across the board; the tier is the quick summary and the number is the finer reading within it. The tiers describe *how to read* the score — they are not the recipe behind it. ## How does Fincanva handle it? - A single 0–5 score, higher is better, summarising a strategy across several dimensions at once. - Shown on the metrics view as one headline figure with its Strong / Fair / Weak tier. - Marked "Beta" while the feature is being refined. - Treat it as an at-a-glance summary, then open the individual metrics to see the detail behind it. ## What does it look like in practice? Two strategies both look reasonable on their headline return. One earns a Fincanva score of 3.8 — Strong — because it holds up across the several dimensions the score weighs together. The other earns 1.6 — Weak — because one or more of those dimensions drags it down. The score flags that the second strategy is worth a closer look before you rely on it; to see what dragged it down, open the individual metrics behind the score. *A Fincanva score is not a rating to buy, hold or follow anything, and no score is a threshold to invest above.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/gross-vs-net # Gross vs net Gross is a result measured **before** costs are deducted; net is the same result **after** costs are deducted. On a position, gross is the trading profit or loss the position produced on price alone, and net is what is left of it once the trading fees and [slippage](/docs/backtesting/slippage) charged on that position are taken out — so the distance between a gross figure and its net twin is exactly what the trading cost. **Also seen as:** gross P&L, net P&L ## What is the difference between gross and net? Gross is the raw result and net is the result you actually kept. Both describe the same trades over the same period; only the treatment of costs differs, and one subtraction turns one into the other. $$ \text{Net} = \text{Gross} - \text{Costs} $$ where **Gross** is the trading profit or loss before any cost deduction, **Costs** are the trading fees and slippage charged on those trades, and **Net** is what remains. Because costs can only ever be a deduction, net is never larger than gross. ## What sits inside the Costs figure? Costs on a position are its trading fees plus its [slippage](/docs/backtesting/slippage) — the two charges that come from the act of trading. Tax and financing are not in this figure: tax on dividends and realized gains, and interest received or paid, are separate results that appear on their own bands of the [P&L breakdown](/docs/analysis/p-l-breakdown) rather than inside a position's Costs. Slippage is not a fee. It is the gap between the price the strategy targeted and the price it actually got, so it is a cost of *execution* rather than a charge anyone bills you — but it lands in the same Costs figure, because in both cases the money is gone before the result is measured. ## How do you read the sign of the Costs column? **Costs are shown as a positive deduction** — a cost of 40 appears as 40, not as −40, and you subtract it from Gross to reach Net. The one invariant to read the three columns by is that **Net is never larger than Gross**: costs can only take away, so if the Net cell is above the Gross cell on the same row, you are not reading a cost. One thing that does look wrong but is not: **each cell rounds independently**, so the three displayed figures need not add up to the last decimal. A true Gross of 500.4, Costs of 40.6 and Net of 459.8 print as 500, 41 and 460 — and 500 − 41 is 459, not the 460 on screen. Nothing was lost; the display simply rounded three times instead of once. ## How does Fincanva handle it? - A backtest reports **Gross**, **Costs** and **Net** next to each other at every level of detail — per symbol, per position, and per individual trade — so the same three-column reading works whether you are looking at a whole instrument or one fill. - Costs are trading fees plus slippage, in the account's base currency; the figures are money, not percentages. - Whether costs are charged at all follows the **Costs & interests** [simulation assumption](/docs/backtesting/simulation-assumptions), which is off by default. With it off, modelled costs are zero and gross and net read the same; with it on, they separate. - Gross and net describe *trading* results, so dividends are counted separately — a position's dividend income is its own column, and net plus that income is what makes up its [Total P&L](/docs/analysis/total-p-l). ## What does it look like in practice? A position is closed with a raw trading gain of 500. It paid 12 in trading fees and 28 in slippage over its life — 40 of cost in all, shown as a positive 40 in the Costs column. Net is 500 − 40 = **460**: the position made 500 on price and kept 460 after the cost of trading. Read the three columns together and that 40 is the whole story of the difference. A gross figure that looks strong can still net poorly when a strategy trades often enough for fees and slippage to accumulate. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/information-ratio # Information ratio The information ratio is a strategy's excess return over its parent Combined divided by its [tracking error](/docs/analysis/tracking-error) — a measure of how *consistently* the strategy outperforms the whole it belongs to. It is measured against the **parent Combined**, not against a benchmark: it asks whether a strategy's edge over the Combined is a steady contribution or an occasional lucky burst. **Also seen as:** IR, active return per unit of active risk ## How is the information ratio calculated? The information ratio divides the strategy's CAGR-based return above its parent Combined by the tracking error — the volatility of that same return difference. The numerator is the strategy's annualised (CAGR-based) return above the Combined, and the tracking error in the denominator is annualised the same way as volatility, by ×√252. High excess return earned smoothly scores well; the same excess earned erratically scores poorly. $$ \text{information ratio} = \frac{\text{strategy return} - \text{Combined return}}{\text{tracking error}} $$ where: **strategy return** and **Combined return** are the annualised, [CAGR](/docs/analysis/cagr)-based returns of the member strategy and of the Combined it sits inside, so the numerator is the strategy's excess return over the whole; and **tracking error** is the [tracking error](/docs/analysis/tracking-error) of that same return difference, annualised by ×√252. Both halves are annualised on the same basis, so the ratio is a plain number with no unit. ## What counts as a good information ratio? Higher is better: it means the strategy beats its parent Combined steadily rather than in occasional spikes. A value near zero means the strategy barely moves the Combined either way, and the sign follows the excess return — a strategy that consistently lags the whole has a negative information ratio. ## How does Fincanva handle it? - Reported on the [Strategy analytics](/docs/analysis/strategy-analytics) page only, in its **Each strategy, against the Combined** card: one bar per strategy in the **Information ratio** column, drawn from zero so a negative value runs to the left of the baseline. A strategy analysed on its own still appears there, but it has no parent Combined to be measured against, so its information ratio carries no meaning — read it only for a strategy inside a Combined. - Divides a strategy's CAGR-based excess return over its parent Combined by its √252-annualised tracking error. - Measured against the parent Combined, **not** against a benchmark. - A higher value reflects steadier outperformance of the whole; a near-zero value reflects a strategy that adds little either way. ## What does it look like in practice? A member strategy returns 2% a year more than the Combined it belongs to. If it earns that 2% edge smoothly — a low tracking error of, say, 1% — its information ratio is about 2.0. If it earns the same 2% edge but erratically — a tracking error of 4% — the information ratio falls to about 0.5. The excess return is identical in both cases; what separates them is consistency, and the information ratio is the number that captures it. *No information ratio is a target to aim for.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/interest-received-and-paid # Interest received and paid Interest received and interest paid are the two financing lines in a strategy's profit and loss: interest received is credited to the strategy, while interest paid is the cost of borrowing to fund leverage or to finance a short position. Fincanva shows them separately in the [P&L breakdown](/docs/analysis/p-l-breakdown) — "Interest received" on the gains side and "Interest paid" on the costs side — so financing shows up as its own effect rather than being buried in the total. **Also seen as:** financing cost, margin interest, carry ## What Fincanva charges interest on Interest paid arises whenever a strategy borrows: it uses leverage (borrows capital to hold more than its cash) or holds a short position (borrows the securities it sells). Each is priced as a spread over the broker's base rate, set by two fields in your simulation assumptions — "Borrowing rate markup" ("Spread added above the broker rate when borrowing capital.") and "Short rate markup" ("Spread added above the broker rate when shorting securities."). Those spreads are the [interest-rate markups](/docs/backtesting/interest-rate-markups); interest paid is only applied when the Costs assumption is on. ## How does Fincanva handle it? - The P&L breakdown carries two bands — "Interest received" on the gains side and "Interest paid" on the costs side — so the two directions are never netted into one figure. - Interest paid is charged only when the Costs simulation assumption is on. That assumption is off by default for every account, so interest paid reads zero until you switch costs on. - Uninvested (idle) cash rides on the same assumption as interest paid: with that assumption off — its default — idle cash earns nothing, so both bands read zero, and a wide cash band on the [capital chart](/docs/analysis/capital-chart) is capital that earned nothing. - With the Costs assumption on, idle cash is credited the [margin-loan reference rate](/docs/data-methodology/special-data-series) minus your "Borrowing rate markup", and never less than zero while that reference rate is above zero, so when the markup is the larger of the two, idle cash earns nothing. - When the reference rate is at or below zero, idle cash can be charged interest instead of earning it — as with the negative rates banks have charged on cash holdings — never more than 1% a year. ## What does it look like in practice? A strategy runs at 1.5× leverage for a month, borrowing 0.5× its capital to hold more exposure than its cash covers. For the days it holds that borrowed portion it pays the broker's base rate plus your "Borrowing rate markup" on the borrowed amount. That financing cost lands on the **Interest paid** band and pulls the net **Portfolio** line down for the month — the price of the extra exposure. Turn the Costs assumption off and the band drops to zero, which is why cost-free results flatter a leveraged strategy. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/longest-drawdown # Longest drawdown Longest drawdown is the longest stretch of time a strategy's value stayed below a prior peak — from the moment the value dropped below that peak until it reached the same peak again. It records **duration, not depth**: a strategy whose worst fall was mild can still have spent years below its old high, and that is exactly what this figure exposes. **Also seen as:** Longest DD, time underwater ## How is longest drawdown different from longest recovery? Longest drawdown counts the whole time spent below the peak; [longest recovery](/docs/analysis/longest-recovery) counts only the climb back up. The two are constantly confused because they describe overlapping parts of the same episode. | Measure | Starts at | Ends at | |---|---|---| | **Longest drawdown** | the old peak, when the value first drops below it | the moment the value reaches that old peak again | | **Longest recovery** | the trough, the lowest point of the fall | the moment the value reaches that old peak again | A longest-drawdown span therefore contains the fall *plus* the climb back, while longest recovery is only the second half of it. For the same episode, longest drawdown is always the longer of the two figures. ## How are these durations displayed? Fincanva formats both durations with one rule, so the same figure reads as a plain number or as years-and-months depending on its size: - **12 months or fewer** — a bare number to one decimal place, with **no unit**: `6.3` means 6.3 months. - **An exact whole number of years** — years only: `2y`. - **Anything else** — years and months: `1y 2m`. The metrics table row is labelled **Longest drawdown (months)**, so a value like `2y 8m` in that row can look surprising: the label names the underlying unit, while the value itself is formatted for readability. A bare `6.3` in that row means 6.3 months, never 6.3 years. ## What if the strategy never recovers before the backtest ends? **Read this before you read the chart.** If the value is still below its prior peak on the last simulated day, the stretch does not get dropped and it does not wait for a recovery that never comes. It is **cut off at the last simulated bar** and counted from the peak to that bar — and that truncated stretch competes for the maximum like any other, so it can be the number the page reports as the longest drawdown. The hazard is what this looks like on screen: **a drawdown that was still open when the data ran out is indistinguishable from one that ended in a genuine recovery.** Both simply stop. A reader glancing at the equity curve will conclude the strategy climbed back to its high; it may never have done so — the backtest just ended while it was still down. Two consequences worth carrying: - The reported figure is a **lower bound** on that episode. Had the backtest run longer, the stretch could only have been the same length or longer, never shorter. - The last episode of a run is the one to check. Look at where the equity curve finishes relative to its highest point: if it ends below that high, the final stretch is truncated, and the longest-drawdown figure may be describing an episode that never closed. ## How does Fincanva handle it? - The metrics table shows it in the **Drawdown** group as the row **Longest drawdown (months)**, using the format rule above. - The KPI strip on the metrics view shows the same span as the **Longest drawdown** card, rounded there to whole months. - It is measured over the whole backtest window, so a longer backtest has had more chances to contain a long stretch below a peak — the figure is not comparable across runs of different lengths. - Your [benchmark](/docs/getting-started/benchmark) gets its own longest drawdown over the same window, so a long stretch can be read against what the reference series did. ## What does it look like in practice? A strategy peaks in March, falls for five months, bottoms out, then grinds back up and finally reaches that same March peak 14 months after leaving it. Its longest drawdown for that episode is 14 months, displayed as `1y 2m`. The [max drawdown](/docs/analysis/max-drawdown) for the same episode might be only −11%: a shallow fall that simply took a long time to undo. The two numbers describe one event from different angles — one says how deep, the other how long. ## What counts as a good value? A shorter longest drawdown means the strategy's value spent less consecutive time below its previous high. It is a **duration** reading, so on its own it is half the picture: read it with [max drawdown](/docs/analysis/max-drawdown) for how deep the falls went, and with [longest recovery](/docs/analysis/longest-recovery) for how much of the stretch was spent climbing back rather than falling. A long value is not automatically a fault of the strategy's rules — a window that happens to contain a slow, broad market decline can produce a long stretch below a peak for almost any strategy exposed to that market. Where the window begins matters for the same reason; see [start-date sensitivity](/docs/analysis/start-date-sensitivity). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/longest-recovery # Longest recovery Longest recovery is the longest stretch of time a strategy took to climb from a trough back to its prior peak — the count starts at the bottom of a fall and ends when the value reaches the old high again. It answers "once it had stopped falling, how long did getting back take?", and it is measured **from the bottom, not from the peak**. **Also seen as:** recovery time, time to get back to the high ## How is longest recovery different from longest drawdown? Longest recovery covers only the climb back up; [longest drawdown](/docs/analysis/longest-drawdown) covers the fall *and* the climb. Both end at the same moment — the return to the old peak — but they start in different places, which is why the same episode produces two different numbers. | Measure | Starts at | Ends at | |---|---|---| | **Longest drawdown** | the old peak, when the value first drops below it | the moment the value reaches that old peak again | | **Longest recovery** | the trough, the lowest point of the fall | the moment the value reaches that old peak again | For a single episode, longest recovery is therefore the shorter of the two. Confusing them is the most common mistake with this pair: a "9-month recovery" and a "14-month drawdown" can be the same event, seen from the bottom and from the top. ## What if the strategy never climbs back before the backtest ends? **Read this before you read the chart.** If the value is still below its prior peak on the last simulated day, the climb is not discarded and it is not left open. It is **cut off at the last simulated bar** and counted from the trough to that bar — and that truncated climb competes for the maximum like any other, so it can be the number the page reports as the longest recovery. The hazard is the same one the [longest drawdown](/docs/analysis/longest-drawdown#what-if-the-strategy-never-recovers-before-the-backtest-ends) page warns about, and it bites harder here: **a climb that was still under way when the data ran out looks exactly like one that finished at the old high.** The figure does not say "still recovering"; it just reports a duration. A reader will take it as the time the strategy needed to get back. It may be the time the strategy had spent trying when the backtest stopped. So the reported figure is a **lower bound** on that episode: run the backtest longer and the same climb could only have taken the same time or more. If the equity curve ends below its highest point, the final recovery is truncated, and the longest-recovery figure may belong to a climb that never reached the peak at all. ## How does Fincanva handle it? - The metrics table shows it in the **Drawdown** group as the row **Longest recovery (months)**. - It uses the same duration format as longest drawdown — a bare one-decimal number for 12 months or fewer, `2y` for exact years, `1y 2m` otherwise. See [how these durations are displayed](/docs/analysis/longest-drawdown#how-are-these-durations-displayed). - Unlike longest drawdown, longest recovery appears in the metrics table only — it has no KPI card on the metrics view. - It is measured over the whole backtest window, so it is not comparable across runs of different lengths. ## What does it look like in practice? A strategy peaks, falls for five months to its trough, then takes nine months to climb from that trough back to the old peak. Its longest recovery for the episode is 9 months. The same episode's [longest drawdown](/docs/analysis/longest-drawdown) is 14 months — the five months of falling plus the nine months of climbing. Same event, two figures: 9 months of recovery sits inside 14 months below the peak. ## What counts as a good value? A shorter longest recovery means that, once a fall had bottomed out, the strategy needed less time to get back to its previous high. Like longest drawdown it describes **duration only**: it says nothing about how far the value fell, which is [max drawdown](/docs/analysis/max-drawdown), nor how much return the strategy earned for that worst fall, which is the [return-to-drawdown ratio](/docs/analysis/return-to-drawdown-ratio). A shallow fall can still take a long time to recover, and a deep fall can be undone quickly — the pairing of depth and duration is what the two readings together describe, and neither one ranks strategies on its own. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/max-drawdown # Max drawdown Max drawdown is the largest fall from a previous peak in a strategy's value to a later low, measured as a percentage of that peak, over the whole backtest period. It is the **worst peak-to-trough fall** the strategy would have lived through — not the loss it ended the period with. A strategy can finish a backtest up +40% and still show a max drawdown of −25%, because the two answer different questions: total return asks where you ended, max drawdown asks how bad it got on the way. A single drawdown is any fall from a running peak to a later low. Max drawdown is the deepest of them. The term stays *drawdown* in every language, including Italian. **Also seen as:** Max DD, DD ## How is max drawdown calculated? Max drawdown compares each low point against the highest value reached before it, and keeps the worst result. $$ \text{max drawdown} = \frac{\text{trough value} - \text{peak value}}{\text{peak value}} $$ where: peak value is the highest value the strategy had reached before the fall, trough value is the lowest value reached after that peak and before the strategy recovered, and the peak-and-trough pair chosen is the one producing the largest fall anywhere in the period. Because it is a ratio, max drawdown does not depend on how much starting capital you used. ## How does Fincanva handle it? - Max drawdown is measured on the strategy's capital curve over the whole backtest window, and shown as a negative percentage — a deeper fall is a more negative number. - The metrics table shows it in the **Drawdown** group as the row **Max drawdown**; the capital view shows the same figure as a KPI, and the by-year table repeats it per calendar year. - The monthly returns heatmap shows the per-year version of it in the compact **DD** column. - Your [benchmark](/docs/getting-started/benchmark) gets its own max drawdown over the same window, so the two are directly comparable. - Max drawdown is also selectable as the **Risk measure** in the Inverse Volatility allocation method, as the alternative to **Annualized volatility** — there it decides weights rather than reporting a result. - It feeds the [return-to-drawdown ratio](/docs/analysis/return-to-drawdown-ratio), which divides the period's return by the size of the max drawdown. - A drawdown deep enough to reach the simulation's floor triggers the [bankruptcy rules](/docs/backtesting/bankruptcy-rules), which close every position and leave the curve flat for the rest of the run. ## What does it look like in practice? A strategy climbs to a peak of 12,000, then falls to a low of 9,000 before recovering. Its drawdown from that peak is (9,000 − 12,000) ÷ 12,000 = −25%. If no other fall in the period is deeper, −25% is the max drawdown. Now suppose the same strategy recovers and finishes the backtest at 14,000, a total return of +40%. The max drawdown is still −25%: the figure records the worst dip along the path, and a strong ending does not erase it. ## What counts as a good value? A max drawdown closer to zero means the strategy's value never fell far below its running high during the period. It describes **depth only** — it says nothing about how long the strategy stayed down, which is what [longest drawdown](/docs/analysis/longest-drawdown) and [longest recovery](/docs/analysis/longest-recovery) measure, nor how far below its own starting point a typical start date left it, which is [average pain](/docs/analysis/average-pain). Two strategies with the same max drawdown can look very different if one recovered in two months and the other took three years. Max drawdown is also period-bound: it can only report the worst fall that happened inside your backtest window, so a shorter window has had fewer chances to produce a deep one. *No drawdown figure is a limit on future losses.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/metrics-table # Metrics table The metrics table is the read-out on a strategy's **Performance Metrics** page that reports 14 backtest metrics for your strategy next to the same 14 metrics for its benchmark, grouped into five named blocks. Each metric has its own definition and its own conventions; this page is the map of the table — what sits where, and where to read each figure's full meaning. **Also seen as:** the metrics page, the summary table Fincanva shows it in two parts on one page: **Summary** (the whole period) and **By year** (the same story, one row per calendar year). ## What does the Summary table show? **Summary** has three columns — the metric name, a **Portfolio** value and a **Benchmark** value — so every figure can be read against the benchmark run over the identical dates. The rows are grouped under five headings. **Performance** - **Total return (%)** — the whole-period gain or loss. See [total return](/docs/analysis/total-return). - **Years** — not a metric but the span: the number of calendar years the backtest covers, carried to decimal months so a partial year counts. It is the denominator that turns a total into a yearly pace, which is why it sits in this group. - **CAGR** — the compound yearly growth rate. See [CAGR](/docs/analysis/cagr). - **AAGR** — the arithmetic yearly average, which takes CAGR's place in the same slot when **Reinvest profits** is off. See [AAGR](/docs/analysis/aagr). **Drawdown** - **Max drawdown** — the deepest peak-to-trough fall. See [max drawdown](/docs/analysis/max-drawdown). - **Return-to-drawdown ratio** — the period's return divided by the size of that fall. See [return-to-drawdown ratio](/docs/analysis/return-to-drawdown-ratio). - **Longest drawdown (months)** — the longest stretch spent below a prior peak. See [longest drawdown](/docs/analysis/longest-drawdown). - **Longest recovery (months)** — the longest climb back from a trough to a prior peak. See [longest recovery](/docs/analysis/longest-recovery). **Volatility and risk** - **Volatility** — the annualized standard deviation of returns. See [volatility](/docs/analysis/volatility). - **Risk-free rate** — the period-matched riskless baseline the risk-adjusted metrics subtract. See [risk-free rate](/docs/analysis/risk-free-rate). - **Sharpe** — return above the risk-free rate per unit of volatility. See [Sharpe ratio](/docs/analysis/sharpe-ratio). **Monthly performance** - **Positive months (%)** — the share of months that closed up. See [positive months](/docs/analysis/positive-months). - **Best month** and **Worst month** — the single strongest and weakest month of the period. See [best month and worst month](/docs/analysis/best-month-and-worst-month). **Averages** - **Monthly average** and **Yearly average** — the plain averages of the monthly and annual return series. See [monthly and yearly average](/docs/analysis/monthly-and-yearly-average). The **Portfolio** value carries the colour: positive figures read green, negative red, and ratio rows are coloured against a neutral band. The **Benchmark** value is deliberately shown muted, because it is context rather than your result. ## How does the By year table work? **By year** repeats six of the same metrics per calendar year: the columns are **Year**, **Annual return (%)**, **Max drawdown**, **Volatility**, **Return-to-drawdown ratio**, **Sharpe** and **Positive months (%)**. Years are listed newest first, and the page's footer pages through them 25 at a time by default, with 50, 100 and **All** available. Each cell stacks two figures: your strategy's value on top, and a second, smaller line underneath. A **Benchmark** toggle in the card header decides what that second line is. - **Value** shows the benchmark's own figure for that year, prefixed with "vs" — and the card's caption reads "Each cell: your portfolio, with the benchmark value below." - **Delta** replaces it with the gap between the two, prefixed by an arrow: up and green when your strategy beat the benchmark on that metric, down and red when it trailed. The caption changes to "Each cell: your portfolio, with the gap vs the benchmark below." Two things about **Delta** are easy to misread. First, the gap between two percentages is a difference in **percentage points**, so it is labelled **pp** rather than **%** — see [excess return](/docs/analysis/excess-return). Second, the arrow means "better", not "bigger": for **Volatility** a lower number is the better one, so a smaller volatility than the benchmark's shows an up arrow. ## Why does the CAGR row sometimes read AAGR? Because the two annualization conventions share one slot and the **Reinvest profits** assumption chooses between them. With **Reinvest profits** on, the compounding assumption holds and the row is **CAGR**; with it off, profits are not compounded and the row becomes **AAGR**. The same choice flows into **Sharpe**, whose return term is whichever of the two is active. See [simulation assumptions](/docs/backtesting/simulation-assumptions). ## Where else do these metrics appear? - A KPI strip above the table leads with four headline figures — **Sharpe ratio**, **Volatility**, **Longest drawdown** and **CAGR vs benchmark**. - Every strategy row in your strategies list carries a compact version of the same read-out: **CAGR**, **Volatility**, **Sharpe** and **Max drawdown** as columns, alongside the **MTD**, **1M**, **YTD** and **1Y** return windows. All of them are shown by default and can be hidden from the **Columns** chooser. See [return windows](/docs/analysis/return-windows). - The **Monthly Returns** page repeats the per-year figures in its compact **Total**, **DD** and **NP/DD** columns. See [months matrix](/docs/analysis/months-matrix). - A Combined's [Strategy analytics](/docs/analysis/strategy-analytics) page repeats several of these figures per strategy — as cards of charts rather than as a table — and adds [Sortino](/docs/analysis/sortino-ratio), [Tracking error](/docs/analysis/tracking-error) and [Information ratio](/docs/analysis/information-ratio). The last two are measured against the parent Combined, not against the benchmark. For a row-by-row walkthrough with each metric's convention stated in place, read [what every number in Performance Metrics means](/docs/analysis/what-every-number-in-performance-metrics-means). ## How does Fincanva handle it? - Every row is computed over the same period for your strategy and for the benchmark, because the benchmark runs as its own full simulation on the same dates and starting capital. - Percentage rows are shown as percentages and ratio rows as plain numbers — **Sharpe** and **Return-to-drawdown ratio** are ratios, not percentages. - The three simulation assumptions — **Costs & interests**, **Taxes**, **Reinvest profits** — change which pre-computed set of figures the table reads; the switch is immediate and does not re-run the backtest. - **By year** opens in **Value** mode; the choice is a view preference and is not saved to the page's address. - The table fills in only after a completed run. Before that the page reads "No results yet" and "Backtest this strategy to generate its metrics." ## What does it look like in practice? Read one **By year** cell out loud. In the **Annual return (%)** column, the row for 2022 shows **−14.2%** on top and, in **Value** mode, "vs −18.0%" below it: the strategy lost 14.2% that year while its benchmark lost 18.0%. Flip the header toggle to **Delta** and the same cell shows **−14.2%** with **↑ 3.8pp** beneath it. The arrow points up and reads green because losing less than the benchmark is the better outcome on this metric, and the gap is 3.8 percentage points, not 3.8%. Move one column right to **Volatility**, where the strategy shows 11.0% against the benchmark's 15.5%: the delta is **↑ 4.5pp**, again up and green, because on volatility the smaller number is the better one. ## What counts as a good value? No single row answers that, and the table is built so that no single row has to. Each metric answers one narrow question — how much, how fast, how deep, how bumpy, how often — and reading one in isolation is how a result gets misread: a high return with a deep max drawdown and a high return with a shallow one are very different results with the same first number. The **Benchmark** column exists for the same reason. It tells you which part of a figure was the market and which part was the strategy's own doing, which is a genuinely different question from whether the figure is large. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/monthly-and-yearly-average # Monthly and yearly average Monthly and yearly average are the plain arithmetic means of a strategy's monthly and annual return series over the backtest period. The [metrics table](/docs/analysis/metrics-table) lists them as two rows, "Monthly average" and "Yearly average", in the **Averages** group. Both are simple averages — the figures in a series added up and divided by how many there are — not compounded growth rates, which is what makes them read differently from [CAGR](/docs/analysis/cagr). **Also seen as:** average monthly return, average annual return, Avg month ## How are the monthly and yearly averages calculated? Each is the arithmetic mean of its own return series. $$ \text{monthly average} = \frac{1}{n}\sum_{i=1}^{n} r_i $$ where: $r_i$ is the return of month $i$ and $n$ is the number of months in the backtest period. The yearly average is the same calculation over the series of annual returns, with $n$ as the number of years. ## Why is the yearly average not twelve times the monthly average? Because each yearly return already compounds its own twelve months, while the monthly average only adds monthly figures up and divides. Compounding means a year's return is built by multiplying its months together, not by summing them, so the annual series carries growth-on-growth that the monthly series does not. Multiplying the monthly average by twelve therefore usually lands below the yearly average, and neither result is the strategy's compounded growth rate — that is [CAGR](/docs/analysis/cagr), or [AAGR](/docs/analysis/aagr) when **Reinvest profits** is off. ## What counts as a good value? A positive monthly or yearly average means the typical period in the series gained rather than lost, but an arithmetic mean hides how spread out the figures were: two runs with the same monthly average can have completely different [best and worst months](/docs/analysis/best-month-and-worst-month). Comparing the yearly average with CAGR is the useful reading — a yearly average far above the run's CAGR points to returns that swung widely from year to year, because dispersion drags a compounded rate below an arithmetic one. ## How does Fincanva handle it? - Both appear in the **Averages** group of the metrics table, labelled "Monthly average" and "Yearly average", as percentages to one decimal place and coloured by sign. - The monthly returns view shows the same monthly figure as a KPI labelled "Avg month". - Neither is annualized or compounded — the annualized slot in **Performance Metrics** holds CAGR or AAGR instead, depending on the **Reinvest profits** assumption. - The monthly average is computed over the same month-by-month series the [monthly returns heatmap](/docs/analysis/reading-the-monthly-returns-heatmap) displays; the yearly average uses the annual returns the by-year metrics table lists as "Annual return (%)". ## What does it look like in practice? A five-year backtest has 60 monthly returns that add up to +41 percentage points, so its monthly average is 41 ÷ 60 ≈ +0.7% a month. The same run's five annual returns are +14%, −6%, +21%, +3% and +16%; they add up to +48, so the yearly average is 48 ÷ 5 = +9.6% a year. Twelve times the monthly average is about +8.2%, below the +9.6% yearly average, because each annual figure already compounds its own twelve months while the monthly average simply adds them up. Neither +0.7% nor +9.6% is the run's CAGR, which compounds the whole period into one rate. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/months-matrix # Months matrix The months matrix is the grid on a strategy's **Monthly Returns** page, titled **Monthly returns**, that shows one row per calendar year and one column per month, with each cell holding that month's return and each row ending in a three-column summary of the year. It answers a question a single total cannot: *when* the result happened — which months carried a year, which ones gave it back, and whether the gains were spread out or came from one stretch. **Also seen as:** monthly returns heatmap, month grid. ## What is in the matrix? The columns run **Year**, then **Jan** through **Dec**, then three per-year summary columns. - **Year** is the calendar year, and its column help reads "Calendar year". It stays pinned to the left as you scroll sideways, and clicking a year selects it. - **Jan**–**Dec** each hold that month's return for that year, printed as a percentage in the cell. Months that have not been simulated yet — the remainder of the current year, for instance — are left blank. - **Total** is the year's own total return. See [total return](/docs/analysis/total-return). - **DD** is the deepest fall inside that year. See [max drawdown](/docs/analysis/max-drawdown). - **NP/DD** is that year's return divided by the size of that fall. See [return-to-drawdown ratio](/docs/analysis/return-to-drawdown-ratio). Rows start with the most recent year at the top. Clicking any column header sorts the whole grid by that column and clicking again reverses it, so sorting by **Jan** ranks the years by their January, and sorting by **DD** brings the roughest years together. Blank months always sort to the bottom. The grid scrolls rather than paging. ## What do the colours mean? The shading carries one fact and one fact only: **the size and direction of that month's return.** Every figure is also printed as a number in its cell, so the colour is a way to find things quickly, never the only way to read a value. - **Green** means the month ended positive; **red** means it ended negative. - **Stronger colour means a bigger move.** The intensity is scaled against the strongest single month currently in the grid, so the most saturated green cell is the best month on view and the most saturated red cell is the worst. Every non-zero month keeps at least a faint tint, so a small move is still visible as a colour rather than disappearing. - **No colour means no move or no data.** A month that ended exactly flat is left untinted, and so is a month with no result yet — a blank cell has no figure in it, which is how you tell the two apart. Because the scale is relative to what is on view, the shading is a ranking within your own backtest, not an absolute scale you can compare between two different strategies. A strategy whose worst month was −4% will still show a deep red cell for it; that red means "worst month here", not "−20%". ## What does the vs. Benchmark switch do? The **vs. Benchmark** switch above the grid turns the month cells and the **Total** column into *excess* figures — your strategy's return minus the [benchmark's](/docs/getting-started/benchmark) return for the same month — so a green cell then means "beat the benchmark that month" rather than "made money that month". The switch leaves **DD** and **NP/DD** unchanged, since those describe the strategy's own path. The result is in percentage points; see [excess return](/docs/analysis/excess-return). ## What does the year detail above the grid show? Selecting a year — by clicking its row or the year itself — fills three stacked panels above the grid with just that year, and the most recent year is selected when the page opens. - **Equity**, labelled "vs benchmark", is that year's value curve for your strategy against the benchmark. See [equity curve](/docs/analysis/equity-curve). - **Drawdown** is how far below its previous peak the strategy sat on each day of that year. - **Monthly returns** is the same twelve months as bars, green above the line and red below. Hovering any of the three highlights the matching point on the other two. Only the **Monthly returns** bars follow the **vs. Benchmark** switch; the **Equity** and **Drawdown** panels always show the strategy's own figures. ## How does Fincanva handle it? - Four KPIs sit above the grid: **Avg month**, **Best month**, **Worst month** and **Positive months**. They cover the whole backtest, not the selected year, and they always describe the strategy itself even when the **vs. Benchmark** switch is on. See [monthly and yearly average](/docs/analysis/monthly-and-yearly-average), [best month and worst month](/docs/analysis/best-month-and-worst-month) and [positive months](/docs/analysis/positive-months). - Sorting, year selection and the **vs. Benchmark** switch are display choices; none of them re-runs the backtest. - The three simulation assumptions — **Costs & interests**, **Taxes** and **Reinvest profits** — change which set of figures the grid reads. - With no completed run there is nothing to draw, and the page reads "No monthly data for this run." ## What does it look like in practice? Say you want the worst month of a ten-year backtest without reading a hundred and twenty numbers. Scan for the darkest red cell: it sits in the **Mar** column of the 2020 row and reads −18.4%. That single cell is also the figure the **Worst month** KPI shows above the grid, and the one the metrics table reports as **Worst month**. Now read the rest of that row across. **Total** for 2020 is +6.1% — the year finished up despite that March — and **DD** is −22.0%, deeper than the worst single month, because the fall ran across the end of February and into March rather than fitting inside one calendar month. That gap between −18.4% and −22.0% is the point of having both columns: a monthly grid cuts the path at month boundaries, and a drawdown does not. Finally, click 2020 to load its detail panels: the **Equity** curve shows the drop and the recovery inside the year, and the **Monthly returns** bars show one deep red bar in March followed by green ones. ## What counts as a good pattern? The matrix describes distribution, not quality. A row of many small greens and a row with one huge green and several reds can both total the same, and they tell you different things about where the year's result came from — the second one depended on a single month, so it would look very different had the backtest window started or stopped a few weeks earlier. Reading a column down instead of a row across shows whether one calendar month recurs as strong or weak. Bear in mind that ten years give only ten samples per month, which is far too few to distinguish a pattern from coincidence — and a pattern in past months is not a statement about future ones. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/negative-dividends # Negative dividends A negative dividend is a dividend that counts against a strategy instead of for it, which happens when the strategy holds a short position in a stock that pays a dividend. When you are short a stock, you have borrowed the shares and sold them, so on the ex-dividend date you owe the dividend to whoever lent them to you — the cash a long holder would have received becomes cash the short position pays out, and it appears on the **Negative dividends** line of the P&L breakdown. **Also seen as:** short dividend, dividend payable on a short ## Why a dividend can show as negative The sign of a dividend follows which way the position points. Hold a stock long and its dividend is income — a gain that lands on the "Dividends" band. Hold the same stock short and the dividend flips into a cost: the lender of the borrowed shares is still entitled to the dividend, so the short position has to pay it, and it lands on the "Negative dividends" band on the costs side of the [P&L breakdown](/docs/analysis/p-l-breakdown). It is the mirror image of a normal dividend, not a data error. ## How does Fincanva handle it? - Negative dividends appear on the negative stack of the P&L breakdown, under the label "Negative dividends", kept separate from the positive "Dividends" line. - They arise only when a strategy runs short positions — for example a beta-neutral or short-enabled allocation method — so a long-only strategy never shows a negative dividend. ## What does it look like in practice? A strategy is short 100 shares of a stock that pays a dividend of 0.50 per share. On the ex-dividend date the short position owes 100 × 0.50 = 50. That 50 is a negative dividend: it reduces the strategy's P&L and shows on the "Negative dividends" band — the exact mirror of the 50 in dividend income a holder who was long the same 100 shares would have collected on the "Dividends" band. See [dividends and splits](/docs/analysis/dividends-and-splits) for how the same event is recorded on a long position. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/p-l-breakdown # P&L breakdown The P&L breakdown is a stacked view of a strategy's profit and loss that splits the total result into the separate gain and cost components that produced it. On the [capital chart](/docs/analysis/capital-chart)'s **P&L breakdown** view, gains stack upward and costs and losses stack downward, while a single **Portfolio** line traces the net total P&L across the whole period — so you can see not just how much a strategy made or lost, but where that money came from and where it went. **Also seen as:** profit and loss breakdown, P&L attribution ## What the P&L breakdown splits your result into The breakdown separates every unit of profit and loss into named components, split into a gains side and a costs-and-losses side. - **Gains (stacked upward):** Realized profit, Open profit, Dividends, Interest received. - **Costs and losses (stacked downward):** Realized loss, Open loss, Negative dividends, Interest paid, Costs, Taxes. The net of the two sides is the **Portfolio** line — the strategy's total P&L. Realized profit and loss come from positions already closed, while open profit and loss come from positions still held; the two are kept apart because only the open side still moves with the market (see [realized vs open P&L](/docs/analysis/realized-vs-open-p-l)). The **Costs** band here is the same charge that separates gross from net on a position — trading fees plus slippage; see [gross vs net](/docs/analysis/gross-vs-net) for how the two figures sit either side of it. ## How does Fincanva handle it? - Each component is a coloured band; gains stack above the axis and costs and losses below it, so the height on each side shows how much came from each source. - The breakdown responds to the Costs, Taxes, and Reinvest simulation assumptions: the Costs, Interest paid, and Taxes bands are zero when those assumptions are off, and costs are off by default for every account. - [Negative dividends](/docs/analysis/negative-dividends) and [Interest paid](/docs/analysis/interest-received-and-paid) appear only when a strategy uses short positions or borrows to fund leverage. ## What does it look like in practice? A strategy ends a period with the "Portfolio" line at +4,000, and the breakdown shows line by line how it got there. On the gains side: Realized profit +3,200, Open profit +1,900, Dividends +600, Interest received +50 — a total of +5,750. On the costs-and-losses side: Costs −900, Taxes −500, Realized loss −250, Open loss −80, Interest paid −20 — a total of −1,750. The two sides net to +5,750 − 1,750 = +4,000, which is exactly where the **Portfolio** line finishes. Reading the bands tells you the 4,000 was earned mostly from realized and still-open gains, and trimmed by roughly 1,750 of costs, taxes, and losing positions. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/positions-detail-drill-down # Positions detail drill-down The positions detail drill-down is the expansion of one symbol into the individual positions the strategy took in it, and of each position into the fills, dividends and splits that made it up. It exists to answer a question a summary cannot: not "what did this instrument earn overall", but "what exactly happened to *this* position, from the trade that opened it to the trade that closed it". **Also seen as:** the position drill-down; trade history. ## How do you follow one position from entry to exit? The detail opens in three layers, each one narrowing the scope. 1. **The symbol** — a row of the [positions summary table](/docs/analysis/positions-summary-table), covering everything the strategy ever did in that instrument. 2. **Its positions** — one row per position the strategy held in that symbol, with its **Start** and **End** dates, its **Side** (long or short), its **Max contracts** — the largest [quantity](/docs/strategies/contracts) it ever held — and the same money columns as the summary: Gross, Costs, Net, Dividends, [Total P&L](/docs/analysis/total-p-l). 3. **Inside one position** — its **Trade history**, one row per fill, and its **Dividends & splits**, one row per event. A position that is still open at the end of the run has no closing fill, so its result is still [open rather than realized](/docs/analysis/realized-vs-open-p-l). ## What does each trade row record? Each row of the trade history is one fill: its **Execution date**, its [**Execution time**](/docs/strategies/execution-time) — Open, IntraBar or Close, which fixes the price the fill books at — its **Side**, the **Contracts** filled, the **Actual execution price** it filled at, then **Gross**, **Costs** and **Net** for that fill, and the [**Reason**](/docs/strategies/exit-reason) it happened when the fill closed a position. Realized results belong to closing fills, so an opening fill shows a dash for its Gross and no Reason — nothing is realized yet at that point in the position's life. ## How does Fincanva handle it? - Trades are listed newest first, and fills sharing a date are ordered by execution time — Open, then IntraBar, then Close — so a same-day sequence reads in the order it happened. - Prices are in the instrument's own currency and profit-and-loss figures are in the account's base currency; a position in a foreign-listed instrument therefore mixes two currencies across one row, by design. - Dividends and splits are merged into a single event stream per position, newest first — see [dividends and splits](/docs/analysis/dividends-and-splits) for how each row reads. - Each level has its own empty state: "No positions for this symbol.", "No trades.", and "No dividends or splits." - Gross, Costs and Net mean the same thing at every level: [gross before costs, net after](/docs/analysis/gross-vs-net) — for one fill, for one position, or for the whole symbol. ## What does it look like in practice? A symbol's row opens to show three positions. You take the second: it starts in March, ends in September, is long, and reached a maximum of 40 contracts. Opening it, the trade history shows a Buy of 25 contracts at the Open in March with no Reason and no realized result, a second Buy of 15 contracts in May that took it to its peak of 40, and a Sell of all 40 in September IntraBar, this time carrying a realized Gross, its Costs, its Net, and a Reason of stop loss. Beneath, the Dividends & splits stream shows the two dividends collected while the position was held. Those five rows are the position's whole life: how it was built, what it collected on the way, why it ended, and what it kept. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/positions-summary-table # Positions summary table The positions summary table is the one-row-per-instrument view of a backtest's trading: every symbol the strategy ever held gets a single row summarising what that symbol did over its whole life in the simulation. It is a lifetime summary, not a list of trades — a symbol bought and sold five separate times still occupies one row, with its results added together. **Also seen as:** the **By symbol** table, per-symbol P&L ## What does each row of the positions summary tell you? Each row reads left to right as one symbol's whole story, in money: - **Symbol** — the instrument, with its ticker and name. - **Asset type** — what kind of instrument it is. - **Gross** — the symbol's trading profit or loss before costs. - **Costs** — the trading fees plus slippage it paid over its life. - **Net** — [gross minus costs](/docs/analysis/gross-vs-net). - **Dividends** — the dividend income it realized, counted apart from trading. - [**Total P&L**](/docs/analysis/total-p-l) — the symbol's whole-life money result, dividends included. Because every figure is a lifetime total, the table answers "which instruments actually carried this strategy, and what did they cost me?" rather than "what happened on a given day". Every one of those columns is **money**, which is what separates this table from the [metrics table](/docs/analysis/metrics-table): that page reports the strategy's percentages, this one reports each instrument's cash result. The last column is therefore [Total P&L](/docs/analysis/total-p-l) — a money figure — and not the percentage that the metrics table calls [total return](/docs/analysis/total-return). ## How does Fincanva handle it? - **The positions history page is included from the Starter plan.** The Free plan does not open it, so the summary table is not shown there at all; Starter, Advanced, Ultimate and Professional include it. See [what each plan includes](/docs/account-security/what-each-plan-includes). - One row per symbol ever held, whether or not it is still held at the end of the run — a symbol that was traded and fully exited still has its row. - Every money column is in the account's base currency, so rows are directly comparable to each other regardless of where each instrument trades. - Rows are sorted by **Total P&L**, largest first, until you sort by another column; the table is searchable by symbol and loads more rows as you scroll. - Above the table, four figures summarise the same data set: how many symbols were traded, how many of them ended profitable, the single best symbol by money, and the total trading costs — the sum of fees and slippage across every symbol. - With no trading at all the table shows "No symbols in this backtest." - Each row opens into the [positions detail drill-down](/docs/analysis/positions-detail-drill-down) for that symbol. ## What does it look like in practice? A symbol's row reads: Gross 3,294 · Costs 12 · Net 3,282 · Dividends 129 · Total P&L 3,411. Read aloud: this instrument made 3,294 on price movement across every position the strategy took in it, paid 12 in fees and slippage to do so, kept 3,282 from trading, collected 129 in dividends along the way, and finished 3,411 up overall. A neighbouring row with a large Gross but a Costs figure many times bigger tells the opposite story in the same five numbers. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/positive-months # Positive months Positive months is the share of months in the backtest period that closed with a positive return, expressed as a percentage. The [metrics table](/docs/analysis/metrics-table) lists it as "Positive months (%)" in the **Monthly performance** group. It is a count-based measure: every month contributes equally whether it gained 0.1% or 12%, so positive months describes how *often* a strategy went up, never by how much. **Also seen as:** monthly win rate, hit rate, up months ## How is positive months calculated? Positive months divides the number of months whose return was above zero by the number of months in the period. $$ \text{positive months} = \frac{\text{number of months with a return above } 0}{\text{total number of months in the period}} $$ where: each month's return is the figure the monthly returns view shows for that month, and the total is every month of the simulated period. ## What counts as a good value? A figure above 50% means more months closed up than down, and a figure near 100% means the strategy rarely had a losing month. On its own the number says nothing about magnitude, so it can be high while the outcome is poor: a strategy that gains a little in eleven months and loses heavily in the twelfth can still report over 90% positive months. Read it beside [best month and worst month](/docs/analysis/best-month-and-worst-month), which show the size of the extremes, and [max drawdown](/docs/analysis/max-drawdown), which shows the deepest fall. ## How does Fincanva handle it? - Positive months appears as "Positive months (%)" in the **Monthly performance** group of the metrics table, shown as a whole-number percentage. - The same measure is repeated as a KPI on the monthly returns view, labelled "Positive months", and per calendar year in the by-year metrics table as "Positive months (%)". - It is computed over the months of the backtest period, from the same month-by-month return series the [monthly returns heatmap](/docs/analysis/reading-the-monthly-returns-heatmap) displays. - A month that closes exactly flat is not a positive month — the test is a return above zero. ## What does it look like in practice? A ten-year backtest covers 120 months, and 84 of them closed with a positive return. Positive months is 84 ÷ 120 = 0.70, displayed as 70%. That means roughly seven months in ten went up. It does not mean the strategy was up 70% of the time by value: the remaining 36 months could each have been small losses, or a handful of them could hold the whole of the run's max drawdown, and the 70% figure would read the same either way. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/projection-cone # Projection cone A projection cone is the fan of values a strategy could reach over a chosen horizon, drawn from many possible paths. Each path — a scenario — is built by drawing daily returns out of the strategy's own backtest one day after another and compounding them from today's value; at every future day the cone marks where the middle of all those paths falls. It shows the spread of outcomes the strategy's past makes plausible, never the one that will happen. In Fincanva it is drawn on the [Projection tab](/docs/analysis/see-where-a-strategy-could-go-with-the-projection-tab). **Also seen as:** Monte Carlo projection, fan chart, percentile cone ## What do the bands of a projection cone show? The bands are percentiles of the paths, read day by day. The light band, **5–95%**, holds the middle 90% of the scenarios at each future day; the darker band, **25–75%**, holds the middle half; the **Median** line is the middle scenario, with half of the paths ending above it and half below. So one outcome in 20 lands below the light band and one in 20 above it, and the cone widens with the horizon because uncertainty compounds as days add up. ## Which ways of drawing days can a projection use? Three **Method** options decide how a future day is drawn from the past, each keeping a different property of the history: - **Blocks of days** draws runs of consecutive days, so calm and turbulent spells stay together — a block bootstrap. - **Single days** draws each day independently, keeping every day's size but shuffling their order — the classic independent bootstrap. - **Gaussian** draws from a normal distribution with the history's average and volatility, which makes very large days rarer than markets produce them. The Projection tab's guide says what each one assumes in more depth — see [what each projection method assumes](/docs/analysis/see-where-a-strategy-could-go-with-the-projection-tab#what-does-each-projection-method-assume). ## Does drawing more scenarios make a projection more accurate? No — more **Scenarios** make the cone's edges steadier, not the projection truer. With few paths, the 5th and 95th percentiles rest on a handful of extreme scenarios and shift noticeably if the draw changes; with many, they settle. How wide the cone is comes from the strategy's history and the method, and does not change because more paths were drawn. ## What does the Change row under a projection show? **Change** is how far each percentile of the cone ends from today's value, as a percentage. The table under the chart reads the cone at the horizon, one column per percentile — P5, P25, P50, P75 and P95 — and gives each one twice: as a **Value**, and as a **Change** from the value the cone starts from. A P5 Change of −12% means that one scenario in 20 ended at least 12% below today's value; a P50 Change of +28% means the median scenario ended 28% above it. It looks forward, from today to the horizon — not back over the backtest. ## How does Fincanva handle it? - The cone starts from the last value of the backtest and runs one to five years ahead, a year being 252 trading days; the **Horizon** and **Scenarios** your plan allows are on [the Projection tab's guide](/docs/analysis/see-where-a-strategy-could-go-with-the-projection-tab#how-far-ahead-does-my-plan-let-me-project). - It projects the figures the tab is showing: with costs, interest or taxes switched on under **Simulation settings**, it draws on the net daily returns — see [simulation assumptions](/docs/backtesting/simulation-assumptions). - The same request on the same backtest always returns the same cone. - Under the chart the tab restates it: "This is not a forecast." ## What does it look like in practice? A strategy worth 100,000 today is projected three years ahead with **Blocks of days** and 1,000 scenarios. The **Median** ends at 128,000, the **25–75%** band runs from 112,000 to 146,000, and the **5–95%** band from 91,000 to 178,000. Read it as: half the paths built from this strategy's own past ended between 112,000 and 146,000, and one in twenty ended below 91,000. A history that happened to be kind makes a kind cone too, which is why the figure is a range of what the past allows, not an expectation. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/realized-vs-open-p-l # Realized vs open P&L Realized P&L is the profit or loss from positions a strategy has already closed, while open P&L is the profit or loss from positions it still holds, valued at their current price. The difference is whether the result is final: realized P&L is locked in and no longer moves, whereas open P&L is a mark-to-market figure that keeps changing with the market until the position is sold. **Also seen as:** unrealized P&L, paper profit, mark-to-market P&L ## What separates realized P&L from open P&L Realized P&L is banked and open P&L is still in play. A closed position's gain or loss is settled — selling it turned the paper result into a realized one that no later price move can change. An open position's gain or loss is unrealized: it is measured by marking the position to its current price, so it rises and falls every day the position is held and only becomes realized when the position is closed. In the [P&L breakdown](/docs/analysis/p-l-breakdown) each side has its own bands — "Realized profit" and "Realized loss", "Open profit" and "Open loss". ## How does Fincanva handle it? - The P&L breakdown shows realized and open results as four separate bands, so you can tell locked-in profit and loss from profit and loss that is still exposed to the market. - The realized bands stop changing once positions close; the open bands revalue as prices move over the period. ## What does it look like in practice? A strategy holds two positions. It sells the first for a gain of +800 — that +800 is realized profit, banked, and it will not change no matter what the market does next. The second it still holds, and at today's price it is up +450 — that +450 is open profit, and it will keep moving until the position is sold. The strategy's total P&L today is +1,250, but only the +800 is locked in; the +450 could grow, shrink, or turn negative before it is realized. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/regime-timeline # Regime timeline The regime timeline is the band under the growth chart on a strategy's **Performance Metrics** tab that shows, day by day, whether the strategy was running its normal **Risk-On** allocation or its defensive **Risk-Off** one. It lines up with the chart above it, so a Risk-Off stretch sits directly under the part of the curve it shaped, and beside each row it gives the share of time spent in each: "Risk-Off 18% · Risk-On 82%". It appears only on a strategy with an active [risk condition](/docs/strategies/risk-condition) — without one, a strategy is Risk-On from start to finish and there is nothing to show. **Also seen as:** regime band, time in Risk-Off, Risk-On/Risk-Off timeline ## How do I read the regime timeline? Each row is one strip running along the same time axis as the growth chart above it. - **Grey** marks the days in Risk-On, **solid dark grey** the days in Risk-Off. The band uses neutral shades on purpose: green and red already mean gain and loss everywhere else in the app. - A small **triangle** marks a switch whose risk condition was set to rebalance immediately — see [auto-rebalance on flip](/docs/strategies/auto-rebalance-on-flip). A switch without one waits for the next scheduled rebalance. - Hovering a stretch names its regime and its first and last day, in the form "Risk-Off · … to …". - Beside the row, the time shares — "Risk-Off 18% · Risk-On 82%" — or, for an element that never switched, "always Risk-On". What Risk-On and Risk-Off mean for the allocation is on [Risk-On and Risk-Off](/docs/strategies/risk-on-and-risk-off). ## Why does a Combined show more than one row? Because on a [Combined](/docs/getting-started/combined) the rules can act at two levels, and each keeps its own timeline. The first row, labelled **Combined**, is the Combined's own rule — the one that watches the portfolio as a whole. Below it comes one row per strategy inside it, each following that strategy's own rule. A Combined whose own rule is off still shows its row, grey from end to end, so its strategies' rows can be read against it. A single strategy shows one row: its own. ## How does Fincanva handle it? - The timeline appears on **Performance Metrics**, under the growth chart, whenever the strategy or any strategy inside a Combined has an active risk condition. The band has no plan of its own: it follows the risk conditions, and which plan includes those is stated on [Risk-On and Risk-Off](/docs/strategies/risk-on-and-risk-off). - It follows the tab's **Simulation settings**. A rule that watches the strategy's own value can switch on different days when **Costs & interests**, **Taxes** or **Reinvest profits** change what that value was, so the band is redrawn for the figures the tab is showing. - It reads the switch dates the backtest itself recorded; it is not recomputed or estimated after the fact. - A simulation stored before the regime timeline existed shows no band until the backtest is run again. ## What does it look like in practice? A strategy with a trend-following risk condition is backtested over twenty years. Its timeline is grey for most of the period with three dark stretches: a long one through 2008, a short one in early 2020, and one across most of 2022; the row reads "Risk-Off 14% · Risk-On 86%". Two of the three switches into Risk-Off carry a triangle, so those rebalanced the same day; the third waited for the monthly rebalance. Laid under the growth chart, the 2008 stretch sits under the flatter part of the curve — the defensive allocation was in charge while the market fell. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/return-windows # Return windows Return windows are the four fixed periods Fincanva reports a return over: **1M**, **1Y**, **YTD** and **MTD**. Two of them are trailing — 1M and 1Y count back one month and one year from the end of the data — and two are calendar-anchored, since MTD starts at the beginning of the month the data ends in and YTD at the beginning of that year. They appear as columns on the strategies list and on screener results, which is why the same strategy can show four different return figures side by side. **Also seen as:** trailing return, rolling return, month to date, year to date ## What does each return window cover? Each window has a fixed start rule and the same end point: the last bar of the data. The start rules below are the ones a **strategy's** windows follow. The screener's per-symbol columns carry the same four names but are anchored differently — see [do the screener's columns work the same way?](#do-the-screeners-columns-work-the-same-way) below. | Window | Starts | The app's own description | |---|---|---| | 1M | one month back from the last bar (trailing) | "Return over the last month." | | 1Y | one year back from the last bar (trailing) | "Return over the last 12 months." | | MTD | the first day of the calendar month the last bar falls in | "Return since the start of the month." | | YTD | the first day of the calendar year the last bar falls in | "Return since the start of the year." | In words: 1M and 1Y answer "how did this do over the last month / last year", regardless of where those periods fall on the calendar. MTD and YTD answer "how has this done so far this month / this year", so they get longer the further into the month or year the data runs, and start over when a new one begins. If you have seen the trailing windows written as **M1** and **Y1**, those are older labels that have been retired: **1M** and **1Y** are the names the product uses everywhere today, for the same two windows. ## Are the windows trailing or calendar-anchored? 1M and 1Y are trailing; MTD and YTD are calendar-anchored. On a strategy, a trailing window is built by rolling back one month or one year from the last bar of its data and then snapping forward to the first available price bar on or after that date — so a 1M figure covers approximately, not exactly, one month, because markets are closed on some days. A calendar-anchored window ignores the length of the period entirely and simply starts at the first day of the month or year that the last bar falls in, which makes MTD and YTD partial periods of whatever length the calendar happens to give them. All four end at the same point. ## Do the screener's columns work the same way? No — and this is the one place the four names mislead. A strategy's windows end at **the last bar of that strategy's run**; the screener's per-symbol columns of the same names end at **today**, because they describe an instrument's own live price history rather than a stored backtest. Two figures labelled "YTD" side by side can therefore cover two different periods. - The screener's **YTD** runs from **1 January of the current year** to today. - The screener's **MTD** runs from the **first day of the current month** to today. - The screener's **1Y** is the trailing twelve months up to today, drawn as the sparkline beside the return. Those are fixed calendar anchors: they ignore the trading calendar and simply take the price on or before the anchor date. That is a different convention from a strategy's trailing windows, which roll back from the run's last bar and then snap forward to the first available price bar. **Do not read a screener column and a strategy column as the same measurement** — they answer the same question about two different things, over two periods that only coincide by accident. ## Why can a window end before today? Because the windows end at the last bar of the data, not on today's date. For a strategy, that last bar is the final day of its [backtest](/docs/getting-started/backtest) — so a strategy that was last run a week ago shows an MTD that stops a week ago, and its four window figures do not move until the strategy is run again. "YTD" therefore means year-to-date-of-the-data, and comparing two strategies whose runs ended on different dates compares two slightly different windows. ## How does Fincanva handle it? - The strategies list shows all four as sortable columns, in the order "MTD", "1M", "YTD", "1Y", as percentages to one decimal place and coloured by sign. - On screener results, the **Returns** tab shows "YTD", "1M" and "MTD" as numeric columns and "1Y" as a mini line chart with the return percentage beside it; each header carries the hover description quoted in the table above. - The windows are period returns, not annualized figures: 1M is one month's return as it stands, never scaled up to a yearly rate. See [annualization](/docs/analysis/annualization) for the figures that are scaled. - The [live book](/docs/getting-started/live-book) summary strip uses the same four windows as a selector: pick **MTD**, **YTD**, **1Y** or **1M** and every panel recomputes against that window. ## What does it look like in practice? A strategy's backtest ends on 18 March. On that run, MTD covers 1 March to 18 March. 1M is trailing, so it rolls back one calendar month to 18 February, takes the first price bar on or after that date, and runs to 18 March. YTD covers 1 January to 18 March. 1Y is trailing over the same rule, from mid-March a year earlier to 18 March. Open the same strategy in April without re-running it and none of the four figures change — they still end on 18 March, and MTD still covers 1–18 March rather than the days of April, because every window is anchored to the run's last bar rather than to today's date. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/return-to-drawdown-ratio # Return-to-drawdown ratio The return-to-drawdown ratio is a strategy's return over a period divided by the size of its [max drawdown](/docs/analysis/max-drawdown) in that same period — the return earned per unit of worst peak-to-trough loss. It answers "how much return did this strategy produce for the deepest fall it put up with?", which a return figure on its own cannot say. It is a standard, publicly known ratio, not a proprietary Fincanva measure. **Also seen as:** NP/DD, NPDD, NP max DD, net profit ÷ maximum drawdown ## How is the return-to-drawdown ratio calculated? The ratio divides the period's return by the absolute size of the max drawdown, so the drawdown's minus sign does not flip the result. $$ \text{return-to-drawdown ratio} = \frac{\text{return}}{\lvert\text{max drawdown}\rvert} $$ where: return is the period's return (the whole-period return for the headline figure, that year's return for a per-year figure), max drawdown is the largest peak-to-trough fall in the same period, and the vertical bars mean its absolute value — the drawdown's size without its minus sign. ## Why is it a ratio and not a percentage? The return-to-drawdown ratio is a **plain number**, not a percentage, because it divides one percentage by another and the units cancel out. A value of 4.0 means the return was four times the size of the worst drawdown; it does **not** mean 4%, and it does not mean 400%. Since a percentage divided by a percentage has no unit, the figure is shown as a bare number everywhere it appears in Fincanva — the metrics table, the by-year table, the [Strategy analytics](/docs/analysis/strategy-analytics) page, and the heatmap's **NP/DD** column. Reading it as a percentage is the most common mistake made with this metric, and it is why the canonical name carries the word *ratio*. ## How does Fincanva handle it? - The metrics table shows it in the **Drawdown** group as the row **Return-to-drawdown ratio**, as a plain number. - The by-year table gives a **Return-to-drawdown ratio** column per calendar year. The Strategy analytics page gives one bar per strategy inside a Combined, in the column its **Each strategy, against the Combined** card labels **Return / fall** — the same ratio under a shorter name, because that card puts four figures side by side. - The [monthly returns heatmap](/docs/analysis/reading-the-monthly-returns-heatmap) carries the same per-year figure in its compact **NP/DD** column — net profit divided by maximum drawdown, the same quantity under an abbreviated label. - It turns negative when the period's return is negative, because the denominator is always a positive size: a negative ratio means the strategy lost money over that period. - Where the figure is not available for a period, Fincanva shows "—" rather than a number. ## What does it look like in practice? A strategy returns +80% over its backtest and its max drawdown in the same period is −20%. The ratio is 80 ÷ 20 = **4.0**: four units of return for every unit of the worst fall. Compare a second strategy that also returns +80% but whose max drawdown was −40%. Its ratio is 80 ÷ 40 = 2.0. On return alone the two look identical; the ratio separates them by what each went through to get there. ## What counts as a good value? A higher ratio means more return per unit of the worst fall. A ratio above 1.0 means the period's return was larger than its deepest drawdown; below 1.0, the deepest fall was larger than the return earned; a negative value means the period's return was itself negative. The ratio uses only the *single deepest* fall, so it says nothing about how often drawdowns happened or how long they lasted — read it next to [longest drawdown](/docs/analysis/longest-drawdown) for duration, and the [Sharpe ratio](/docs/analysis/sharpe-ratio) for return measured against overall variability instead of one worst-case event. It is also period-bound: a short window containing one mild dip can produce a very high ratio. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/risk-free-rate # Risk-free rate The risk-free rate is the short-term reference interest rate that risk-adjusted metrics subtract from a strategy's return, so that only the return earned *above* a near-riskless baseline counts as the reward for taking risk. It is the return you could have earned over the same period with essentially no risk, and it is the baseline the [Sharpe ratio](/docs/analysis/sharpe-ratio) and [Sortino ratio](/docs/analysis/sortino-ratio) measure excess return against. **Also seen as:** riskless rate, reference rate ## How Fincanva sets the risk-free rate Fincanva uses a real market-data series rather than a fixed number: the 3-Month US Treasury Bill secondary-market rate, published by FRED as the series `DTB3`. A short-term government bill is the standard textbook proxy for a near-riskless return, because you are almost certain to be repaid over such a short horizon. The series is time-varying, so the rate is matched to your backtest's own date window and reported as the period average. ## What risk-free rate is used where the series has no data? For any month of your backtest window that falls outside the DTB3 series — before its first observation or after its last — Fincanva uses a flat **2% a year** in its place, and the period average blends those months with the months the series does cover. A window that sits entirely outside the series is measured against 2% throughout. This stand-in belongs to the risk-free rate only: it is not the rate charged on borrowed money, which is set separately — see [interest-rate markups](/docs/backtesting/interest-rate-markups). The stand-in covers dates outside the series, not a missing series. If the series itself could not be loaded, backtests would not run at all rather than run on an assumed rate. ## How does Fincanva handle it? - The rate comes from the FRED `DTB3` series (3-Month US Treasury Bill), a live market-data series — not a hardcoded constant. - It is matched to the first and last dates of your backtest and shown as the period average for that window. - Months of the window outside the series are filled with a flat 2% a year, blended into the period average. - It feeds the excess-return term of the Sharpe ratio and the Sortino ratio: both subtract it, stand-in months included, before dividing by a risk measure. - The **Sharpe** a screener shows for an instrument does not subtract it — see [Sharpe ratio](/docs/analysis/sharpe-ratio#does-the-screeners-sharpe-subtract-the-risk-free-rate). ## What does it look like in practice? Suppose a strategy returns 8% over a year while the risk-free rate averaged 3% across the same window. Only the 5 percentage points *above* the risk-free rate are the reward for taking risk — the first 3% is a return you could have earned with essentially no risk at all. The Sharpe ratio divides that 5% excess by the strategy's volatility, so subtracting the risk-free rate is exactly what turns "total return" into "reward for the risk you took". A strategy that beat cash by a wide margin and one that barely beat it can post the same headline return but very different excess returns. *The risk-free rate shown is a historical average over your backtest's window, not a rate available to you now or a return you can count on.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/rolling-correlation # Rolling correlation Rolling correlation is the correlation between two return series measured over a window that slides forward through time, producing one correlation value per date instead of a single figure for the whole period. Where a [full-period correlation](/docs/analysis/correlation-matrix) compresses years of behavior into one number, a rolling correlation keeps the timeline: it shows when two assets moved together, when they went their own ways, and — most usefully — whether the relationship held up when it mattered. A full-period correlation of 0.4 can be the average of a long calm stretch near 0.1 and a few violent months near 0.9, and the two situations mean entirely different things for a portfolio. **Also seen as:** moving-window correlation, rolling-window correlation, time-varying correlation ## How is a rolling correlation calculated? A rolling correlation applies the ordinary correlation calculation repeatedly, each time to the most recent window of observations only. $$ \rho_t = \operatorname{corr}\big(r^A_{t-w+1 \dots t},\; r^B_{t-w+1 \dots t}\big) $$ where: $r^A$ and $r^B$ are the two series' per-period returns, $w$ is the window length in periods, and $\rho_t$ is the correlation of the two series across the window ending at date $t$. Each step forward drops the oldest observation and adds the newest, so the window "rolls" and the output is a series in the range −1 to +1. Two properties follow from the shape of that calculation. The series cannot begin until the window is full, so the first $w$ periods of history produce no value at all. And the window length is a trade-off: a short window reacts quickly to a change in the relationship but jumps around on noise, while a long window is smooth but slow, still reporting a crisis-era correlation months after the crisis ended. Windows from a few months to a few years are standard practice. **Fincanva's window is one year.** Wherever Fincanva computes a rolling correlation it rolls a one-year window, so every value you read is the correlation of the twelve months ending on that date — not the whole history, and not the last quarter. The window is part of the reading, not a technical footnote: a correlation of 0.8 on a one-year window and a correlation of 0.8 on a one-month window are different statements about the same pair. It also fixes where the series can start: the first year of any pair's shared history produces no value, because until then there is no full window to compute. ## Why does correlation spike in a crash? Correlation between risk assets rises sharply in a sell-off because in that regime a single force — investors reducing exposure across the board — dominates the individual reasons the assets would otherwise move apart. Positions are sold because they can be sold, not because of what they are, so shares, credit, and often assets held precisely as diversifiers all fall in the same weeks. The practical consequence is uncomfortable: diversification measured on calm data overstates the protection it provides in exactly the periods it is meant to protect against. A pair of holdings that spent a decade at 0.2 and combined into a genuinely smoother portfolio can behave like one holding for the three months that produce most of the [max drawdown](/docs/analysis/max-drawdown). A rolling correlation is how that becomes visible; a single full-period figure hides it by construction. ## How can two sleeves decouple, then move together? Take two sleeves of a strategy — a broad equity sleeve and a corporate-credit sleeve — and compute their correlation on a rolling window across a ten-year backtest. | Period | Rolling correlation | What it means | |---|---|---| | Calm years (most of the decade) | 0.25 to 0.40 | the sleeves move partly independently; combining them lowers portfolio [volatility](/docs/analysis/volatility) | | The three crash months | 0.85 | both sleeves fall together; the pair behaves close to a single asset | | Full-period figure | 0.42 | a number that describes neither regime | The full-period 0.42 is not wrong — it is the correct average — but it is the answer to a question nobody asked. The diversification benefit the 0.25–0.40 stretch implies is real for nine years and largely absent for the quarter that produced the worst of the drawdown, and only the rolling series shows that the two facts are about the same pair of sleeves. {/* VISUAL: chart — one rolling-correlation series across ten years, y-axis -1 to +1, crash quarter shaded, full-period average as a flat dashed line; axis labelled "rolling window", never a window length — tracked in VISUAL_BACKLOG */} ## What counts as a good value? There is no good value, only a reading. A rolling correlation near +1 means the two series have been moving almost identically over that window, near 0 means recent moves have been largely unrelated, and near −1 means they have been moving in opposite directions. What a rolling series adds over a single figure is *stability*: a pair that holds a steady 0.3 through several market regimes has behaved differently from a pair averaging 0.3 by alternating between 0.0 and 0.9, even though both report the same full-period number. Correlation also says nothing about magnitude — two series can be perfectly correlated while one moves five times as far, which is what [beta](/docs/analysis/beta) measures instead. Fincanva does not tell you which correlations to seek or avoid in a portfolio — see [Is this financial advice?](/docs/investing-theory/is-this-financial-advice). ## Does Fincanva show a rolling correlation? Fincanva does not currently display a rolling-correlation chart on any screen in the app. Correlations themselves are shown: a Combined's analysis has a correlations page carrying a [correlation matrix](/docs/analysis/correlation-matrix) and a comparison against [factors](/docs/analysis/factor-roster). What those tables report is a single figure per pair, scoped to the whole run or to one calendar year — not a value per date, which is what makes a series rolling. The term is documented here because it is standard vocabulary for reading a diversified strategy, and because the difference between one figure and a series is exactly what the sections above are about. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/semideviation # Semideviation Semideviation is the [volatility](/docs/analysis/volatility) of a strategy's losing days alone: the standard deviation of the daily returns below zero, annualized with the square root of 252 like volatility itself. It measures how much the losing days differed from one another — whether the bad days were all alike or ranged from mild to much worse — and leaves the winning days out entirely. **Also seen as:** semi-deviation, semi-standard deviation, downside volatility ## How is semideviation calculated? Keep only the days the strategy lost money, take the standard deviation of those returns around their own average, and annualize it: $$ \text{semideviation} = \sqrt{252}\times\text{standard deviation of the daily returns below zero} $$ where 252 is the number of trading days in a year, the same convention volatility uses. In words: it is volatility, measured on the losing days only. A strategy whose losing days were all about −0.5% has a low semideviation; one whose losing days ranged from −0.1% to −4% has a high one. ## Why is semideviation about 0.6 times volatility even for symmetric returns? Because it measures the losing days around their own average, not around zero, semideviation is not the share of the movement that went down. Take returns that are perfectly symmetric — as many ups as downs, of the same sizes: their losing half, measured around its own average, has a standard deviation of about 0.6 times the full volatility. So a semideviation near 0.6 × volatility is the ordinary case, not a sign that most of the movement was upward; a figure well above it means unusually uneven losing days. ## How does Fincanva handle it? - Performance Metrics shows it in the **Volatility and risk** group as **Semideviation (downside only)**, right under **Volatility**, annualized the same way — see [what every number in Performance Metrics means](/docs/analysis/what-every-number-in-performance-metrics-means). - It follows the same losing-days convention as the [Sortino ratio](/docs/analysis/sortino-ratio) on the **Components** tab. - A simulation computed before the row existed shows "n/a", never 0%. ## What does it look like in practice? Two strategies both show a **Volatility** of 15%. The first reads **Semideviation (downside only)** 9%, close to 0.6 × 15%: its losing days were about as varied as a symmetric distribution expects. The second reads 13%: its losing days ranged much more widely — most mild, a few far worse — even though its overall volatility is the same. ## What counts as a good value? Lower means more uniform losing days. Compare it with the strategy's own volatility first: about 0.6 × volatility is ordinary, well above means some losing days were much worse than the rest, which is worth reading beside the [Value at Risk](/docs/analysis/value-at-risk) and [Conditional Value at Risk](/docs/analysis/conditional-value-at-risk). Between strategies, compare it only over the same period. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/sharpe-ratio # Sharpe ratio The Sharpe ratio is a strategy's annualized return minus the risk-free rate, divided by its annualized volatility — the return it earned per unit of the variability it took on. Return on its own cannot say whether it was worth the ride; the Sharpe ratio puts return and variability in one number so two strategies with different returns and different swings can be compared on the same scale. It is a standard, publicly known ratio, not a proprietary Fincanva measure. **Also seen as:** Sharpe, risk-adjusted return ## How is the Sharpe ratio calculated? The Sharpe ratio subtracts the risk-free baseline from the strategy's annualized return, then divides what is left by the strategy's annualized volatility. $$ \text{Sharpe ratio} = \frac{\text{annualized return} - \text{risk-free rate}}{\text{annualized volatility}} $$ where: the numerator is the **excess return** — the part of the return earned above a near-riskless baseline — and the denominator is the strategy's [annualized volatility](/docs/analysis/volatility), the standard deviation of its returns scaled to a per-year figure with the square-root-of-252 convention. Because a percentage is divided by a percentage, the result is a plain number with no unit. ## Which risk-free rate does Fincanva use? Fincanva subtracts a real market rate, not a fixed assumption: the **3-Month US Treasury Bill secondary-market rate**, published by FRED as the series `DTB3` (a daily series running from 1954). A short-term government bill is the standard textbook proxy for a near-riskless return, and using a live series means the baseline moves with the era your backtest covers — a strategy tested through a high-rate decade is held to a higher bar than one tested through a near-zero-rate decade. The rate is matched to your backtest's own date window. The [risk-free rate](/docs/analysis/risk-free-rate) page is the canonical description of the series, including the flat 2% a year that stands in for months outside it. ## Which return feeds the Sharpe ratio, CAGR or AAGR? It depends on where you read it. On the metrics table — the **Sharpe** row and the KPI strip's **Sharpe ratio** — the annualized-return term follows the same **Reinvest profits** switch as the annualized-return row in **Performance Metrics**: it is the [CAGR](/docs/analysis/cagr) when Reinvest profits is on, and the [AAGR](/docs/analysis/aagr) when it is off. The by-year table and the [Strategy analytics](/docs/analysis/strategy-analytics) page always use CAGR, whatever the setting. This matters when comparing runs, because AAGR ignores compounding and usually reads higher than CAGR over multi-year gains. Two backtests of the same strategy that differ only in the Reinvest profits setting therefore feed different numerators into the metrics-table Sharpe ratio, and those Sharpe values are not directly comparable. ## Does the screener's Sharpe subtract the risk-free rate? No. The Sharpe a screener shows is return divided by volatility with no risk-free rate subtracted, unlike the Sharpe ratio a backtest reports. It is measured on the instrument's own adjusted price: its annualized return over a trailing window, divided by the annualized volatility of its daily price moves over the same window. - The **Sharpe** column on the **Returns** tab of a screener's results table covers the last 12 months. - The **Sharpe Ratio** filter covers the number of months you set in its **Months** input, from 1 to 36. **Positive Sharpe Ratio** is the same measure, keeping only values above zero. Because nothing is subtracted, the screener's figure reads higher than an excess-return Sharpe whenever short-term rates are above zero, so an instrument's screener Sharpe and a strategy's backtest Sharpe are not comparable. The filter's description in the app speaks of subtracting a Treasury-bill rate; the value the screener computes does not. ## How does Fincanva handle it? - The metrics table shows it in the **Volatility and risk** group as the row **Sharpe**, as a plain number, and the KPI strip calls the same figure **Sharpe ratio**. - The [Strategy analytics](/docs/analysis/strategy-analytics) page draws it rather than tabulating it: on its **Return and oscillation** card each strategy is a dot, and the line through that dot starts at the risk-free rate, so the steeper the line the higher the Sharpe ratio. The value itself reads **Sharpe** on the dot's own label. Narrow that page to a single year and the lines disappear; the [Strategy analytics](/docs/analysis/strategy-analytics) page explains why, and the [risk-free rate](/docs/analysis/risk-free-rate) page owns the figure behind it. - The by-year table repeats it per calendar year, computed on that year's own return and volatility. - On the metrics table the numerator uses CAGR with **Reinvest profits** on and AAGR with it off; the by-year table and Strategy analytics always use CAGR. The denominator is always the square-root-of-252 annualized volatility. - The risk-free rate row on the same metrics table shows the period average of the baseline the numerator subtracts, so you can see the two inputs side by side. - It turns negative whenever the annualized return fell below the risk-free rate over the period — the strategy earned less than a near-riskless baseline. ## What does it look like in practice? A strategy returns 11% a year over its backtest while the risk-free rate averaged 3% over the same window, and its annualized volatility was 10%. The excess return is 11% − 3% = 8 percentage points, so the Sharpe ratio is 8 ÷ 10 = **0.8**: the strategy earned 0.8 units of excess return for each unit of volatility. Now take a second strategy that returned the same 11% a year with volatility of 20%. Its excess return is the same 8 points, but its Sharpe ratio is 8 ÷ 20 = 0.4 — the same reward, from twice the variability. Headline return alone would have called these two identical. ## What counts as a good value? A higher Sharpe ratio means more excess return per unit of variability, and a value of zero means the strategy merely matched the risk-free baseline. A negative value means it trailed that baseline. Since the ratio is a plain number, a difference between 0.4 and 0.8 is a doubling of return-per-unit-of-risk, not "0.4 percentage points". The Sharpe ratio treats every swing as risk, upward ones included, so a strategy penalised by a burst of *good* months scores lower than the experience of holding it might suggest — the [Sortino ratio](/docs/analysis/sortino-ratio) is the variant that counts only downside variability. It also says nothing about the worst single fall, which is [max drawdown](/docs/analysis/max-drawdown), or about return against that fall, which is the [return-to-drawdown ratio](/docs/analysis/return-to-drawdown-ratio). And because both of its inputs are measured over the backtest's own window, Sharpe ratios from windows of different lengths or different rate environments are not like-for-like. *No Sharpe ratio is a target to aim for or a promise about future risk.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/sortino-ratio # Sortino ratio The Sortino ratio divides a strategy's excess return by its downside deviation only — a variant of the [Sharpe ratio](/docs/analysis/sharpe-ratio) that penalises harmful downward volatility while leaving harmless upside swings out of the risk measure. Where Sharpe treats all variability as risk, Sortino counts only the periods that finish below zero, on the reasoning that investors mind losses far more than they mind unexpectedly good months. **Also seen as:** Sortino, downside-adjusted return ## How is the Sortino ratio calculated? The Sortino ratio takes the strategy's excess return over the risk-free rate and divides it by the downside deviation, but the two halves use different baselines. The numerator is the strategy's [CAGR](/docs/analysis/cagr) minus the [risk-free rate](/docs/analysis/risk-free-rate), whatever the **Reinvest profits** setting. The downside deviation in the denominator is measured against a 0% per-period threshold: only periods with a negative return feed the downside deviation, while periods at or above 0% are left out. $$ \text{Sortino ratio} = \frac{\text{annualised return} - \text{risk-free rate}}{\text{downside deviation (vs a 0\% threshold)}} $$ where the numerator is the excess return over the risk-free rate and the downside deviation counts only the periods that finished below 0%. It is built like the Sharpe ratio but swaps total volatility for downside-only volatility in the denominator. ## What counts as a strong Sortino ratio? Higher is better — more return earned per unit of *harmful* variability. Because the denominator only counts downside, a strategy's Sortino ratio is usually higher than its Sharpe ratio; the gap between the two is itself telling, since a wide gap means most of the strategy's volatility was to the upside. ## How does Fincanva handle it? - Fincanva reports the Sortino ratio on the [Strategy analytics](/docs/analysis/strategy-analytics) page only — one bar per strategy in the **Sortino** column of its **Each strategy, against the Combined** card. It is not a row on the main metrics table and not a KPI card. A strategy that is not part of a Combined still appears on that card — alone — so it shows a Sortino ratio too. - The numerator is the excess return over the risk-free rate, always measured from CAGR: unlike the Sharpe row of the metrics table, it does not switch to AAGR when **Reinvest profits** is off. - The risk-free rate it subtracts is the period average of the 3-Month US Treasury Bill series over the window, with a flat 2% a year standing in for any months outside that series — see [risk-free rate](/docs/analysis/risk-free-rate). - The denominator counts only periods that finished below a 0% per-period threshold; periods at or above 0% are ignored, so only downside variability is penalised. - A higher value means more return for the same amount of downside variability. ## What does it look like in practice? Take two strategies that both return 9% a year. One climbed in bumpy but mostly upward steps; the other posted the same 9% but with several sharp drops along the way. Their Sharpe ratios can look alike, because Sharpe counts every swing — up or down — as risk. The Sortino ratio only puts the downward moves in its denominator, so the strategy with the sharp drops gets the lower Sortino. Same total return, but the ratio rewards the strategy whose volatility was mostly the harmless, upside kind. *No Sortino ratio is a target to aim for or a promise about future downside.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/start-date-sensitivity # Start-date sensitivity Start-date sensitivity measures how much a strategy's outcome depends on when you started it — how different the results would have been had the same strategy begun on other dates. A single backtest reports one start date's luck; a strategy whose results swing wildly depending on the entry month is fragile, while one that holds up across many start dates is more robust. **Also seen as:** timing luck, entry-date risk ## How is start-date sensitivity measured? The strategy is re-run over many possible entry dates and several holding windows, and the spread of outcomes across those runs is summarised. Because each run can be annualised with [CAGR](/docs/analysis/cagr), the results are directly comparable regardless of window length, and the width of the resulting range is the sensitivity: a narrow range means the start date barely mattered, a wide one means timing dominated. ## How does Fincanva handle it? - **Start-date sensitivity is included from the Starter plan.** The Free plan does not open this page; Starter, Advanced, Ultimate and Professional include it. See [what each plan includes](/docs/account-security/what-each-plan-includes). - The analysis tests rolling holding windows of 1, 3, 5, 7 and 10 years, each started on many different entry dates. - Its headline figures are a CAGR range (the best-start versus worst-start annualised return), the worst start on record, and the share of start dates that finished positive. - A summary-statistics table repeats the detail per holding window — the best, worst and average CAGR, the spread of those CAGRs, the **Avg pain** ([average pain](/docs/analysis/average-pain)) and the worst starting point — and the view also draws the best, the worst and the most painful start as separate curves. - Because it compares annualised returns, windows of different lengths sit on the same yearly scale and can be read side by side. ## What does it look like in practice? Take one strategy and start it at the beginning of every month of 2015, holding each run for the same window. Collect the CAGR of each start. If the best month annualises to +14% and the worst to +2%, the strategy earned a positive return whichever month you began — but the 12-point gap shows the outcome still leaned heavily on timing. ## What counts as a good result? A robust strategy shows a narrow spread of outcomes across start dates and a high share of start dates that ended positive; a fragile one shows a wide spread and a low positive share. A single strong backtest tells you little on its own — it may simply have caught a lucky entry — so the value of this view is in the range, not any one run. This is also the cleanest defence against [cherry-picking bias](/docs/investing-theory/cherry-picking-bias): a window chosen after the fact to flatter a strategy is one start date among many, and the spread shows you all the others. *A narrow spread is not a promise of a repeatable result.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/strategy-analytics # Strategy analytics Strategy analytics is the per-strategy page of a [Combined](/docs/getting-started/strategy-in-a-combined), reached from its **Components** tab: every strategy the Combined holds is read across four cards, each measured on that strategy's own returns inside the run. It is how you compare the pieces of a Combined against each other and against the whole they belong to, instead of reading only the Combined's single blended result. **Also seen as:** per-strategy metrics, per-strategy analytics ## What does strategy analytics report for each strategy? Eight figures per strategy, spread across three cards rather than gathered into one row of columns, with a fourth card for the profit each strategy brought. Six of the figures describe the strategy on its own terms, and two describe it relative to the Combined. Every card lists the strategies in the same order, so one strategy can be followed down the page with your eye. | Metric | What it says about the strategy | Where it is drawn | |---|---|---| | [CAGR](/docs/analysis/cagr) | its annualised growth rate | the vertical axis of **Return and oscillation** | | [Volatility](/docs/analysis/volatility) | how much its returns varied | the horizontal axis of the same card | | [Sharpe ratio](/docs/analysis/sharpe-ratio) | return per unit of total risk | the slope of that strategy's line on the same card, and the figure on its point label | | [Max drawdown](/docs/analysis/max-drawdown) | its deepest peak-to-trough fall | the **Worst fall** card | | [Information ratio](/docs/analysis/information-ratio) | whether moving differently paid off | the **Each strategy, against the Combined** card | | [Tracking error](/docs/analysis/tracking-error) | how differently it moved from the Combined | the same card | | [Sortino ratio](/docs/analysis/sortino-ratio) | return per unit of downside risk | the same card | | [Return-to-drawdown ratio](/docs/analysis/return-to-drawdown-ratio) | return against its deepest fall | the same card, under the shorter label **Return / fall** | In prose: the first card plots each strategy as a dot, return upwards against oscillation sideways, with the Combined drawn as a diamond and a line through each dot whose steepness is that strategy's Sharpe ratio. The second card draws the worst fall each strategy took, in that same shared order. The third puts the four comparison figures side by side as bars, one row per strategy. The fourth, **How much profit each one brought, over time**, is not a metric at all: it draws the cumulative profit each strategy contributed to the Combined, all of them on one scale. The first six carry exactly the definitions they carry on the Combined's own [metrics table](/docs/analysis/metrics-table), so the same name means the same thing in both places — read one strategy across the cards and you are reading it the way you would read a whole portfolio. ## Why are tracking error and information ratio measured against the Combined? Because on this surface both metrics answer a question about membership, not about the market: they compare a strategy to the **parent Combined it sits inside**, not to the [benchmark](/docs/getting-started/benchmark). This is the single most misread fact on the surface — elsewhere in finance tracking error and the information ratio are usually quoted versus a benchmark index, so a reader who assumes that here will draw the wrong conclusion from the number. A strategy with a high tracking error is one that diverges from *its own Combined*, and an information ratio near zero means it contributed little relative to *the Combined*, whatever either of them did against the benchmark. ## How does Fincanva handle it? - **Strategy analytics is included from the Advanced plan.** Like every Combined-only page it follows Combined itself, which Free and Starter do not include; Advanced, Ultimate and Professional open it. See [what each plan includes](/docs/account-security/what-each-plan-includes). - Each strategy's metrics come from its own share of the one Combined backtest — not from running that strategy standalone — so a strategy's figures here can differ from the numbers on its own standalone run. - Tracking error and information ratio are measured against the parent Combined; the other six metrics are measured on the strategy's own return series. - Daily returns are annualised by ×√252, the same [annualization](/docs/analysis/annualization) convention used for volatility and the Sharpe ratio across the product — including for tracking error and the information ratio. - The cards follow the [simulation assumptions](/docs/backtesting/simulation-assumptions) toggles: switching costs, taxes or reinvestment changes every strategy's figures, as it changes the Combined's own metrics. - A **Period** selector above the cards narrows the whole page to one calendar year, or back to **All period**. In a year view the Sharpe lines are not drawn: the risk-free rate the engine reports is a whole-period figure, and Fincanva does not invent a per-year one to replace it. - The profit card always covers the whole period, whatever the **Period** selector says; selecting a year shades that year on it rather than cropping the curves. - A strategy that is not part of a Combined has nothing to be compared with, so the page shows it alone on each card. - Above the four cards, the tab opens with a fifth, "Strategies: where the result comes from", which splits the Combined's own return, volatility, Sharpe and daily VaR among its strategies so the parts add up to the whole. See [contribution analytics](/docs/analysis/contribution-analytics). - The pieces of a Combined are **strategies**, and that is the word this page's own copy uses for them throughout, on every axis and every row label. The tab that opens the page is labelled **Components**, which names the page rather than renaming its rows. ## What does it look like in practice? A Combined returns 6.2% a year. Strategy A inside it returns 9.0% with a tracking error of 7%, so its information ratio is (9.0% − 6.2%) ÷ 7% ≈ **0.40** — it moved differently from the Combined, and the difference went its way. Strategy B returns 5.8% with a small tracking error, giving a slightly negative information ratio: it tracked the Combined closely and still ended just behind it. Now read the trap: a reader who took A's 7% tracking error as "7% away from the benchmark" would be measuring against the wrong thing entirely — the 7% is A's divergence from the Combined it belongs to. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/stress-test # Stress test The stress test is the panel of a strategy's **Robustness** tab that asks how its risk figures would change under a scenario you set — an average return of −20% a year, volatility twice as high, or both. It invents no data: it keeps the strategy's own historical days and gives more weight to the ones that resemble the scenario, changing those weights as little as possible, then recomputes the average annual return, the annual volatility and the daily VaR and CVaR at 95% on the reweighted history. Two gauges beside the result say how far history had to be bent to get there, and so how much the result can be trusted. **Also seen as:** stress testing, scenario analysis, what-if analysis, entropy pooling ## How can a stress test work without inventing data? By changing how much each past day counts rather than what happened on it. Normally every day of the backtest counts equally. To make the history average −20% a year, the test counts the losing days a little more and the winning days a little less — just enough for the weighted average to hit the target, and no more. To double volatility, it leans on the large days, up and down, over the quiet ones. The textbook name is **entropy pooling**: among all the ways of reweighting the days that satisfy the scenario, it picks the one closest to the original, equal weighting. Every figure it reports is still made of days the strategy really lived. That is also its limit. A scenario can only be reached with the kinds of day the history contains: a strategy that never had a bad day cannot be made to average −40% a year, and the panel then says "We couldn't calculate this scenario." ## How do I read the two gauges? They are the honesty check on the result, and they are the first thing to read. - **How far we bent history** measures how different the reweighted history is from the original. "A little" means the scenario is plausible for this strategy; "Noticeably" means it asked visible effort of the history — read the result with care; "A lot" means the scenario is far from anything the strategy has lived through, and the result is not very reliable. - **Days that still count** measures how much of the history still carries real weight. It reads, from best to worst: the result rests on almost the whole history; on a good part of it; on a small part of it — read it with care; on a few extreme days — read it with great care. A result with both gauges in their first reading is the one to lean on. When the worst 5% of days shrinks to a single day, the VaR and CVaR rows are marked "· a single day": the two are then equal and say little. ## How does Fincanva handle it? - It runs on request, from the **Robustness** tab's **Stress test** panel. Pick one of the **Ready-made scenarios** — "A −20% year", "Double volatility", "A flat year", "Crash: −40% and volatility ×2" — or set **Assumed annual return** (−50% to +50%) and **Volatility multiplier** (0.5× to 3×) yourself, then press **Apply scenario**. At least one of the two has to differ from normal; a volatility multiplier alone keeps the average return where it was. - The result is a table, **On the strategy's historical days**, with the **Base** figures beside **With the scenario**: average annual return (arithmetic), annual volatility, daily VaR 95% and daily CVaR 95%. VaR and CVaR are daily losses, shown as positive numbers; they are defined on [Performance Metrics](/docs/analysis/what-every-number-in-performance-metrics-means). - The **Base** column is computed on the same footing as the scenario column, not the way Performance Metrics computes its figures, so it does not match that page. Compare **Base** with **With the scenario**. - The figures follow the tab's **Simulation settings**: with **Costs & interests** or **Taxes** on, the test runs on the net returns. - A simulation stored before the panel existed has to be run again first. The stress test is included from Advanced upwards, on the same plans as [backtest reliability](/docs/analysis/backtest-reliability), so the **Robustness** tab opens as one. See [what each plan includes](/docs/account-security/what-each-plan-includes). ## What does it look like in practice? A strategy's history averages 8% a year with 15% volatility, and a worst-5% day loses 1.4%. Apply "A −20% year": the table shows the average return moved to −20%, volatility up slightly to 17%, and the daily VaR at 2.1% — the reweighted history leans on its bad days, and the bad days are bigger than the average ones. **How far we bent history** reads "Noticeably" and **Days that still count** says the result rests on a good part of the history: a plausible, if demanding, scenario for this strategy. Try "Crash: −40% and volatility ×2" on the same strategy and both gauges drop to their last readings — the history holds too few days like that for the answer to mean much. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/total-p-l # Total P&L Total P&L is the money a symbol or a single position made or lost over a backtest — its trading result after costs, plus the dividends it received — reported in the account's currency. The Positions tables show it as the final column, "Total P&L", after Gross, Costs, Net and Dividends, both in the "By symbol" table and in the per-symbol position rows underneath it. Because it is an amount of money rather than a rate, Total P&L tells you the size of a result but not how efficiently the capital was used. **Also seen as:** total PnL, profit and loss, P/L ## How does Total P&L differ from total return? Total P&L is a money amount for one symbol or position; [total return](/docs/analysis/total-return) is a percentage for the whole strategy. This column was previously labelled "Total return" as well — the same wording used for the percentage in **Performance Metrics** — and was renamed to Total P&L so the two can never be confused. Reading a Positions row, "Total P&L 1,245" means that symbol contributed 1,245 of currency to the run. Reading the metrics table, "Total return (%) 40.0" means the whole strategy finished 40% above the value it started with. One is per-instrument and in money, the other is per-strategy and in percent, so they are never two views of the same number and never add up to each other. ## What the Total P&L column adds up Total P&L is the last of five money columns that build the result up step by step. | Column | What it holds | |---|---| | Gross | the position's trading gain or loss before any costs | | Costs | the trading fees and [slippage](/docs/backtesting/slippage) charged to it | | Net | Gross minus Costs — the trading result after costs | | Dividends | the dividends the position received while it was held | | Total P&L | Net plus Dividends — the position's whole result | In words: start from the raw trading gain, subtract what it cost to trade, then add the income the holding paid you. The five columns are identical in the "By symbol" table and in the per-symbol position rows — the first summarises every position in one symbol, the second breaks that symbol down position by position. ## How does Fincanva handle it? - Total P&L is money in the account's base currency, formatted like the other P&L columns and coloured by sign; a negative value is a loss. - What lands in the Costs column, and therefore in Total P&L, follows the run's [simulation assumptions](/docs/backtesting/simulation-assumptions) — with **Costs & interests** off, no trading costs are deducted. - Dividends are the realized dividend income of the position, so a symbol that pays none has a Total P&L equal to its Net. - The whole-strategy version of this money view is not this column but the [P&L breakdown](/docs/analysis/p-l-breakdown), whose net "Portfolio" line traces the strategy's total P&L across the period. - Positions that are still open at the end of the run carry a mark-to-market result, so part of a Total P&L can be unrealized — see [realized vs open P&L](/docs/analysis/realized-vs-open-p-l). ## What does it look like in practice? A position in one symbol closes with a gross trading gain of 1,200. Fees and slippage charged to it come to 45, so Net is 1,200 − 45 = 1,155. While it was held, the symbol paid 90 of dividends. Total P&L is therefore 1,155 + 90 = 1,245 — the price gain plus the income, minus what the trading cost. Notice what the figure does not say: 1,245 is money, so whether it is a large result depends on how much capital the position tied up and for how long, which the percentage figures in **Performance Metrics** answer instead. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/total-return # Total return Total return is the percentage a strategy gained or lost across its whole backtest — the change from its starting value to its final value over the entire simulated period. It is the percentage measure of the strategy as a whole, shown as "Total return (%)" in the **Performance** group of the [metrics table](/docs/analysis/metrics-table), stored as a fraction (`0.153`) and formatted for display as a percentage ("15.3%"); the money figure for one symbol or position is a separate column, [Total P&L](/docs/analysis/total-p-l). Total return is not annualized, so a three-year run and a ten-year run cannot be compared by it; [CAGR](/docs/analysis/cagr) is the annualized view of the same result. **Also seen as:** cumulative return, whole-period return ## How does total return differ from Total P&L? Total return is a percentage for the whole strategy; [Total P&L](/docs/analysis/total-p-l) is a money amount for one symbol or one position. A money column in the Positions tables was once labelled "Total return" as well; it now carries its own name, so the two figures no longer share one word. Total return answers "by what percentage did this strategy grow or shrink over the run?" and lives in **Performance Metrics**. Total P&L answers "how much money did this symbol or position make or lose, after costs and including dividends?" and lives in the Positions tables. The two measure related things at different scopes and in different units, which is why the money column carries its own name: if a figure is in currency it is Total P&L, and if it is a percentage of the strategy's starting value it is total return. ## How is total return calculated? Total return divides the strategy's final value by the value it started with and subtracts one. $$ \text{total return} = \frac{\text{final value}}{\text{starting value}} - 1 $$ where: starting value is the capital the backtest began with, and final value is the capital on the last simulated day. ## How does Fincanva handle it? - Total return appears as "Total return (%)" in the **Performance** group of the metrics table, shown to one decimal place and coloured by sign. - It is never annualized. The annualized slot beside it holds [CAGR](/docs/analysis/cagr) when **Reinvest profits** is on and [AAGR](/docs/analysis/aagr) when it is off. - The by-year metrics table reports the same measure one calendar year at a time, under the header "Annual return (%)". - Total return is read off the strategy's capital curve, so which costs and taxes are already deducted follows the run's [simulation assumptions](/docs/backtesting/simulation-assumptions). - It can be negative, and it does not depend on how much starting capital you chose — it is a ratio. ## What does it look like in practice? A backtest starts with 10,000 and finishes with 14,000. Its total return is 14,000 ÷ 10,000 − 1 = 0.40, displayed as +40.0%. If that run covered four years, the total return is still +40% — the annualized view is CAGR, roughly +8.8% a year. A ten-year run that also ended at 14,000 would read +40% as well, which is exactly why total return on its own never tells you how fast the money grew. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/tracking-error # Tracking error Tracking error is the volatility of the return differences between a strategy and the Combined it belongs to — the standard deviation, period over period, of how far the strategy's return strays from its parent Combined's return. It measures a strategy against its **parent Combined**, not against a benchmark: the common assumption that tracking error is always measured versus a benchmark does not apply here. **Also seen as:** active risk, tracking risk ## How is tracking error calculated? Tracking error is the standard deviation of the difference between the strategy's return and its parent Combined's return in each period. A strategy that moves almost in step with the whole produces small, steady differences; one that often diverges produces wide, variable differences. The daily return differences are annualised by multiplying by √252 (252 trading days a year), the same convention Fincanva uses for volatility and the Sharpe ratio. $$ \text{Tracking error} = \operatorname{stddev}\big(r_{\text{strategy}} - r_{\text{parent}}\big) \times \sqrt{252} $$ where $r_{\text{strategy}} - r_{\text{parent}}$ is the per-period gap between the strategy's return and the return of the Combined it sits inside, and the daily differences are annualised by ×√252. ## What counts as a high tracking error? A low tracking error means the strategy moves closely in line with its parent Combined; a high tracking error means it diverges from the whole. Neither is inherently good or bad — the value tells you how much a given strategy pulls the Combined away from its own average path. ## How does Fincanva handle it? - Reported on the [Strategy analytics](/docs/analysis/strategy-analytics) page only, in its **Each strategy, against the Combined** card: one bar per strategy in the **Tracking error** column. A strategy analysed on its own still appears there, but it has no parent Combined to be measured against, so its tracking error carries no meaning — read it only for a strategy inside a Combined. - Measured between a member strategy and its parent Combined — the strategy's return relative to the whole, **not** relative to a benchmark. - Reported as the standard deviation of the daily return differences, annualised by ×√252 — the same convention as volatility and the Sharpe ratio. - Pairs with the [information ratio](/docs/analysis/information-ratio), which divides a strategy's excess return over the Combined by this tracking error. ## What does it look like in practice? A Combined holds three strategies. Two of them tend to move closely with the Combined as a whole; the third often zigs when the Combined zags. Month to month, the third strategy's return differs from the Combined's by a wide, shifting margin, while the first two barely differ at all. The standard deviation of those monthly differences — much larger for the third strategy — is its tracking error. A high tracking error flags the strategy that pulls the Combined around the most, independent of whether that strategy made or lost money. *A tracking error is not a limit on how far a strategy can diverge in future.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/value-at-risk # Value at Risk Value at Risk (VaR) is the loss threshold that a strategy's worst days reach: at the 95% level Fincanva uses, it is the daily loss that only the worst 5% of trading days met or exceeded. On the other 95% of days the strategy lost less than the VaR, or gained. It answers "how bad is a bad day?" with one number, and says nothing about how much worse the very worst days were — that is what [Conditional Value at Risk](/docs/analysis/conditional-value-at-risk) adds. **Also seen as:** VaR, VaR 95%, daily VaR, historical VaR, parametric VaR ## How is Value at Risk read off a backtest? The historical VaR takes every daily return of the backtest, lines them up from worst to best, and reads the return at the 5% mark. That loss, written as a positive number, is the historical VaR: no assumption is made about the shape of the returns, so whatever the strategy actually lived through — calm years, crashes, fat tails — is in the figure. Its weakness is the sample itself: a backtest of a few hundred days rests its 5% mark on a handful of days, so the figure moves noticeably when the history is short. ## How is the Gaussian VaR calculated? The Gaussian VaR assumes the daily returns follow a normal distribution with the backtest's own average and volatility, and reads the 5% mark off that curve instead of off the history: $$ \text{VaR}_{95\%} = 1.645\,\sigma - \mu $$ where: $\sigma$ is the daily volatility, $\mu$ is the average daily return, and 1.645 is the number of standard deviations that leaves 5% of a normal distribution below it. In words: start from the average day, go 1.645 standard deviations down, and the distance below zero is the Gaussian VaR. ## Why do the historical and the Gaussian VaR differ? The two agree when the strategy's returns really were close to normal, and part ways when they were not. A normal curve makes very large days rare, and markets produce them more often than it expects, so a historical VaR clearly above the Gaussian one means the strategy's bad days were worse than a normal distribution predicts — its losses have fat tails, and the Gaussian figure understates them. A historical VaR below the Gaussian one is rarer and usually means a short or unusually calm history. ## How does Fincanva handle it? - **Daily, at 95%.** Every VaR in the app is a one-day loss at the 95% level, written as a positive number: "2.1%" means a loss of 2.1% in one day, and a larger number is a larger loss. - **Performance Metrics** shows both forms in the **Worst days · 95%** group, as **Daily VaR · historical** and **Daily VaR · Gaussian** — see [what every number in Performance Metrics means](/docs/analysis/what-every-number-in-performance-metrics-means). - **Contribution analytics** shows the Combined's **Daily VaR 95% · Gaussian** above the table and splits it among the strategies in the **VaR 95% contribution** column — see [contribution analytics](/docs/analysis/contribution-analytics). - The **Stress test** sets the **Daily VaR 95%** of the strategy's historical days beside the same figure under the scenario — see [stress test](/docs/analysis/stress-test). - A simulation computed before these rows existed does not carry them, and shows "n/a" rather than 0%: a 0% loss would claim a safety the figure does not show. ## What does it look like in practice? A strategy's Performance Metrics read **Daily VaR · historical** 2.4% and **Daily VaR · Gaussian** 1.8%. On 95% of its trading days it lost less than 2.4% or gained; on roughly one day in twenty it lost 2.4% or more. The normal-curve estimate of the same threshold is 1.8%, so the strategy's bad days were deeper than its volatility alone suggests — a fat left tail. A second strategy with the same volatility but both figures near 1.8% had bad days that behaved as a normal curve expects. ## What counts as a good value? Lower is a smaller loss on a bad day, but VaR is only comparable between strategies over the same period: a history that includes a crash has a higher VaR than one that does not, whatever the strategy. Read it beside [volatility](/docs/analysis/volatility) and the [Conditional Value at Risk](/docs/analysis/conditional-value-at-risk): VaR marks where the bad days begin, CVaR says how bad they are once there, and neither is a limit on what a single future day can lose. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/analysis/volatility # Volatility Volatility is the annualized standard deviation of a strategy's returns — a measure of how widely those returns swing around their own average. Wide swings in both directions mean high volatility; returns clustered close to their average mean low volatility. Volatility counts **all** variability, up as well as down, which is what separates it from a drawdown measure: a strategy that rose in violent jumps and one that fell in violent jumps can have the same volatility. **Also seen as:** standard deviation, Std Dev, Vol, sigma ## How is volatility calculated? Volatility starts as the standard deviation of the return series — the typical distance of a return from the series average — and is then scaled up to a per-year figure. $$ \text{annualized volatility} = \text{daily volatility} \times \sqrt{252} $$ where: daily volatility is the standard deviation of the strategy's daily returns, and 252 is the conventional number of trading days in a year. Because a standard deviation grows with the square root of the time span, not linearly with it, the daily figure is multiplied by the square root of 252 rather than by 252. ## Why is volatility annualized with the square root of 252? Fincanva uses the standard **252-trading-day** convention: a year is treated as 252 trading days, and a daily standard deviation is turned into an annual one by multiplying by the square root of that count. Stating the convention matters because the same underlying returns produce a different-looking number under a different one — 365 calendar days, or 12 months, would each give a different figure for identical data. The 252 basis is used consistently across the risk figures built on volatility, including the [Sharpe ratio](/docs/analysis/sharpe-ratio), the [Sortino ratio](/docs/analysis/sortino-ratio) and [tracking error](/docs/analysis/tracking-error), so those ratios are all built on the same annualization. See [annualization](/docs/analysis/annualization) for how *returns*, as opposed to dispersion, are put on a yearly scale. ## How does Fincanva handle it? - The metrics table shows volatility in the **Volatility and risk** group as the row **Volatility**, as a percentage, and the group heading and the KPI strip use the same name for the same quantity. - The [Strategy analytics](/docs/analysis/strategy-analytics) page uses it as the horizontal axis of its **Return and oscillation** card, labelled **Annual oscillation (volatility)**: the further right a strategy's dot sits, the more its returns varied. - The by-year table repeats it per calendar year, so you can see whether the ride was bumpier in some years than others. - It is always the annualized figure, using the square-root-of-252 convention — never a raw daily or monthly dispersion. - Volatility is also selectable as the **Risk measure** in the Inverse Volatility allocation method, under the label **Annualized volatility**, where it decides weights rather than reporting a result. - Because it is a dispersion measure, volatility is never negative. ## What does it look like in practice? Two strategies both average +1% a month over a year. The first posts months of +1.2%, +0.8%, +1.1%, +0.9% — a tight spread around its average. The second posts +9%, −7%, +8%, −6% — the same kind of average, from a far wider spread. Their average return is nearly identical; their volatility is not. The first strategy's returns sit close to their average, so its standard deviation is small and its annualized volatility is low. The second strategy's returns are scattered far from theirs, so its standard deviation — and therefore its volatility — is several times higher. Volatility is the number that tells these two apart when the average return cannot. ## What counts as a good value? Lower volatility means returns were more tightly clustered around their average, and higher volatility means they were more scattered. Volatility says nothing on its own about *direction*: a strategy with high volatility may have swung mostly upward, and volatility does not distinguish that from swinging mostly downward — which is exactly the gap the [Sortino ratio](/docs/analysis/sortino-ratio) exists to close by counting only downside variability. Volatility is also not the same as loss. It measures spread around an average, while [max drawdown](/docs/analysis/max-drawdown) measures the worst actual fall from a peak; a strategy can have modest volatility and still have suffered one deep, sustained decline. Read the two together, and read volatility against a comparable window, since it is measured over the backtest's own period. Volatility is also measured without reference to any benchmark: how much of a strategy's movement tracks the market is [beta](/docs/analysis/beta), a separate reading. *Past volatility is not a limit on future variability.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/changelog # Components is rebuilt, and Correlations gets its own page **2026-09-12** · analysis · 2026.09 The **Components** tab of a Combined's Analysis is rebuilt: a return-versus-volatility view of each strategy against the Combined, one row-aligned comparison panel, and each strategy's profit curve — see [component analytics](/docs/analysis/strategy-analytics). What used to sit inside it now has its own **Correlations** tab, showing how the strategies of a Combined move with each other, with the Combined itself and with the wider market — see [correlation matrix](/docs/analysis/correlation-matrix). Correlations is included from Advanced; see [what each plan includes](/docs/account-security/what-each-plan-includes) and [find your way around the Analysis tabs](/docs/analysis/find-your-way-around-a-strategy-s-analysis-tabs). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/changelog # Project a strategy forward with the Projection tab **2026-09-24** · analysis · 2026.09 A strategy's Analysis has a new **Projection** tab that draws a cone of values the strategy could reach over the coming years, by simulating many possible paths from the returns it has already lived through — resampled days or blocks of days, or a normal curve fitted to them — a spread of outcomes, never a forecast. You choose the method, the horizon and the number of scenarios; see [the Projection guide](/docs/analysis/see-where-a-strategy-could-go-with-the-projection-tab). The tab is on every plan, Free included, and your plan sets how far ahead it projects and how many scenarios one calculation may draw — see [what each plan includes](/docs/account-security/what-each-plan-includes). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/changelog # Test how far to trust a backtest with the Robustness tab **2026-09-24** · analysis · 2026.09 A strategy's Analysis has a new **Robustness** tab with two checks that question the backtest instead of reporting it. [Backtest reliability](/docs/analysis/backtest-reliability) resamples the strategy's history to ask whether a result this good could be luck, and how much its figures could have varied; the [stress test](/docs/analysis/stress-test) reweights the same history toward a scenario you set and shows how the risk figures move. Both run only when you ask — see [the Robustness guide](/docs/analysis/test-how-much-to-trust-a-backtest-with-the-robustness-tab). The tab is included from Advanced — see [what each plan includes](/docs/account-security/what-each-plan-includes). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/changelog # Worst-days metrics and contribution analytics **2026-09-24** · analysis · 2026.09 **Performance Metrics** has a new **Worst days · 95%** group — historical and Gaussian value at risk, and conditional value at risk — on every plan; see [what the worst-days rows show](/docs/analysis/what-every-number-in-performance-metrics-means#what-do-the-worst-days-rows-show). A Combined's **Components** tab now opens with [contribution analytics](/docs/analysis/contribution-analytics), which splits the Combined's return, risk, Sharpe and daily VaR among the strategies inside it, with what belongs to none of them in a **Residual** row. It comes with the Combined, so it is included from Advanced — see [what each plan includes](/docs/account-security/what-each-plan-includes). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/portfolio-holdings/follow-a-strategy-live # Follow a strategy live You follow a strategy by marking it **Live**, which starts tracking what its rules would hold from today forward and lists it on the **Portfolios** page. ↗ See this in Fincanva — the Portfolios page ## Before you start You need one of your own strategies — a Public strategy has no Live control, because it is not yours to follow. There is no separate "create a portfolio" step: a portfolio *is* a strategy you have marked Live, which is why **Portfolios** and **Strategies** show the same rows filtered differently. **Live is monitoring only.** Fincanva places no orders, connects to no broker, and moves no money — see [Mark Live](/docs/getting-started/mark-live#does-marking-a-strategy-live-trade-anything). ## Steps 1. Open the strategy, or find its row on **Strategies**. 2. Flip the switch in the strategy's title cluster — it reads **Off** until you do — or select **Mark Live** in the row's menu. 3. Read the confirmation. It asks "Mark this strategy as Live?" and states what follows: "It'll show in Portfolios and count toward your dashboard." 4. Confirm with **Mark as Live**. **Cancel** backs out and changes nothing. ## What you should see The switch turns and reads **Live**, and the strategy appears on the **Portfolios** page as one row of your [live book](/docs/getting-started/live-book). Its star turns on and locks while it stays Live, its numbers start being kept current for you as new market data arrives, and it begins counting toward the summary strip at the top of the page. Reading what it now holds is [Read your order plan](/docs/portfolio-holdings/read-your-order-plan); keeping the whole book healthy is [Keep your live book in order](/docs/portfolio-holdings/keep-your-live-book-in-order). Marking a strategy Live is not a prediction that it will perform, and Fincanva never suggests which strategy to follow — see [Is this financial advice?](/docs/investing-theory/is-this-financial-advice#is-this-financial-advice). ## What changes once a strategy is Live? Four things, and none of them involve money — [Mark Live](/docs/getting-started/mark-live#what-changes-when-a-strategy-is-live) lists them. The one that surprises people is what does *not* change: editing a Live strategy does not re-run it by itself, so an edited strategy sits with a stale result until you run it, exactly as it would if it were not Live. ## How do I stop following a strategy? Flip the same switch back, or select **Unfollow** in the row menu. Fincanva asks "Stop following this strategy?" and tells you what that costs — "It'll leave Portfolios and stop counting toward your dashboard." — and commits with **Stop following**. Nothing about the strategy itself changes: its settings and its whole backtest history are untouched, its star unlocks, and you can mark it Live again whenever you want. ## Common problems ### The strategy I want to follow has no Live switch It is a Public strategy, which cannot be followed because it is not yours. Make your own copy first with **Copy to Mine**, then mark the copy Live. A copy never starts Live: **Duplicate** and **Copy to Mine** both produce a strategy whose switch starts **Off**. ### A toast says "Couldn't update Live status. Try again." The change did not go through, so the strategy is still in whatever state it was before. Nothing is half-applied — try the switch again. ### The switch is refused with a message naming your plan This is not the generic toast above — it is your plan talking. Your account is already at the number of strategies your plan follows Live, so this one has nowhere to go: the refusal states the plan and how many it allows, and offers the plan level that would raise the number, named on its own button rather than a generic "Upgrade". This is the [plan compliance](/docs/backtesting/plan-compliance) check, and it answers the same way whether you flip the switch in the strategy's title cluster or pick **Mark Live** from the row's menu on **Strategies**. ### I marked a strategy Live but Portfolios shows nothing to act on That is the healthy state, not a fault. Until the strategy has a completed run there is no target book to show, and the Holdings view says so directly: "Backtest this strategy to see its target portfolio." Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/portfolio-holdings/keep-your-live-book-in-order # Keep your live book in order The **Portfolios** page tells you which of your live-followed strategies need attention and what each one is waiting for, so you can clear them one at a time. ↗ See this in Fincanva — the Portfolios page ## Before you start You need at least one strategy marked Live — with none, the page reads "No live strategies yet" and "Mark a strategy Live to start following it here." Following one is covered in [Follow a strategy live](/docs/portfolio-holdings/follow-a-strategy-live). ## Steps 1. Open **Portfolios**. The **To do** card carries one number above the caption "priority actions", with a quiet `{count} in order` beside it for the portfolios that are fine. 2. Read the attention tile under it. It reads **To fix** when something has hard-failed, **To finish** when a Combined does not yet hold enough strategies to run, **To update** when something merely wants a look, and "Updates" / "All up to date" when nothing is flagged. 3. Select the tile to open **Needs attention** — every flagged portfolio with its reason, worst first. 4. Select a row to open that portfolio's Holdings view and see what it is actually waiting for. 5. Clear it from the portfolio's row on the list, whose action follows its state: **Run** for one that has never run, **Re-run** for one whose result is stale, **Retry** for one that failed. 6. Check **Next rebalance**, the tile beside the attention tile, which names the portfolio whose rebalance falls soonest. ## What you should see The number on the card falls by one as each portfolio is cleared, and the tile drops to the next-worst reason behind it. Once nothing is flagged, the tile reads "Updates" over "All up to date" and there is nothing left to open. The same information reaches you on **Home** under **Needs you**, where each row carries a one-word chip — **Fix**, **Re-run**, **Run**, **Finish** or **Review** — naming what that portfolio wants. The card triages your Fincanva setup, not the market: it says a result needs re-running or a setting needs review, never that a position should be bought or sold — see [Is this financial advice?](/docs/investing-theory/is-this-financial-advice#is-this-financial-advice). ## What is the difference between To fix and To update? **To fix** is a hard failure and **To update** is everything softer, so the tile always names the worst thing in your book rather than the first. That matters when you are working the list: a single failed portfolio hides every stale one behind it until you clear it, and the tile only drops to a softer label once nothing is failing. **To finish** and **To update** share that softer tier: neither outranks the other, so which of the two the tile shows is whichever flagged portfolio sorts first. Which status lands in which label is the table on [To do, To fix, To finish, To update](/docs/portfolio-holdings/to-do-to-fix-to-finish-to-update). ## Which statuses count as in order? Two: **Up to date** and **Computing**. A portfolio actively recomputing is not a problem to solve, so it is counted with the healthy ones rather than flagged. [Run status](/docs/backtesting/run-status) covers each state and how a portfolio moves between them. ## Common problems ### A portfolio is flagged To update but its run looks perfectly healthy It carries configuration warnings you have not dismissed. The tile then shows the count of those warnings as its reason instead of a status — open the portfolio and review them. ### A Combined says "Add one more strategy to run this Combined." It holds a single strategy, and a Combined needs at least two before it can run. Add a second one from its Settings; until then it stays **Incomplete**, and the attention tile reads **To finish**. ### The card counts portfolios I do not think of as live It counts every strategy you have marked Live, and only those. A strategy you have merely backtested never appears — and one you no longer want counted leaves the card as soon as you stop following it, covered in [Follow a strategy live](/docs/portfolio-holdings/follow-a-strategy-live#how-do-i-stop-following-a-strategy). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/portfolio-holdings/read-your-order-plan # Read your order plan The **Holdings** view shows what a strategy would hold at a chosen rebalance date, and the **Order plan** card lists what would change to get there. ↗ See this in Fincanva — a strategy's Holdings, under Order plan ## Before you start You need a strategy that has completed at least one run. With none, the view reads "No results yet" and "Backtest this strategy to see its target portfolio." **Nothing here is ever placed.** Fincanva has no broker connection and no way to mark an order as executed — the order plan is a list on paper, and any trade on it is yours to place yourself, with your own broker, entirely at your own discretion. ## Steps 1. Open the strategy and go to **Holdings**. 2. Choose which rebalance to look at with the **Date** control. It opens on the most recent date, tagged **Most recent**; typing filters the list. 3. Set **Capital** to the amount you want the plan sized for. It opens at 100,000 in your base currency. 4. Read the four figures across the top: **Target notional**, **Cash**, **Positions**, and **Accuracy**. 5. Read the **Order plan** card — the count of moves to execute, the **est. turnover** figure, and the three groups **Entering**, **Exiting**, and **Adjusted**. Selecting a group opens the full list of instruments in it. 6. Read **Target allocation** for the resulting weights, and **Target positions & exits** for the position-by-position detail. ## What you should see **Entering** means instruments being added, **Exiting** instruments being dropped, and **Adjusted** instruments kept but re-sized. On a strategy's first rebalance it reads "Everything enters — this is the portfolio's first buy-in", because there is no previous book to differ from. With nothing due it reads "No changes this rebalance" and "There are no trades to place." The **Target positions & exits** sheet lists every position under **Symbol**, **Asset type**, **Side**, **Last**, **Quantity**, **Target value**, **Deployed**, and **Exits**, with a **Total** row at the foot. The picture beside each **Symbol** is [its own logo, or a flag for its recorded origin](/docs/getting-started/instrument-logo). These are paper figures describing what a strategy's rules imply, never advice to buy or sell anything — see [Is this financial advice?](/docs/investing-theory/is-this-financial-advice#is-this-financial-advice). ## Does changing Capital change my strategy? No. **Capital** is an input to this view only: it re-sizes the target figures and the share counts, and it moves no weight, re-runs nothing, and is not saved with the strategy. It is a different thing from starting capital, which is a backtest setting belonging to the strategy itself and does flip the last run to **Needs re-run** when changed. [Capital](/docs/portfolio-holdings/capital#how-is-capital-different-from-starting-capital) covers the distinction. ## Why is the Deployed amount lower than the Target value? Because you can only buy whole shares, so the target is rounded down to a whole number of them and the remainder stays as cash rather than becoming a trade. [Target vs deployed](/docs/portfolio-holdings/target-vs-deployed) carries the arithmetic and the size of the gap; [accuracy](/docs/portfolio-holdings/accuracy) averages how close each holding lands, with every holding counting equally, and it is the fourth number across the top of this view. ## Why does the allocation show "Others (N)"? Because the treemap draws the largest cells individually and folds the tail into one. Cash gets its own cell whenever the book is not fully invested, and on a Combined the cells are its strategies until you select one to drill into it. [The target allocation treemap](/docs/portfolio-holdings/target-allocation-treemap) covers both the fold and the drill-down. ## Common problems ### A warning says I'm not viewing the latest rebalance The line reads `You’re viewing {date} — not the latest rebalance`. You have selected an older rebalance date. Nothing is wrong and nothing was changed — you are reading history. Pick the date tagged **Most recent** to get back to the current plan. ### A toast says "Couldn't update — reverted to the last result." A re-fetch after a Date or Capital change failed, so the view put the last working value back rather than showing figures it could not stand behind. Try the change again. ### There is no way to mark the plan as done There is none to find. The card is reporting, not a task list: it will describe the same rebalance until the underlying run or the date you are viewing changes. ### The card says "No changes this rebalance" The strategy's target book at this date is the same as the book it already implies, so there is nothing to place. This is a normal outcome between rebalances, not an error or an empty result. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/portfolio-holdings/accuracy # Accuracy Accuracy is the average, across your holdings, of how much of each holding's target value its whole-share position actually covers. Each holding's own figure is its deployed amount divided by its target value, so it measures only what rounding down to whole shares left behind; the KPI then averages those figures with every holding counting equally, whatever its size. Fincanva shows it as the "Accuracy" KPI on the Holdings view for the book at the selected rebalance date. ## How is accuracy calculated? Accuracy is the plain average of the holdings' individual accuracies, and each holding's accuracy is its deployed amount divided by its target value. $$ \text{Accuracy} = \frac{1}{N} \sum_{i=1}^{N} \frac{\text{deployed}_i}{\text{target value}_i} $$ where $N$ is the number of holdings that hold at least one share, $\text{deployed}_i$ is holding $i$'s whole-share quantity times its price, and $\text{target value}_i$ is the amount the strategy aims to hold in it before any rounding (see [target vs deployed](/docs/portfolio-holdings/target-vs-deployed)). In words: only rounding moves each holding's ratio — the deployed amount is rounded to whole shares and the target value is not, so the shortfall from 100% is exactly what rounding left behind. The average then gives every holding the same say. A holding worth 2% of the book moves Accuracy as much as one worth 40%, so a single small or high-priced holding that rounds badly can pull the figure down while almost all of the money is deployed, and a large holding that rounds badly counts for no more than any other. A holding too small to buy even one share takes no position at all, so it is left out of the average rather than counted as 0% — and so is a holding in a Combined whose strategies' whole-share positions cancel out to zero shares, even when its net target is not zero. Accuracy therefore does not register a holding that ends up with no shares. ## What counts as good accuracy? A figure near 100% is good: in the typical holding, rounding down to whole shares left almost nothing behind. A lower figure means that at least some holdings lost a noticeable share of their target to rounding — often one or two small or high-priced ones, because every holding counts equally. Each holding's own figure sits under its "Deployed" amount in the "Target positions & exits" sheet, which is where to look to see which ones pull the average down. **Shorts behave the same way as longs here.** Rounding moves a short's share count toward zero just as it does a long's, so a short's deployed amount is normally no larger than its target either. **A reading above 100% is possible.** A holding whose quantity falls within a hair of a whole share is counted as that whole share, which can put it over its target by a fraction of a point. A Combined can move a holding much further, in either direction: when two of its strategies hold the same instrument on opposite sides, each side is rounded to whole shares on its own before they are netted, and the net that remains can sit well above or well below the net target. At a price of 100, a long target of 12.01 shares rounds to 12 and a short one of 10.99 rounds to 10, so 2 shares — 200 — are deployed against a net target of 102, and that holding reads 196%. ## How does Fincanva handle it? - Accuracy is shown as a percentage KPI on the Holdings view, to one decimal place, and reflects the book at the selected rebalance date. - It is an unweighted average: every holding with at least one share counts once, whatever its size. A holding that ends up with no shares — too small to buy one, or a Combined whose sides cancel out — is not in the average. - It tends to rise with more capital, because the whole-share leftover on each holding becomes a smaller fraction of that holding's target. - It measures how faithfully the targets were filled — it is not a rating or ranking of the strategy's quality or its expected return. ## What does it look like in practice? Suppose a book of 10,000 holds two instruments. Holding A has a target value of 9,000 at a price of 100: that is exactly 90 shares, so 9,000 is deployed and its accuracy is 100%. Holding B has a target value of 1,000 at a price of 300: 3.33 shares round down to 3, so 900 is deployed and its accuracy is 90%. The Accuracy KPI shows 95.0%, the plain average of 100% and 90% — even though 9,900 of the 10,000 target, or 99%, is deployed. The small holding pulls the figure down exactly as much as the large one holds it up, which is what averaging with every holding counting equally means. *Accuracy measures how closely a paper target book was filled, never real orders, and no reading of it is a reason to put money behind a strategy.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/portfolio-holdings/capital # Capital Capital is the amount of money you enter on a strategy's [Holdings](/docs/getting-started/holdings) view so Fincanva can size that strategy's target orders. It is a view input rather than a strategy setting: change it and every money figure on the page — the target notional, each holding's target value, the deployed amount, and the share quantities — is rebuilt for the new amount, while the target weights stay exactly as they were. It is a different thing from [starting capital](/docs/backtesting/starting-capital), which is a backtest input belonging to the strategy itself. **Also seen as:** investment amount, account size ## What does changing Capital do? Changing Capital re-sizes the order plan and nothing else. The strategy's rules, its allocation, and its saved backtest results are untouched; what changes is how much money those weights are applied to. Because weights are ratios, doubling the capital doubles every [target notional](/docs/portfolio-holdings/target-notional) and roughly doubles every share count — it never changes *what* the strategy wants to hold, only how much of it. The page re-requests its figures at the new amount, dimming briefly while they are rebuilt. ## How is Capital different from starting capital? Capital sizes today's target orders; [starting capital](/docs/backtesting/starting-capital) sizes the historical simulation. Starting capital is the amount a [backtest](/docs/getting-started/backtest) begins with at the start of the simulated period and then compounds forward, so it lives in the strategy's settings and changing it flips the last run to **Needs re-run**. Capital on the Holdings view answers "what would this portfolio look like at this much money, right now" — it re-runs nothing, and it is not saved with the strategy. ## How does Fincanva handle it? - The field is labelled `Capital`, prefixed with your [base currency](/docs/backtesting/base-currency)'s symbol, and opens at 100,000. - The amount is a view parameter: it is not stored with the strategy and does not trigger a new backtest. - While the page is refreshing the field is disabled; if the refresh fails, the field reverts to the last working amount and the page shows `Couldn't update — reverted to the last result.` - A larger capital usually raises [accuracy](/docs/portfolio-holdings/accuracy). - [Cash % and capital invested](/docs/portfolio-holdings/cash-and-capital-invested) are percentages of whatever Capital you set, so scaling the amount moves the money behind them far more than it moves the split itself. - These are paper figures. Fincanva monitors a live-followed strategy without trading, so no [order plan](/docs/portfolio-holdings/order-plan) it produces ever reaches a broker (see [Portfolio](/docs/getting-started/portfolio)). ## What does it look like in practice? A target portfolio holds four instruments at weights of 40%, 30%, 20%, and 10%. With Capital at 100,000 their target values are 40,000 / 30,000 / 20,000 / 10,000. Type 25,000 instead and the weights do not move, but every target value scales to a quarter — 10,000 / 7,500 / 5,000 / 2,500 — and each share count is recomputed at the instrument's own price. The strategy is unchanged; you have only asked what the same portfolio looks like on a quarter of the money. Accuracy typically dips a little at the smaller figure, because one unbuyable fraction of a share now weighs more against a smaller book. *Capital only rescales the target figures this page displays. It is not a suggested amount to invest, and Fincanva does not recommend how much money to put behind any strategy.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/portfolio-holdings/cash-and-capital-invested # Cash % and capital invested Cash % and capital invested are two readings of one split on a strategy's [Holdings](/docs/getting-started/holdings) view: **Cash** is the share of your capital that the target portfolio does not aim to hold, and **capital invested** is the share that it does. They always add to 100%, and both are measured against the [Capital](/docs/portfolio-holdings/capital) figure you entered — not against the positions alone. The `Cash` KPI at the top of the page and the headline percentage on the `Target allocation` card read the same split, so the two can never disagree. **Also seen as:** idle cash, uninvested capital, effective exposure (capital invested, shown as a KPI on Holdings) ## How are Cash % and capital invested calculated? Both come from one sum: add up what every target position is meant to be worth, express it as a share of your capital, and whatever is missing is cash. $$ \text{capital invested} = \sum_i \frac{\text{target value}_i}{\text{capital}} \times 100 \qquad \text{Cash} = 100 - \text{capital invested} $$ where $\text{target value}_i$ is holding *i*'s [target notional](/docs/portfolio-holdings/target-notional) in your base currency, capital is the amount entered on the Holdings view, and both results are percentages. Note which figure that sum uses: the **target** value, before each position is rounded to whole shares. The extra sliver left over by rounding is measured separately, by [target vs deployed](/docs/portfolio-holdings/target-vs-deployed) and [accuracy](/docs/portfolio-holdings/accuracy) — it is not part of Cash %. ## What is effective exposure? Effective exposure is the Holdings page's own name for capital invested: the `Effective exposure` KPI at the top of the page states the same percentage as `capital invested` on the `Target allocation` card — Σ of the target positions' notional value, as a percentage of capital. It is **unclamped**: it reads above 100% exactly when [leverage](/docs/backtesting/leverage) or an [invested portion](/docs/backtesting/invested-portion) above 1.00× pushes a strategy past its capital, and Cash % goes negative for the same reason (see [why is my cash negative?](#why-is-my-cash-negative) below). ## Why do the allocation weights and the Cash % seem to disagree? Because the two are normalised against different totals, and that is the single most confusing thing on the page. - **Shares of a strategy's own slice.** A strategy's allocation weights divide up whatever that strategy was given. They add to 100% of its slice no matter how much of the slice it actually deploys. - **Shares of your whole capital.** Cash %, capital invested, and every tile in the [target allocation treemap](/docs/portfolio-holdings/target-allocation-treemap) are expressed against the capital you entered, so cash shows up as a visible remainder. So a strategy whose asset weights read 60/40 can still leave a quarter of its slice in cash: the 60/40 describes how the *invested* part is divided, not how much is invested. Read the weights when you want the mix; read Cash % when you want to know how much of the money is at work. For the same split across a whole backtest rather than at one date, see the [capital chart](/docs/analysis/capital-chart). ## What leaves capital in cash? Two settings put capital in cash rather than into positions, and they stack: - **Leverage below 1.** [Leverage](/docs/backtesting/leverage) is a multiplier on position sizes — `1.00 = no leverage`, with a range of `0.00 – 3.00` and presets from `Cash only` to `Max`. At `0.50` a strategy targets half the money it was allocated and the other half sits idle. This is the case that surprises people, because the asset weights still read as a full 100% split of the invested part. - **A deliberate cash reserve.** A Combined's [Invested portion](/docs/backtesting/invested-portion) setting — `Share of capital this profile deploys` — holds back a slice on purpose. Leverage above `1.00` works the other way: target positions add up to more than your capital, and Cash % goes **negative** rather than to zero — see [why is my cash negative?](#why-is-my-cash-negative) below. ## Why is my cash negative? Cash % (and the Cash amount) goes negative when the target positions add up to more than your capital: the difference is borrowed, and Fincanva calls it margin debt. Two settings can push a strategy or Combined there, and they work the same way in reverse of the two above: - **A single strategy's [Leverage](/docs/backtesting/leverage) above 1.00×.** At 1.50× a strategy targets 150% of its capital; 50% is borrowed and Cash % reads −50%. - **A Combined's [Invested portion](/docs/backtesting/invested-portion) above 100%.** The same borrowing happens at the Combined level — see invested portion's own worked example. On the Holdings page, negative cash relabels the `Cash` KPI to `Cash · margin debt` and switches its tone to negative — the figure itself is never clamped to zero, it reads the actual debt. The `Target allocation` card's exposure bar draws the same debt as a segment to the left of zero, captioned `Debt {amount} · {pct}`, with the positions laid out to the right of it; an unlevered book draws the same axis with no debt segment at all. Margin debt is financed the same way leverage is — only when the **Costs & interests** [simulation assumption](/docs/backtesting/simulation-assumptions) is on — see [what leverage costs](/docs/backtesting/leverage#what-does-leverage-cost). ## How does Fincanva handle it? - The Holdings view's tray states capital invested as the `Effective exposure` KPI (a percentage) and cash as the `Cash` KPI (a money amount, `Cash · margin debt` and negative-toned once it goes below zero). The `Target allocation` card states the same split again: capital invested as its large percentage, captioned `capital invested`, plus a muted `Cash` tile inside the treemap and — only once the book is levered — the signed exposure bar's `Debt` and `Positions` segments (see [why is my cash negative?](#why-is-my-cash-negative) above). - All of these read for the rebalance date selected on the page and the capital entered there — change either and every figure recomputes. - Cash is capital the plan does not deploy, not a holding you can size or a position you can see in the table. - If the strategy's last run reads **Needs re-run**, these figures come from that older run; the Portfolios page flags such a portfolio under [To update](/docs/portfolio-holdings/to-do-to-fix-to-finish-to-update). - Nothing is traded. This is the split of a paper portfolio Fincanva monitors, never an instruction to move money (see [Portfolio](/docs/getting-started/portfolio)). ## What does it look like in practice? A portfolio shows `92%` capital invested with `Cash 8%`, on 100,000 of capital: 92,000 is targeted by positions and 8,000 is not. The cause is the strategy's Leverage setting of `0.92` — it deliberately targets 92% of what it was given. Now decode the allocation beside it. The strategy's four holdings carry weights of 40 / 30 / 20 / 10 within its own slice, so their target values are 36,800 / 27,600 / 18,400 / 9,200 — 40% of 92,000, and so on. The treemap tiles read `36.8%`, `27.6%`, `18.4%`, `9.2%` and a muted `Cash 8%`, because tiles are shares of your capital and must total 100%. Both readings are correct at the same time: 40% of the strategy's slice is 36.8% of your capital. Set Leverage to `1.00` and Cash drops to 0% while the 40 / 30 / 20 / 10 mix does not change at all. *These are the split of a paper target portfolio. Neither figure is a recommended amount to hold in cash or to put to work, and Fincanva does not tell you what leverage or cash reserve to set.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/portfolio-holdings/holdings-columns # Holdings columns Holdings columns are the fields of the `Target positions & exits` table on a strategy's [Holdings](/docs/getting-started/holdings) view, one row per holding. Three of them get misread most often: **Side** says whether the target position is `Long` or `Short`, **Last** is the instrument's most recent price **in the asset's own currency**, and **Qty** is the number of shares or units the target works out to. The currency of `Last` is the trap — it is never converted to your account's [base currency](/docs/backtesting/base-currency), so a single row can pair a dollar price with a euro value. The table has eight columns, in this order: `Symbol`, `Asset type`, `Side`, `Last`, `Qty`, `Target value`, `Deployed`, `Exits`. ## What do Side, Last, and Qty mean? | Column | What it holds | Currency or unit | |---|---|---| | `Side` | `Long` — the position profits if the price rises — or `Short`, which profits if the price falls | not a number | | `Last` | the instrument's most recent price | the **asset's** currency, at that asset's own decimal precision | | `Qty` | the target quantity of the instrument | a count of shares, units, or contracts — never money | `Qty` is the same quantity concept the app calls [Contracts](/docs/strategies/contracts) in its trade and position tables. ## Why is Last in a different currency from the rest of the row? Because `Last` is the price on the instrument's own exchange, quoted the way that market quotes it, while the money columns are converted to your account's base currency so a portfolio total can be added up at all. A US-listed stock is quoted in dollars whatever currency your account keeps score in; converting that quote would show you a price no exchange displays. The row tells you when the two differ. `Target value` prints in your base currency and adds a second, muted figure in the asset's currency underneath — but **only** when the asset's currency is not your base currency. If a row shows that sub-line, `Last` is in the sub-line's currency. If it shows no sub-line, the asset trades in your base currency and every figure on the row is in one currency. The practical consequence: you cannot check a row by multiplying `Last` × `Qty` and comparing the result to `Target value`. That product is in the asset's currency, while `Target value` and `Deployed` are in yours. Convert first, or compare against the muted sub-line instead. ## How does Fincanva handle it? - `Side` renders as a badge reading `Long` or `Short`. - `Last` is formatted in the asset's currency at that asset's own number of decimals, so one row may show two decimal places and another more. - `Qty` is a plain count, shown without decimals when the target quantity is a whole number. - Take-profit and stop-loss chips in the `Exits` column are priced in the asset's currency too, matching `Last` rather than the money columns (see [Exit reason](/docs/strategies/exit-reason)). - The money columns are always in your base currency: `Target value` is the [target notional](/docs/portfolio-holdings/target-notional) and `Deployed` is what fits in whole shares (see [Target vs deployed](/docs/portfolio-holdings/target-vs-deployed)). - Every figure is a target for a paper portfolio; no order is placed and nothing is traded (see [Portfolio](/docs/getting-started/portfolio)). ## What does it look like in practice? Your account keeps score in euros and the portfolio holds a US-listed stock. The row reads `Side Long` · `Last USD 412.00` · `Qty 6` · `Target value EUR 2,500` with a muted `USD 2,700` beneath it, and `Deployed EUR 2,289`. Read it in the right currencies. The target is EUR 2,500, which is USD 2,700 at the day's rate — that is what the sub-line is for. At USD 412.00 a share, USD 2,700 buys 6 whole shares, so `Qty` is 6. Multiplying `Last` × `Qty` gives USD 2,472, which is dollars, and falls short of the USD 2,700 target by less than one share's price; that shortfall is [target vs deployed](/docs/portfolio-holdings/target-vs-deployed) at work. The `Deployed` column shows that same USD 2,472 converted back to euros, about EUR 2,289. Nothing on the row is inconsistent: `Last` is the price New York quotes, while `Target value` and `Deployed` are the euros your account measures in. *Every column describes a paper target a strategy's rules produced. A `Short` badge is a description of that target position, never a suggestion to short anything, and no row is a recommendation to buy, sell, or hold.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/portfolio-holdings/order-plan # Order plan The order plan is the list of buys, sells, and adjustments a strategy's rules imply for its next [rebalance](/docs/backtesting/rebalance), grouped into positions Entering, Exiting, and Adjusted. It shows what the portfolio would change from its current holdings to reach the new target portfolio, with an estimated turnover figure summarizing how much of the book moves. Fincanva shows it as the "Order plan" card on the Holdings view. **Also seen as:** trade list ## What is in the order plan? The order plan sorts every change into three groups: **Entering** (instruments the strategy is adding), **Exiting** (instruments it is dropping), and **Adjusted** (instruments it keeps but re-sizes). It compares the current holdings against the next rebalance's target portfolio and lists only what differs. When there is nothing to do, the card reads "No changes this rebalance". ## How does Fincanva handle it? - Groups are labelled "Entering", "Exiting", and "Adjusted"; the first time a strategy is followed, everything falls under Entering as the portfolio's first buy-in. - The plan carries an "est. turnover" figure — an estimate of how much of the portfolio changes hands at the rebalance. It is an approximation and excludes exits, so it reads slightly low whenever instruments leave the book. - The order plan describes a rebalance on paper: it is what the strategy's rules imply, not real orders sent to a broker (see [Portfolio](/docs/getting-started/portfolio)). - With no changes due, the card shows "No changes this rebalance". ## What does it look like in practice? At a rebalance, a strategy drops one instrument it no longer wants, adds two that now pass its rules, and keeps three others but changes their sizes. The order plan lists those as Exiting (1), Entering (2), and Adjusted (3), and shows an estimated turnover — say "35% turnover" — as a rough gauge of how much of the book is moving. That 35% covers only the two entries and the three re-sizings: the instrument leaving is counted as a move in the list but not in the turnover figure, so the real churn is a little higher. *The order plan describes what a strategy's rules imply, not an instruction to place anything.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/portfolio-holdings/target-allocation-treemap # Target allocation treemap The target allocation treemap is the mosaic on a strategy's [Holdings](/docs/getting-started/holdings) view that shows what the target portfolio is made of, with each tile's area proportional to that piece's share of your capital. Biggest tile, biggest position. It fills the right side of the `Target allocation` card, beside a headline `capital invested` percentage and a count of how many assets are held, and on a Combined it is interactive: click a strategy's tile to see the assets inside it. **Also seen as:** Target allocation, allocation treemap ## What the treemap shows, in words The card is split in two. On the left sit the title `Target allocation`, the number of holdings (`{n} assets`), and one large percentage captioned `capital invested`. On the right sits the mosaic: rectangles filling the card, largest first, each labelled with its name and its own percentage. Area is the only thing that encodes a value — a tile twice the size of another is twice the share of capital. The colours only separate neighbouring tiles from each other and carry no meaning of their own. Two tiles are deliberately muted rather than coloured: the `Cash` tile, which appears whenever some capital is not put to work, and the `Others (N)` tile below. Nothing in the mosaic is visual-only: every tile prints its own label and its own percentage, so the whole allocation is readable as text. ## What does "Others (N)" mean? `Others (N)` is one tile standing in for all the pieces too small to draw, where **N** is how many were folded into it. The treemap draws the seven largest pieces at a level and groups everything after that into this single tile, whose percentage is their combined share. `Others (12)` therefore means twelve holdings share that tile's area — it is a grouping, never a holding of its own, and there is no instrument called "Others". ## How does the drill-down work? On a Combined, the top level of the treemap is the **strategies** inside it: one tile per strategy, sized by its share of your capital. Clicking a strategy's tile replaces the mosaic with that strategy's own assets, and a back control labelled with the strategy's name returns you to the top level. A single strategy has nothing to drill into, so its assets are shown flat from the start. Percentages do not re-scale when you drill in. A strategy's asset tiles stay shares of your whole capital, so they add up to that strategy's own tile — not to 100%. The `Cash` tile appears only at the top level, because cash belongs to the whole book rather than to one strategy's asset list. ## How does Fincanva handle it? - Tile area = share of the [Capital](/docs/portfolio-holdings/capital) you entered; the tiles plus the `Cash` tile account for the whole 100% (see [Cash % and capital invested](/docs/portfolio-holdings/cash-and-capital-invested)). - At most seven tiles are drawn per level; everything beyond that folds into `Others (N)`, at the top level and inside a drill-down alike. - `{n} assets` counts distinct instruments held, so a holding shared by two strategies is counted once. - The mosaic redraws when you change the rebalance date or the capital, and dims while it refreshes. - The treemap shows targets for a paper portfolio — nothing in it is an order sent to a broker (see [Order plan](/docs/portfolio-holdings/order-plan) and [Portfolio](/docs/getting-started/portfolio)). ## What does it look like in practice? A Combined holds two strategies. At the top level the treemap shows `Growth 61%`, `Defensive 31%`, and a muted `Cash 8%` — so roughly two thirds of the mosaic's area is the Growth strategy, and you can see at a glance that the book is not evenly split. Click the `Growth` tile. The mosaic becomes Growth's own holdings: its seven largest, plus `Others (9)`. The biggest reads `9.4%` and `Others (9)` reads `7.1%`, so nine holdings together take less area than the single largest one. Those eight tiles add up to the same `61%` the Growth tile showed, because they are still shares of your capital, not of Growth's slice. The back control now reads `Growth`; clicking it returns you to the two-strategy view. *The treemap describes the allocation a strategy's own rules produce; it is not a recommended mix and Fincanva does not tell you how to divide your money.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/portfolio-holdings/target-notional # Target notional Target notional is the money amount a holding is meant to take in your portfolio: its target weight multiplied by your capital. It is the ideal position value the strategy's allocation aims for at a rebalance, before Fincanva rounds that amount to a whole number of shares. On the Holdings view, the portfolio's total target appears as the "Target notional" KPI, and each holding's own target appears as the "Target value" column of the "Target positions & exits" sheet. **Also seen as:** target position value ## How is target notional calculated? Multiply the holding's target weight by your [capital](/docs/portfolio-holdings/capital). A target weight is the share of the portfolio the allocation method assigns to that holding, so its target notional is simply that fraction of the capital you set for the strategy. $$ \text{target notional} = \text{target weight} \times \text{capital} $$ where target weight is the holding's share of the portfolio (0–1) and capital is the amount entered on the Holdings view — not the strategy's [starting capital](/docs/backtesting/starting-capital), which is a backtest input. ## How does Fincanva handle it? - The "Target notional" KPI adds up every holding's target and follows the capital figure the Holdings view is working from. - Target notional is the ideal, pre-rounding figure; the amount actually put to work is a little smaller once each position is rounded to whole shares. - Changing your capital rescales every holding's target notional proportionally — the weights stay the same, only the money behind them changes. - Nothing is traded: these are the target figures Fincanva monitors on paper for a [live-followed strategy](/docs/getting-started/portfolio), not real orders. ## What does it look like in practice? A holding has a target weight of 10% and you set 25,000 of capital. Its target notional is 0.10 × 25,000 = 2,500 — the position is meant to be worth 2,500. If the instrument trades at 412, that 2,500 only buys 6 whole shares, so slightly less than the full target ends up deployed. The difference between the target and what fits in whole shares is covered by [target vs deployed](/docs/portfolio-holdings/target-vs-deployed). *A target notional is the money amount a paper target portfolio implies, never a real order, and it is not a recommended amount to invest in that instrument.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/portfolio-holdings/target-vs-deployed # Target vs deployed Target vs deployed is the gap between what a holding is meant to be worth and what actually gets put to work in it, which appears because you can only buy whole shares. The target value is the ideal money amount for the holding (its [target notional](/docs/portfolio-holdings/target-notional)); the deployed amount is what that becomes once the position is expressed as a whole number of shares at the latest price. On the Holdings view these are the "Target value" and "Deployed" columns of the "Target positions & exits" sheet. ## How is the deployed amount calculated? Divide the holding's target value by the instrument's price, round down to a whole number of shares, then multiply back by the price. You cannot buy a fraction of a share, so the deployed amount is the target rounded down — the leftover is a small amount of cash, not a trade. $$ \text{shares} = \left\lfloor \frac{\text{target value}}{\text{price}} \right\rfloor \qquad \text{deployed} = \text{shares} \times \text{price} $$ where the brackets round down to the nearest whole share and price is the instrument's latest price. A `Short` position works the same way: the share count is floored on its magnitude before the side is applied, so a short's deployed amount is normally no larger than its target either. Rounding moves both sides toward zero, and the gap is under one share's worth either way. Two cases are exceptions: a quantity within a hair of a whole share is counted as that share, so deployed comes out a hair over; and a Combined whose strategies hold one instrument on opposite sides rounds each side before netting, so its net deployed amount can land well above or below the net target. [Accuracy](/docs/portfolio-holdings/accuracy) explains both, with an example. ## What counts as a large gap? The gap is normally small — under one share's worth of value for each strategy that holds the instrument. It is largest for high-priced instruments held with little capital, where a single share is a big slice of the target, and negligible for low-priced instruments or large capital. On a long it is leftover cash; on a short it is a slightly smaller position than the target. Neither is a loss. ## How does Fincanva handle it? - Deployed is normally at or below the target value, long or short — the share count is floored on its magnitude, so rounding moves toward zero; the two exceptions are above. - On a long, the difference (target value − deployed) is leftover cash that stays uninvested for that holding — no partial-share position is taken. - Share counts follow each instrument's own price, so the gap differs from one holding to the next. - [Accuracy](/docs/portfolio-holdings/accuracy) averages ratios, not these gaps: each holding's deployed amount divided by its target value, with every holding counting equally. ## What does it look like in practice? A holding has a target value of 2,500 and the instrument trades at 412. Dividing gives 2,500 ÷ 412 = 6.06, which rounds down to 6 shares. Deploying 6 × 412 = 2,472, so 2,472 is deployed against a 2,500 target — 28 stays as cash, because a 7th share (another 412) would overshoot the target. *Both figures describe a paper target portfolio, never real orders, and neither is a recommended amount to put into any instrument.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/portfolio-holdings/to-do-to-fix-to-finish-to-update # To do, To fix, To finish, To update To do, To fix, To finish, and To update are the priority-action labels on the Portfolios page. **To do** is the card that counts how many of your live-followed portfolios need attention; **To fix**, **To finish** and **To update** are the three labels its attention tile can carry — To fix for a hard failure, To finish for a [Combined](/docs/getting-started/combined) that is still missing a strategy, To update for something that merely wants a look. Together they triage your [live book](/docs/getting-started/live-book) so you know which portfolio to open first. **Also seen as:** priority actions ## What does the To do card show? The To do card shows one number — how many portfolios need attention — under the caption `priority actions`, with a quiet `{n} in order` count of the portfolios that are fine. Below that sit two tiles: the attention tile, and a `Next rebalance` tile naming the portfolio whose [rebalance](/docs/backtesting/rebalance) falls soonest. Clicking the attention tile opens a `Needs attention` list of every flagged portfolio and its reason, each row linking straight to that portfolio's [Holdings](/docs/getting-started/holdings) view. When nothing is flagged, the attention tile reads `Updates` / `All up to date` and there is nothing to open. ## What puts a portfolio in To fix? **To fix** appears for one reason: the portfolio's [run status](/docs/backtesting/run-status) is `Failed`. It is the only hard failure among the statuses — a failed run leaves no usable result at all — so a portfolio in To fix outranks everything else needing attention, and the tile names it first however many softer cases sit behind it. ## What puts a portfolio in To finish? **To finish** appears for one reason: the portfolio is an [Incomplete Combined](/docs/backtesting/incomplete-combined) — a Combined holding fewer than two strategies. It cannot be backtested at all until a second strategy is added, so the tile does not ask you to update it: the reason line reads `Add one more strategy`, and on the Home page the matching row carries the verb **Finish** rather than Run or Review. The strategy's own row in the library says the same thing at greater length on its disabled run action — "Add one more strategy to run this Combined." Every other reason a strategy is unfinished — one you started and left empty, one with no settings at all — still reads **To update**, because the missing piece there has no single sentence to name. ## What puts a portfolio in To update? **To update** covers every softer case: the portfolio still shows a usable result, but something wants a look. Where more than one problem applies, the label follows the worst one found. | What Fincanva finds | Label | |---|---| | Run status `Failed` | To fix | | Run status `Needs re-run` | To update | | Run status `To run` | To update | | An Incomplete Combined (fewer than two strategies) | To finish | | Run status `Incomplete` for any other reason | To update | | Status fine, but open configuration warnings | To update | | Run status `Up to date` or `Computing` | neither — the portfolio is in order | A portfolio whose run is perfectly healthy can still be flagged **To update** if it carries configuration warnings you have not dismissed; the tile then shows the count of those warnings as its reason instead of a status. ## How does Fincanva handle it? - The tile names the single worst item and is tinted by severity — red for To fix, amber for To finish and To update alike. An Incomplete Combined is never counted as in order, whatever its stored run status says. The complete list lives in the `Needs attention` popover, worst first. - `Computing` counts as in order: a portfolio actively recomputing is not a problem to solve. - Only strategies you [follow Live](/docs/getting-started/mark-live) are counted, so the card summarises your live book rather than every strategy you own. - The card triages your Fincanva setup, not the market: it says a result needs re-running or a setting needs review — never that a position should be bought or sold. Nothing is ever traded (see [Portfolio](/docs/getting-started/portfolio)). ## What does it look like in practice? You follow four portfolios. One finished its last run cleanly with no warnings. Two read `Needs re-run`, because you edited their settings after their last run. The fourth errored during its last run and reads `Failed`. The To do card shows `3` above `priority actions`, with `1 in order` beside the title. The attention tile shows **To fix** in red and names the failed portfolio, because a failure outranks two stale results; opening the tile lists all three, the failure first. Re-run the failed strategy and, once it completes, the tile switches to **To update** with the two portfolios still needing a re-run and the count drops to `2`. Re-run those two as well and the tile becomes `Updates` / `All up to date`. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/getting-started/find-your-strategies-and-screeners-with-search # Find your strategies and screeners with search Search finds any strategy, live portfolio or screener you own by its name, and jumps to any main page of Fincanva. Open it with **⌘K** on a Mac or **Ctrl+K** elsewhere, type part of a name, and pick the result. ## Before you start No prerequisites. Search is available on every page of the app once you are signed in, and it only ever looks at items you own. ## Steps 1. Press **⌘K** (Mac) or **Ctrl+K** (Windows, Linux). You can also select the **Search** field at the top of the sidebar, or its magnifier icon when the sidebar is collapsed — all three open the same search. 2. Type part of the name. The start of any word in it is enough, and capitals do not matter. 3. Read the results, grouped as **Strategies**, **Portfolios**, **Screeners** and **Pages**. 4. Select a result, or move to it with the arrow keys and press **Enter**. Search closes and opens what you picked. Press **Esc**, or click outside search, to close it without choosing anything; that also clears what you typed, so the next search starts from an empty field. Pressing **⌘K** or **Ctrl+K** again closes it too, but keeps what you typed, and the next **⌘K** or **Ctrl+K** reopens it on the same search. ## What you should see With nothing typed, search lists only **Pages** — the fixed destinations of the app, in the order the sidebar shows them: **Home**, **Screeners**, **Portfolios**, **Strategies · Single**, **Strategies · Combined**, and one entry per Settings page (**Settings · Profile**, **Settings · Simulation**, **Settings · Security**, **Settings · Billing**, **Settings · Usage**). Typing narrows that list to the pages whose name contains what you typed, so typing "settings" leaves every Settings page. Once you type, "Searching…" is shown briefly, then your own items appear above the pages. The **Strategies**, **Portfolios** and **Screeners** groups list at most eight matches each; **Pages** lists every page whose name matches. Where a result takes you depends on its group: | Group | What it holds | Selecting a result opens | |---|---|---| | **Strategies** | your strategies that are not followed live | the strategy's **Settings** | | **Portfolios** | your strategies that are [marked Live](/docs/getting-started/mark-live) | the strategy's **Holdings** | | **Screeners** | your saved screeners | the screener | | **Pages** | the app's main pages | that page | When nothing matches, search reads "No results found." ## How do I find my strategy? Press **⌘K** or **Ctrl+K** and type the first letters of any word in its name. A strategy you follow live is listed under **Portfolios**, not under **Strategies**, because the two groups never overlap: every strategy you own appears in exactly one of them. Selecting it under **Portfolios** opens its Holdings; selecting it under **Strategies** opens its Settings. If you would rather browse than type, the **Strategies · Single** and **Strategies · Combined** pages list every strategy you own, and the **Folder** filter there narrows the list to the [folders](/docs/getting-started/folder) you tick — one or several. Your live strategies are also listed together on the **Portfolios** page — see [live book](/docs/getting-started/live-book). ## What does search not cover? Search reads the **names** of the strategies, portfolios and screeners **you own**, and nothing else: - **Public strategies and screeners never appear.** Search only reads your Mine library; see [Mine and Public](/docs/getting-started/mine-public). To find a Public item, browse the Public tab of the library. - **Instruments are not searched here.** Finding a stock, ETP or crypto to hold is done in a strategy's asset selection, which has its own instrument search. - **Settings, filters and results inside an item are not searched** — only the item's name is. - **There is no list of recent searches and no action shortcuts**: search finds items and pages, and opens them. ## Common problems ### My strategy is not in the results Check three things in order. If the strategy is followed live, look under **Portfolios** rather than **Strategies**. If more than eight of your strategies, portfolios or screeners match what you typed, only eight are shown in that group — type more of the name to narrow it. If it is a Public strategy you have not copied, search cannot find it; use **Copy to Mine** first, and the copy becomes yours and searchable. ### Search says "No results found." for a name I know exists First check the name is yours and not a Public item's, which search never shows. If it is yours, the lookup itself may have failed: search shows the same "No results found." whether nothing matched or the lookup could not complete, so the two cannot be told apart on screen. Close search with **Esc** and search again. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/getting-started/get-started-with-fincanva-in-five-steps # Get started with Fincanva in five steps You get started with Fincanva by creating a strategy, picking how it's built, configuring it in a stepper, running a backtest, and reading the result. This guide walks a brand-new account through those five steps, start to finish, in about ten minutes. ## What do I need to start using Fincanva? You need a Fincanva account and to be signed in. No instruments or strategies need to exist yet — you create the first one here. ## How do I make my first strategy? 1. From the sidebar, open **Single** (IT: **Singole**) and select **New strategy** (IT: **Nuova strategia**). 2. Choose a strategy type under "How do you want to build this strategy?" (IT: "Come vuoi costruire questa strategia?"). Pick the shape that matches what you're building: - **Single instrument** — trade a single instrument. - **Multiple instruments** — a basket of instruments you choose. - **Screener** — let a screener pick the instruments. - **Full setup** — every setting, built from scratch. You can change this later — the type only shapes which steps come next. 3. Walk the stepper the type opens. Depending on what you picked, it shows some or all of: General (name the strategy and set how often it rebalances), Asset selection (define the instruments and screeners it trades), Risk (conditions that switch it to its Risk-Off allocation), Allocation (how capital is divided across instruments), Exit rules (take-profit and stop-loss conditions), and Review. 4. On Review, check the recap and the "Strategy alerts" panel, then select **Backtest** to save the strategy and start its first backtest. The button carries the same word in Italian. 5. Read the first result: an equity curve with headline figures including CAGR and max drawdown. ## What should I see after my first backtest? Your new strategy appears in the **Single** library, and the backtest shows an equity curve with headline figures such as CAGR and max drawdown. From the next sign-in on, that strategy is summarised for you on [Home](/docs/getting-started/home-the-page-you-land-on-after-signing-in), the page Fincanva opens first. See [What is a strategy?](/docs/strategies/what-is-a-strategy-in-fincanva) for what those parts mean, [Create a strategy](/docs/strategies/create-a-strategy-and-choose-its-instruments) for a closer look at building one, [Choosing a strategy type](/docs/strategies/choosing-a-strategy-type) for how the four types differ, and [How a backtest works](/docs/backtesting/how-backtesting-works) for what the equity curve and metrics actually compute. ## Which steps will I actually see? The stepper only shows the steps your strategy type needs: - **Single instrument** shows just Asset selection and Review. - **Multiple instruments** and **Screener** show General, Asset selection, Allocation, and Review. - **Full setup** shows all six: General, Asset selection, Risk, Allocation, Exit rules, and Review. Any step a type skips can still be added later from Review. If you'd rather configure everything yourself from the start, pick **Full setup** and then switch to **All at once** (IT: **Tutto insieme**). ## How do you sign in, and how do you keep the account yours? The sign-in screen offers [passwordless sign-in](/docs/account-security/passwordless-sign-in) first: you type your email and Fincanva sends one message carrying both a link and a 6-digit code. A password and **Continue with Google** stay available as the other two routes. [Passkeys](/docs/account-security/passkeys) are not available yet: the setting reads "Coming soon". Two account settings are worth setting up on day one rather than after something goes wrong: [two-factor authentication](/docs/account-security/two-factor-authentication), which adds a second step to every sign-in, and [active sessions](/docs/account-security/active-sessions), the list of devices currently signed in — that list is where you sign a forgotten laptop out from anywhere. ## Common problems ### Why is the backtest button disabled? A backtest needs at least one instrument selected on the strategy. Add an instrument, then select **Backtest** again — the same rule blocks saving an empty strategy. Each strategy type also enforces its own instrument or screener count before you can leave a step; see [Why can't I continue past a step?](/docs/strategies/create-a-strategy-and-choose-its-instruments#why-cant-i-continue-past-a-step) for those messages. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/getting-started/home-the-page-you-land-on-after-signing-in # Home, the page you land on after signing in **Home** is the first page Fincanva opens after you sign in, and it is a summary rather than a workspace: it tells you what your strategies did, what needs attention, and what you were last working on, then sends you to the page that can act on it. This guide reads it top to bottom and answers the things about it that look like faults and are not. ↗ See this in Fincanva — the Home page ## How is Home laid out? At the top, either a date band with one true sentence about the strategies you follow live or a **Needs you** list of the ones asking something of you, with tiles beside it that agree with whichever it is; then a rail holding those same strategies ranked, and a **Recently edited** block, reading your whole book, that gets you back to work. If you follow nothing live, **Recently edited** is the whole page. While a backtest is running, Home keeps itself up to date — the verdict and the tiles follow the run without you reloading the page. ## What do I need before Home is useful? Nothing beyond a signed-in account, and at least one strategy [marked Live](/docs/getting-started/mark-live) before the top of the page has anything to say. Home picks what to show you: a **first-run** version until you have saved anything at all, **Recently edited** on its own while nothing is marked Live, and the full board once something is. ## What does Home show on a brand-new account? Until you have saved a strategy or a screener, Home shows three cards instead of a board — **Build a strategy**, **Screen the market** and **Follow it live** — each stating what that route is for, plus the **Fincanva templates** rail underneath. There is no live book and no status tile on this version, because there is nothing yet for either to be about. Home switches to the full board from the first save onwards. ## Why does Home show me only "Recently edited"? Because you have saved strategies but have not [marked any of them Live](/docs/getting-started/mark-live), and everything above **Recently edited** describes your live strategies only. With none of them live there is nothing for the date band, **Needs you** or the tiles to be about, so Home leaves the whole top half out rather than printing a green all-clear over an empty set. This is not the first-run version: that one appears only while you have saved nothing at all, and it shows three route cards instead of **Recently edited**. Mark one strategy Live and the full top half is there the next time you open Home. ## What is on Home once I have strategies? Two halves that describe two different sets. **Everything above Recently edited is about the strategies you have [marked Live](/docs/getting-started/mark-live), and only those.** **Recently edited** is about your whole book, every strategy in it, live or not. The live half is one card at the top of the page, and that card has two layouts: a **Needs you** list when something is asking you for an action, and a dated verdict band when nothing is — never both at once, which is what [Why does the top of Home change shape from one day to the next?](#why-does-the-top-of-home-change-shape-from-one-day-to-the-next) below is about. Under that card sits **Your live book**, the ranked rail of your live strategies, covered further down. Then the whole-book half: **Recently edited**, covered below too. The **Browse Fincanva templates** link sits last and belongs to neither half — it opens the **Public** tab of the strategy library, which is Fincanva's own catalogue rather than anything of yours. Most mornings most of your book will read **Needs re-run**, because a result computed against an earlier market day is no longer current even when you have changed nothing — see [run status](/docs/backtesting/run-status). **Needs you** does not fill up with them, because it lists live strategies only and those are the ones Fincanva keeps current for you. One you merely saved arrives at **Needs re-run** because that is what you chose for it, and Home does not ask you to undo the choice. ## Why does the top of Home change shape from one day to the next? Because the top of Home is one card with two layouts, and it shows exactly one of them: a **Needs you** list when something is asking you for an action, and a dated verdict band when nothing is. They never appear together, so a tile that was there yesterday can be gone today. **When something needs you**, the card is a **Needs you** header with a count beside it, then up to five of your live strategies, each with the reason and the folder it lives in: one that **failed**, one that is **incomplete**, one you have never run, one with open configuration warnings, and one whose result is no longer current. Beside that list sit two tiles, **Next rebalances** and **Live book status**. The **View all in Portfolios** link at the top, and the **View all N** line under the rows, both open **Portfolios**, the page that lists exactly these strategies. There is no date band and no **Followed live** tile in this layout. **When nothing needs you**, the card is the date band instead: `Today · {date}`, in your browser's own [time zone](/docs/backtesting/time-zone), with one sentence of verdict over your live strategies — for example `All 12 live strategies up to date`, `3 live strategies still computing`, `Couldn't reach the engine`, or a line saying Home is showing the most recently updated of a larger number of them. Beside it sit **Followed live** and **Next rebalances**. There is no **Needs you** block and no **Live book status** tile in this layout. Two of the three tiles are therefore conditional. **Followed live** — how many strategies you are following live, with their **Median 1M** and how many are **Positive 1M** — appears only while nothing needs you. **Live book status** — your live strategies split into `up to date`, `computing`, `to re-run`, `to run`, `failed` and `incomplete` — appears only while something does. **Next rebalances** appears in both. Which layout you get is decided in a fixed order, first match wins: something needs you, then Home could not reach the engine, then Home read only part of your live book, then something is still computing, then everything is up to date. **Needs you** comes first because an action outranks a wait, and the other four are all sentences of that same band. The order is also why `N live strategies still computing` is hard to catch in practice: a strategy that is computing is not something Home asks you to act on, so that sentence only ever appears on a live book where nothing else is asking for anything. ## Why is a strategy I never marked Live not flagged on Home? Because the top half of Home describes your live strategies and nothing else, and the rule has no exception for a broken one: a strategy you never [marked Live](/docs/getting-started/mark-live) is not counted, ranked or flagged up there even when its last run **failed** or it is still **incomplete**. There is no other place on Home that flags it either. It is not lost, and nothing about it has changed. It keeps its own [run status](/docs/backtesting/run-status) chip wherever it is listed, it appears in **Recently edited** if it is one of the five you touched most recently, and it is in **Strategies** with the rest of your book. Mark it Live and it joins **Needs you** the next time you open Home. ## What is in "Your live book"? **Your live book** is the ranked rail of the strategies you have [marked Live](/docs/getting-started/mark-live), and only those. Each card carries the strategy's return over the chosen window, its folder and type, and a small curve. Above the rail, **Return window** switches the headline figure between **1M**, **YTD** and **1Y**. If no live strategy has a figure for the window you pick, the rail says so and invites you to pick another one rather than showing an empty rail. The rail stops at eight cards. When you have more than that, it ends with **View all N live strategies**, which opens the full list. Returns shown here are past results. ## Why does the curve not change when I change the return window? Because the curve is always the one-year series, whatever the **Return window** says. The card labels it **1Y curve** for that reason, and a card with less than a year of history reads **No 1-year curve yet** instead of drawing a shorter one. **Return window** re-windows the headline percentage only. It is worth knowing before you compare a **1M** figure against the shape of the curve beside it, because those two are measuring different spans on purpose. ## What is in "Recently edited"? Two columns — **Strategies** and **Screeners** — each listing the five you touched most recently, so you can get back into something you left half-built. This is the one block on Home that reads your **whole** private book: it lists what you edited last whether or not you have [marked it Live](/docs/getting-started/mark-live). **The Screeners column is the only place in Fincanva that lists your saved screeners.** Nowhere else does. That is why the two columns are not symmetrical: **Strategies** ends with an **All N** link to the full library, and **Screeners** ends with nothing, because opening **Screeners** from the sidebar starts a new screener rather than showing a list of the ones you have. ## What happens when I pick a strategy type from Home? The strategy is created immediately, before you have configured anything. **New strategy** opens the type tiles, and pressing one creates a real strategy and takes you into its walk. So there is no draft state to discard: if you change your mind and leave the walk, the strategy stays in **Strategies**, empty. **Deleting it from the Strategies list is how you undo it.** The same is true if you close the dialog while the strategy is being created — Fincanva tells you it was created and leaves you where you are, because by then it exists. ## Why does Home say it is showing only some of my strategies? Because Home reads a capped slice of your book, most recently updated first, and says so on the date band when you have more live strategies than it read. The strategies it did not read are the ones you have touched least recently. The band counts live strategies, like everything else in the top half — `Showing the 500 most recently updated of your 640 live strategies` — and every count beside it describes what Home read, not necessarily the whole of your live book. ## Limits and edge cases ### Why did a failed strategy disappear from my live book? Because the rail ranks strategies by their returns, and a strategy whose last run **failed** has no returns to rank. That is intended, and it is not a strategy that has been lost: it moves to **Needs you** above, which is the block that owns what is broken. That move happens only for a strategy you have [marked Live](/docs/getting-started/mark-live). A failed strategy you never marked Live was never in the rail and does not appear in **Needs you** either — see [Why is a strategy I never marked Live not flagged on Home?](#why-is-a-strategy-i-never-marked-live-not-flagged-on-home) above. The split is the same across the live half of the page — **Needs you** owns what is wrong, the live book owns what is working. A strategy that merely **needs a re-run** is a different case: it keeps its last known figures and stays in the rail, dimmed. ### What does Home show when it cannot reach the engine? It shows your book as it was last recorded, dated, instead of reporting an all-clear. Where that dating appears depends on which layout the top of Home is in. On the verdict band, the verdict itself reads `Couldn't reach the engine`, with `Couldn't reach the engine — showing results as of {date}.` under it; that verdict outranks both the "showing the most recently updated of N" line and the `N live strategies still computing` line, and it is never the green all-clear. When something needs you, that same `Couldn't reach the engine — showing results as of {date}.` line sits above the **Needs you** list instead, and the **Live book status** tile beside it keeps its counts with `Couldn't reach the engine` next to them, because those are counts of what was last recorded rather than of what is true right now. Each strategy keeps its last recorded [run status](/docs/backtesting/run-status) and figures, dimmed — unless that recording predates the latest market data, in which case the chip reads **Needs re-run** rather than repeating a state that is no longer true. Two blocks have nothing recorded to fall back on and say so rather than assert an absence. **Next rebalances** has no saved rebalance dates, so it says `Couldn't reach the engine` instead of `No upcoming rebalances`. **Your live book** does the same instead of telling you no live strategy has a figure for the window you picked. Every row in **Needs you** still carries its chip during an outage, because each chip names something you can do to the strategy itself: one you have never run reads **Run**, one whose result is no longer current reads **Re-run**, one whose last run failed reads **Fix**. Home keeps retrying on its own and stops as soon as the engine answers, so the page recovers without you reloading it. ## Related For what those figures mean, see [How a backtest works](/docs/backtesting/how-backtesting-works) and [Metrics explained](/docs/analysis/what-every-number-in-performance-metrics-means); for the workflow Home sits at the centre of, see [The Fincanva loop](/docs/getting-started/the-fincanva-loop). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/getting-started/the-fincanva-loop # The Fincanva loop The Fincanva loop is the core workflow of the product, and it has three stages: you **build** a strategy, **backtest** it on real market history, and **analyze** the result — then refine what you built and go round again until it holds up. The forward path runs one way, Build → Backtest → Analyze; refining is the only edge that goes back. An idea enters the loop at Build, and a strategy leaves it when you [Mark Live](/docs/getting-started/mark-live) to follow it going forward — which is monitoring only, and reversible. If you are new to Fincanva, [What is Fincanva, and what can you do with it?](/docs/getting-started/what-is-fincanva-and-what-can-you-do-with-it) covers the product itself. For the click-by-click version of the loop, follow [Get started with Fincanva in five steps](/docs/getting-started/get-started-with-fincanva-in-five-steps). ## What are the three stages of the Fincanva loop? The Fincanva loop has three stages, and every idea you test goes through all three: 1. **Build** — you define the strategy: what it may hold, how capital is spread across it, when it turns defensive, and when it exits a position. 2. **Backtest** — Fincanva replays that strategy over real market history and reports what it would have produced. 3. **Analyze** — you read the evidence: the equity curve, the metrics, the drawdowns. Analyze is a decision point, not an end point. If the result holds up you leave the loop and Mark Live; if it does not, you refine — back to Build — and run it again. Nothing else in the app sits outside this shape: screeners feed Build, and a [Combined](/docs/getting-started/combined) runs the same three stages one level up, over several strategies at once. {/* VISUAL: svg-diagram — the three-stage cycle Build → Backtest → Analyze with the refine edge closing it, Idea entering at Build and Mark Live exiting at Analyze — tracked in VISUAL_BACKLOG */} ## What do you configure in the Build stage? Build is the single stage in which a strategy is defined — there is no separate stage for picking instruments, because choosing what a strategy holds is part of building it. In Build you set: - **What it may hold** — a basket of instruments you choose, or a [screener](/docs/getting-started/screener) that picks them by rule from a [universe](/docs/getting-started/universe). - **When it turns defensive** — the [risk conditions](/docs/strategies/risk-conditions) that switch the strategy to its [Risk-Off allocation](/docs/strategies/risk-on-and-risk-off) when they trigger. - **How capital is spread** — the [allocation method](/docs/strategies/allocation-and-allocation-method) that weights capital across those instruments, and how often the strategy [rebalances](/docs/backtesting/rebalance) back to those weights. - **When a position closes** — the [take-profit](/docs/strategies/take-profit) and [stop-loss](/docs/strategies/stop-loss) exit rules applied to each position. Which of those a strategy requires depends on its [strategy type](/docs/getting-started/strategy-type) — **Single instrument**, **Multiple instruments**, **Screener**, or **Full setup** — and the parts a type does not require stay optional. You do the building in one of two editing views: [Step by step](/docs/getting-started/step-by-step) puts one decision on screen at a time, while [All at once](/docs/getting-started/all-at-once) lays every settings card out on a single page in any order. Same strategy, same settings; see [Step by step and All at once](/docs/strategies/step-by-step-and-all-at-once) for which to use when. One further set of choices shapes what a run *reports* rather than what the strategy *does*: the [simulation assumptions](/docs/backtesting/simulation-assumptions) — whether trading costs, tax, and profit compounding are applied. They are not part of the strategy itself, and they are not set in the editor: the three toggles sit above the results in the Analyze stage, and the rates behind them are saved in Settings. ## What does the Backtest stage do? The Backtest stage replays the strategy you built over real market history and reports what it would have produced. A [backtest](/docs/getting-started/backtest) applies that strategy's own allocation, rebalancing, risk conditions, and exit rules step by step across the period, and it runs from the earliest date your instruments and configuration allow through the latest available market close — the end date follows the newest market data, not today's calendar date. Nothing is traded and nothing is forecast: a backtest is a simulation over the past. [How backtesting works](/docs/backtesting/how-backtesting-works) covers what it computes and what it cannot. ## What do you read in the Analyze stage? The Analyze stage is where you read the evidence a backtest produced and decide what to do with it. Three things carry most of that reading: the [equity curve](/docs/analysis/equity-curve), which shows the shape of the whole run rather than only its final number; the performance metrics; and the [max drawdown](/docs/analysis/max-drawdown), the deepest fall from a peak the strategy sat through. [What every number in Performance Metrics means](/docs/analysis/what-every-number-in-performance-metrics-means) explains each figure in turn. The question this stage answers is a single one — does this result hold up, or is there something to change? ## How does refining close the loop? Refining closes the loop by sending you back to the Build stage: you change something about the strategy, backtest it again, and read the new result against the old one. That is the only edge in the loop that runs backwards — Build → Backtest → Analyze goes one way, and refining is the way round. There is no separate "refine" screen: it is the same saved strategy, edited and run again. Changing a setting that feeds the backtest leaves the last result on screen and marks it **Needs re-run** until you re-run it. Most strategies go round the loop several times before their result holds up. ## What starts the loop, and what ends it? An idea starts the loop and **Mark Live** ends it. The idea is whatever you want to test — a market, a rule, a rebalancing habit — and it enters at Build, where picking a [strategy type](/docs/getting-started/strategy-type) turns it into something the app can actually run. [Mark Live](/docs/getting-started/mark-live) is the exit: it starts following the strategy going forward instead of only over history. Live is monitoring only — nothing is traded, no order reaches a broker, and no real money moves — and **Unfollow** reverses it at any time, which puts the strategy back within reach of the loop. ## Limits and edge cases - **Build is one stage, not two.** Instruments, allocation, risk conditions, and exit rules are all part of building a strategy. **Step by step** shows them as separate steps on screen and **All at once** shows them as cards on one page, but neither is a distinct stage of the loop. - **Not every part of Build applies to every strategy.** The strategy type decides which settings a strategy requires; the rest remain optional and can be added later. - **A backtest is evidence, not a promise.** Analyze tells you what would have happened over the period tested. Going round the loop can improve a strategy; it never removes uncertainty. - **Refine is the only loop-back.** The forward path has no shortcuts and no side branches — a result you want to change sends you back to Build, never anywhere else. - **Mark Live is reversible, and it changes nothing about history.** Following a strategy changes what you track going forward; a backtest already run is unaffected. - **Only a Live strategy is re-run for you.** A strategy you have marked Live is refreshed as new market data arrives; one you have only saved goes **Needs re-run** after a data refresh and stays there until you run it again — see [run status](/docs/backtesting/run-status). *The loop is a workflow for testing ideas against history, not a recommendation to act on any result.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/getting-started/the-nine-biases-fincanva-helps-you-avoid # The nine biases Fincanva helps you avoid Backtesting a strategy is easy to get wrong: a handful of well-known research biases can make a strategy look far better on history than it really was. Fincanva is built so that a backtest replays your exact rules over real historical market data, which structurally reduces nine of these biases: look-ahead, survivorship, selection, overfitting, data-snooping, cherry-picking, confirmation, cost-ignoring, and data-quality bias. No tool removes bias entirely — the choices you make still matter — but the sections below explain each bias and the product behavior that works against it. If you are new here, start with [What is Fincanva?](/docs/getting-started/what-is-fincanva-and-what-can-you-do-with-it) and [The Fincanva loop](/docs/getting-started/the-fincanva-loop), then [Get started with Fincanva in five steps](/docs/getting-started/get-started-with-fincanva-in-five-steps). ## How does Fincanva reduce look-ahead bias? Look-ahead bias is using information in a test that would not have been available at the time the decision was made — for example acting on a price or a result before it was actually known. A Fincanva backtest works against this by replaying your strategy's rules in chronological order, using only the data available up to each point in time as it moves forward through history (a walk-forward replay). It runs to the latest available market close and never into the future, so a decision at any date can only rely on what was known by that date. See [How backtesting works](/docs/backtesting/how-backtesting-works) for the replay in more detail. ## How does Fincanva handle survivorship bias? Survivorship bias is testing only on the instruments that survived to today, ignoring the companies that failed, merged, or were delisted — which flatters results because the losers have been removed. Fincanva's data removes it by construction: delisted instruments are retained rather than dropped, each instrument participates only across the span in which it actually existed, and [index membership](/docs/data-methodology/index-lists-and-point-in-time-constituents) is resolved as of the simulated date rather than as it stands today. What stays yours is the choice of universe and period — a hand-typed list of names you know today reintroduces the bias whatever the underlying data contains. ## How does Fincanva reduce selection bias? Selection bias is drawing conclusions from a sample of instruments or periods that is not representative — typically a small, favorable subset picked with hindsight. Fincanva lets you test over a broad instrument universe and a long history rather than a hand-chosen slice that happens to look good. Testing the same rules across a wide universe and a long span makes a result harder to attribute to a lucky handful of names or a single kind stretch of the market. ## How does Fincanva reduce overfitting? Overfitting — also called curve-fitting — is tuning a strategy so tightly to past data that it captures noise rather than a durable signal, so it looks excellent on history and fails afterwards. In Fincanva, you define the rules; Fincanva does not auto-tune or optimize your parameters to fit the past for you, so a backtest shows only what your exact stated rules would have done — which keeps you in control of how closely your rules are shaped to history. ## Can Fincanva prevent data-snooping bias? Data-snooping bias is trying many variations of a strategy until one looks good by chance, then treating that lucky result as if it were real signal. Fincanva does not prevent this for you: the app lets you test freely, so being aware of how many variants you tried — and treating a result that only appeared after many tries with caution — is the discipline this leaves to you. If you run dozens of variants and keep only the best-looking one, that result may reflect chance rather than a repeatable edge — the more combinations you try, the more likely one looks good for no durable reason. ## How does Fincanva reduce cherry-picking bias? Cherry-picking bias is reporting only the favorable results or the periods that worked, while quietly omitting the rest. A Fincanva backtest reports the full-period result together with its drawdowns, not just the stretches that went well — harder to cherry-pick when the same run surfaces the whole history, including the worst peak-to-trough falls; see [drawdown](/docs/analysis/max-drawdown) for what those falls measure. ## How does Fincanva reduce confirmation bias? Confirmation bias is seeing what you expected to see and discounting evidence that contradicts it. A Fincanva backtest applies the same rules mechanically across the whole history regardless of what you hoped would happen, surfacing the full result — including losses and the maximum [drawdown](/docs/analysis/max-drawdown), with headline figures like [CAGR](/docs/analysis/cagr) — rather than only the parts that confirm your idea, giving the rules a chance to disagree with you. ## How does a Fincanva backtest account for trading costs and taxes? Cost-ignoring bias is pretending trading is free — leaving out the costs and taxes that a real account would pay, which inflates results. A Fincanva backtest can include these through its simulation assumptions: under **Include** you can switch on **Costs & interests** ("Trading costs, financing & interest"), **Taxes** ("Tax on dividends & realized gains"), and **Reinvest profits**, so a result is not cost-blind. Turning these on brings a backtest closer to what a real account would have kept after costs and tax. ## How does data quality affect a Fincanva backtest? Data-quality bias is when conclusions are distorted by poor, stale, or incomplete data rather than by the strategy itself. Fincanva runs backtests on broad, daily-updated market data covering many asset classes and regions, and a backtest runs to the latest available market close. Wider, current data across more of the market gives a strategy less room to look good only because the data behind it was thin or out of date. *Reducing a bias is not the same as removing it.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/getting-started/what-is-fincanva-and-what-can-you-do-with-it # What is Fincanva, and what can you do with it? Fincanva is a research and simulation tool: a strategy-building and backtesting platform for investment strategies on historical market data. Concretely, it lets you build a strategy, combine strategies, screen instruments, backtest, analyze the result, and refine what you built — all before you decide whether to follow a strategy over time. ## What kind of tool is Fincanva? Fincanva is a research and simulation tool, not an advisor: it lets you design a strategy's rules and see how those rules would have behaved on historical data, rather than telling you what to buy or sell. The unit you design is a strategy — a saved set of instruments plus the rules for allocating capital and changing positions; see [What is a strategy?](/docs/strategies/what-is-a-strategy-in-fincanva) for what it contains. ## What can you do with Fincanva? You can do six things with Fincanva, in the order most strategies move through them: - **Build a strategy** — save a set of instruments together with allocation and rule settings as a strategy. See [Create a strategy](/docs/strategies/create-a-strategy-and-choose-its-instruments). - **Combine strategies** — blend several strategies into one [Combined](/docs/getting-started/combined). - **Screen instruments** — use a screener to select instruments by rule instead of picking them one by one. - **Backtest** — run a strategy over historical data to see how its rules would have behaved. - **Analyze results** — read the equity curve and headline figures such as [CAGR](/docs/analysis/cagr) and [max drawdown](/docs/analysis/max-drawdown). - **Refine and follow** — adjust the rules and re-run the backtest, and optionally follow a strategy going forward as new data arrives. [The Fincanva loop](/docs/getting-started/the-fincanva-loop) walks through how these steps connect in practice; [Get started with Fincanva in five steps](/docs/getting-started/get-started-with-fincanva-in-five-steps) walks a new account through them directly. ## How current is the data behind a backtest? Fincanva's market data updates daily, so a backtest runs to the latest available market close. Re-running the same strategy on a later day can produce a different result, simply because there is more history for it to run over. ## Limits and edge cases [Biases Fincanva helps you avoid](/docs/getting-started/the-nine-biases-fincanva-helps-you-avoid) covers the reasoning pitfalls a research-and-simulation workflow is built to counter. Nothing here is a commitment: everything you build stays yours to remove, and [account deletion](/docs/account-security/account-deletion) is a scheduled request with a 14-day window you can cancel from, not an immediate erase. ## Related For what a strategy is made of, see [What is a strategy?](/docs/strategies/what-is-a-strategy-in-fincanva). For what actually happens when you run one, see [How a backtest works](/docs/backtesting/how-backtesting-works). To try it yourself, follow [Get started with Fincanva in five steps](/docs/getting-started/get-started-with-fincanva-in-five-steps). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/getting-started/all-at-once # All at once **All at once** is Fincanva's single-page strategy editing view: every settings card of a [strategy](/docs/getting-started/strategy) sits on one page, so you can change any part in any order instead of following a step sequence. **All at once** and [Step by step](/docs/getting-started/step-by-step) are the product's official pair of editing views — the same strategy, the same settings, a different amount of it on screen at once. **All at once** is the view you open to change a strategy you already have. ## What does the All at once view show? **All at once** lays out one card per part of the strategy, each editing that part directly: | Card | What it controls | |---|---| | **Strategy type** | which [strategy type](/docs/getting-started/strategy-type) the strategy is, and therefore which cards apply | | **Rebalance** | the strategy's name and its [rebalance](/docs/backtesting/rebalance) cadence | | **Asset selection** | the instruments the strategy may hold — see [asset-selection modes](/docs/getting-started/asset-selection-modes) | | **Allocation** | the [allocation method](/docs/strategies/allocation-and-allocation-method) that weights capital across those instruments | | **Risk** | the [risk conditions](/docs/strategies/risk-condition) that switch the strategy to its Risk-Off allocation | | **Position exits** | the [take-profit](/docs/strategies/take-profit) and [stop-loss](/docs/strategies/stop-loss) rules applied to each position | A part that does not apply to the strategy's type is not shown; a part that is optional for that type appears as an **Add** row until you set it up, and then becomes a full card. ## How does All at once differ from Step by step? The difference is exposure, not capability: **All at once** shows every applicable card together, while **Step by step** shows one step at a time and hides the optional ones behind its Review step. Neither view can set something the other cannot, and neither holds a private copy of the strategy — a change made in one is the same change in the other. **Step by step** is the better fit for a first build, where the order of decisions is itself the help; **All at once** is the better fit for changing two or three unrelated settings, because you do not walk past the steps in between. ## What does All at once add for a Combined? For a [Combined](/docs/getting-started/combined), **All at once** adds the Combined's own layer on top of the per-strategy cards: a section listing the strategies it holds, and a [Combined-level](/docs/getting-started/combined-level) allocation that splits capital between them. Each member strategy keeps its own set of cards, edited scoped to that strategy. A Combined holding fewer than two strategies is an [Incomplete Combined](/docs/backtesting/incomplete-combined) and cannot run. ## How does Fincanva handle it? - Every card edits the live strategy in the page's own state, so a change is visible immediately — but it only persists once you save. - Changing a setting that feeds the backtest leaves the last result standing and flips its [run status](/docs/backtesting/run-status) to **Needs re-run** until you re-run. - Switching the **Strategy type** card changes which cards the strategy uses, so it is confirmed first: the confirmation names the cards the new type requires, and any card the new type does not require that is currently configured is reset to its defaults. - A **Step by step** control reopens the same strategy in the walk-through, and nothing is lost either way. - A public strategy opens in **All at once** read-only — it cannot be saved directly; see [Mine / Public](/docs/getting-started/mine-public). ## What does it look like in practice? You have a **Full setup** strategy and want to change three unrelated things: the rebalance cadence, the allocation method, and the stop-loss level. In [Step by step](/docs/getting-started/step-by-step) that is three separate steps reached in the rail's fixed order, with the steps in between on the way. In **All at once** all three cards — **Rebalance**, **Allocation**, and **Position exits** — are on the same page: you edit each in place, save once, and re-run once. The strategy that results is identical either way; only the number of screens you passed through differs. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/getting-started/asset-type # Asset type Asset type is the market family an instrument belongs to. In a screener it is the widest cut of the [universe](/docs/getting-started/universe) and the first choice you make in it — **Stocks**, **ETPs**, or **Crypto**: exactly one is active at a time, and the one you pick decides which other universe filters exist. Because only one is active, a screener set to Stocks can never return an ETP, and a screener set to ETPs can never return an individual company's shares. Next to an individual instrument the field is wider — Fincanva recognises nine asset types there, including ones the screener never offers. **Also seen as:** Asset class — the industry's usual name for this field and also the label of one of the nine asset types described below. ## What are the three asset types? The screener's universe selector offers three, and each covers a different family of instruments and brings its own set of universe filters: | Asset type | What it covers | Universe filters it exposes | |---|---|---| | Stocks | Shares in individual companies | Country · Exchange · Asset subtype · Index · Sector | | ETPs | Exchange-traded products — funds and notes that trade like shares | Country · Currency · Exchange · Asset subtype | | Crypto | Cryptocurrencies | none | Crypto has no further universe filters, so choosing it narrows the universe to crypto and nothing else. Stocks is the type a new screener starts on. ## How is asset type different from asset subtype? Asset type is the family; **asset subtype** is the specific instrument kind inside it. Choosing the ETPs asset type gets you every exchange-traded product; the asset subtype filter then narrows that to ETFs, ETNs, ETCs, and so on — see [Asset subtypes](/docs/screeners/asset-subtypes) for what each abbreviation means. Three labels that look like they belong in this taxonomy do not: - **ETP** is an asset *type*, not a subtype — it is the parent of ETF, ETN, ETC, and the rest. - **ADR** is a value of the **Country** filter, not a type or a subtype. - **OTC** is a value of the **Exchange** filter, not a type or a subtype. ## Why do some instruments show an asset type the screener never offers? Because two different fields carry the name **Asset type**, and only one of them is limited to three values: - **A screener's asset type** is the universe choice, made with the first button in the screener's filter strip — the one that shows Stocks, ETPs or Crypto. It offers three values — Stocks, ETPs, Crypto — and exactly one is active. - **An instrument's asset type** belongs to the instrument itself and comes from Fincanva's reference data. It can take nine values. It is what the **Asset type** column shows in Positions (the **By symbol** table), in Holdings (the **Target positions & exits** sheet) and in a strategy's selected-instruments table, and what the instrument picker shows beside an instrument's ticker. The **Asset type** column of a screener's results shows the instrument's own asset type too, but there it always matches the screener's active type, because a screener returns nothing else. The nine values an instrument's asset type can take, as the app labels them: | Label in the app | Selectable in a screener? | |---|---| | Stocks | Yes | | ETPs | Yes | | Crypto | Yes | | Currencies | No | | Funds | No | | Futures | No | | Indices | No | | Macro indicators | No | | Asset class | No | The six the screener never offers are not something you screen for: they reach a strategy as a benchmark or a reference series rather than as something the screener returns. Two of the nine are not self-explanatory: - **Macro indicators** — a market or macro series rather than a tradable instrument: the Shiller PE, the S&P 500 dividend yield, and their kind. - **Asset class** — a long-history return series for a whole asset class, going back further than any individual instrument does. "US Large Cap Value Investment Class 1926" is one. Neither is something you buy. Both exist so a backtest can be measured against a long history, which is why they show up beside instruments you do hold. ## How does Fincanva handle it? - Exactly one asset type is active at a time — picking a new one replaces the current one rather than adding to it. - Switching asset type hides the current type's universe filters but does not discard them: the app confirms with "Switching to `{target}` hides these universe filters: `{filters}`. You can restore them by switching back", and switching back restores what you had selected. - Each asset type carries its own default selections, so Stocks and ETPs remember their filters independently. - Asset type is also a column in a screener's results, labelled **Asset type** and explained in-app as "Stock, ETF, crypto, and so on." ## What does it look like in practice? You want exposure to semiconductors, and there are two ways to get it. A chipmaker's ordinary shares are an instrument of asset type **Stocks**: with Stocks active you can narrow by Sector, so a screener can look for the companies themselves. A semiconductor ETF that holds those same companies is an instrument of asset type **ETPs**: switch to ETPs and the Sector filter disappears (ETPs have no Sector filter) while a Currency filter appears instead. The two never mix in one screener. A screener set to Stocks returns the chipmaker and never the ETF; set it to ETPs and it returns the ETF and never the chipmaker — even though both give you exposure to the same companies. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/getting-started/asset-selection-modes # Asset-selection modes Asset-selection modes are the three ways a strategy decides which instruments it may hold: **Basket**, where you name the instruments yourself; **Screen**, where one screener picks them by rule at every rebalance; and **Compose**, where a basket and screener pools work together. They are peer modes on the strategy's **Asset selection** card, and the mode you are in is what the card's controls edit. The set of instruments that survives the mode is the strategy's [universe](/docs/getting-started/universe). **Also seen as:** Easy and Pro, Pick assets, Build a screen ## What do Basket, Screen, and Compose do? Each mode answers "what may this strategy hold?" a different way. | Mode | How instruments are decided | What you edit | |---|---|---| | **Basket** | you name them — the instruments you add are the whole universe | a search field plus the table of instruments you have added (on a Single instrument strategy, one slot and a **Change** affordance) | | **Screen** | one [screener](/docs/getting-started/screener) selects them by rule, re-evaluated at every rebalance | that screener's [filters](/docs/getting-started/filter) and its universe | | **Compose** | a basket sets the scope, then screener pools qualify and reject inside it | the basket, the **Qualify** and **Reject** pools, and the selection rules | An empty Basket is a real state, not a missing one: with nothing named, the strategy draws from the entire market and the card's readout says **All instruments**. ## How do Easy and Pro relate to the three modes? **Easy** and **Pro** are the two screening modes the three asset-selection modes are built on, and they are underlying state rather than a control you operate: no surface shows an Easy/Pro toggle. The mapping is exact: **Basket** is Easy applied to instruments you name, **Screen** is Easy applied to a screener, and **Compose** is Pro. That is why Pro-only settings survive a trip through Easy — they belong to the same strategy, just to controls Easy does not show, and it is why the confirmation you get when leaving Compose still names both. **Step by step** and [All at once](/docs/getting-started/all-at-once) present these three states the same way, as one **Basket · Screen · Compose** control — and only on a Full setup strategy, as the next section explains. ## Which modes does each strategy type offer? The card only offers the modes the [strategy type](/docs/getting-started/strategy-type) supports — there is no greyed-out placeholder for one it does not. | Strategy type | Modes offered | |---|---| | **Single instrument** | Basket | | **Multiple instruments** | Basket | | **Screener** | Screen | | **Full setup** | Basket · Screen · Compose | The strategy type is a constraint on the card, not a starting preset: three of the four types have exactly one mode, so for them the **Basket · Screen · Compose** control is not shown at all — there is nothing to switch between. Only **Full setup** shows it, in **Step by step** exactly as in **All at once**. **Compose is therefore reachable from Full setup alone**, and with it the Qualify and Reject [screener pools](/docs/getting-started/screener-attach); a Screener strategy that needs a rejecting pool becomes a Full setup one. Two consequences follow inside Basket. On **Single instrument** the mode is a single slot with a **Change** affordance rather than a list you add to — picking another instrument replaces the one held instead of extending a basket. And the Basket's **Filters** strip exists only under **Full setup**; on the two instrument types the mode names instruments and nothing else. Changing type is not how an existing strategy loses a mode. A saved strategy whose content needs a wider surface than its type offers — instruments and a screener together, a second qualifying screener, a rejecting pool — is read as the wider type instead, so the card can still show everything the strategy holds. Nothing is trimmed to fit, and the widening never runs the other way: a Full setup strategy holding a single instrument stays Full setup. ## What is the working scope in Compose? In Compose the basket is the working scope — the set of instruments the attached screeners are evaluated against. With instruments in the basket the screeners are evaluated against those instruments alone; with an empty basket they are evaluated against the entire market. This is the one mode where naming instruments and screening by rule are not alternatives: the basket bounds the search, and the [screener pools](/docs/getting-started/screener-attach) decide who inside it is held. Compose also groups the strategy's **Selection rules** beside the pools — [**Max positions**](/docs/strategies/max-positions), the cap on how many instruments are held at once; [**Max hold**](/docs/strategies/max-hold-months), how long a position may be held; and [**Reinvest delay**](/docs/strategies/reinvest-delay), how long an instrument stays out of the strategy's choices after its position closes. ## How does Fincanva handle it? - The card's readout names the current state rather than the mode: **All instruments** for an empty Basket or an unfiltered Screen, a count of assets, a count of filters, or an assets-and-screeners pair in Compose. A Single instrument strategy shows no count — the one slot is already in view. - Entering Compose, and switching between Basket and Screen, are non-destructive. Both apply to Full setup, the only type that offers more than one mode. - On Basket the strategy holds what you picked: **Max positions** is set to the number of instruments in the basket rather than left as a control, so nothing you named is dropped for being over a cap. It stays a control on Screen and in Compose. - Leaving Compose can leave settings that Basket and Screen have no control for. Fincanva confirms first and keeps them, and the confirmation names the underlying screening modes rather than the three: "Easy mode hides these Pro settings. They're kept and restored if you switch back to Pro:" — and it lists them: the extra qualifying screeners beyond the first, any rejecting screeners, custom hold and reinvest-delay timings, and the universe filters on the screener it keeps. - Saving applies the active mode: in **Basket** the instruments you named are what the strategy keeps, and in **Screen** the screener definition is — a Screen save clears named instruments, because in Screen the rule is the selection. - The strategy needs at least one instrument or one attached screener before it can be saved and run, whichever mode it is in. ## What does it look like in practice? Take the same ten US large caps and build the same idea three ways. - **Basket** — you add all ten by name. The strategy's universe is exactly those ten, every rebalance, whatever the market does. - **Screen** — you name nothing and instead write one screener whose filters describe the ten. The strategy holds whatever matches at each rebalance: nine of them one quarter, thirteen names the next, because membership is recomputed rather than fixed. - **Compose** — you put the ten in the basket and attach one screener to **Qualify**. The candidate set never grows beyond your ten, but only the ones that qualify at that rebalance are held — six of ten in a quiet quarter, all ten in a strong one. Same idea, three different answers to "what may this hold?": a fixed list, an open rule, and a rule applied inside a fixed list. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/getting-started/backtest # Backtest A backtest is a historical simulation that replays a strategy's rules over past market data to show what it would have done. It applies the strategy's own allocation, rebalancing, and exit rules step by step across history and produces an equity curve plus performance metrics. In Fincanva, "backtest" means this historical simulation for every strategy type — there is no separate "backtest" kind of strategy. **Also seen as:** Run, Re-run ## What does a backtest measure? A backtest measures what a strategy's own rules would have produced over historical market data, reported as an [equity curve](/docs/analysis/equity-curve) plus the metrics that summarise it — [CAGR](/docs/analysis/cagr), [Max drawdown](/docs/analysis/max-drawdown), [Sharpe ratio](/docs/analysis/sharpe-ratio) and the rest of the metrics view. It measures the whole path, not only the end point: two strategies can finish at the same value having taken very different routes there, and the curve is what shows the difference. What it does not measure is anything outside the rules you saved — it makes no judgement about whether a strategy is suitable for you, and it says nothing about periods the chosen instruments have no data for. See [How backtesting works](/docs/backtesting/how-backtesting-works) for the step-by-step mechanics. ## How does Fincanva handle it? - A backtest runs from the earliest year your chosen instruments and plan allow, through the latest available market close; its end date follows the newest data, not today's calendar date. - Results are cached and refresh daily as new market data arrives, so the same strategy's numbers can shift from one day to the next with no change to its settings. - Identical strategies share one computed result, so a backtest may already be running because someone else requested the same configuration. - Saving and running is the reliable way to (re)compute today — it applies your latest settings and starts a fresh run. ## What does it look like in practice? A two-asset strategy holds 60% in a stock ETP and 40% in a bond ETP, rebalancing back to 60/40 twice a year. The backtest starts both sleeves from the same capital and replays every trading day; at each rebalance date it trims whichever sleeve has grown past its target and tops the other back up to weight. After two rebalances, the equity curve reflects both the market's moves and the two corrections back to 60/40, and the metrics summarise that whole path. See [how a backtest works](/docs/backtesting/how-backtesting-works) for the step-by-step mechanics. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/getting-started/benchmark # Benchmark A benchmark is a reference series a strategy is compared against — and it is itself a full simulation, not just a line drawn on a chart. You pick one benchmark per strategy, either from a set of market-benchmark presets or — on the plans that include it — from any of your own live portfolios, and Fincanva runs it as its own backtest so the comparison uses the same starting capital and the same period. Comparing a strategy to its benchmark shows whether its returns and its risk came from the wider market or from the strategy's own choices. **Also seen as:** Bench, vs bmk ## How does Fincanva handle it? - A benchmark is computed as its own simulation with the same status states as any backtest — Computing while it runs, Ready when it finishes, Failed if it cannot complete. - Changing the benchmark starts a new benchmark simulation; the comparison waits until that benchmark reaches Ready. - The benchmark uses the same starting capital and date range as the strategy it is measured against, so any difference reflects the holdings rather than a different setup. - **Which portfolios you may choose from is set by your plan: the market benchmarks are open to every plan, and your own live portfolios become benchmarks too from Advanced upwards.** A plan that does not include them still picks any market benchmark, and a strategy that was already pointed at one of your own portfolios keeps that benchmark and keeps running — what changes is that you cannot point one at a portfolio of yours again, whether by picking it or by duplicating a strategy that already uses it. Picking a benchmark, saving your simulation settings, duplicating a strategy and detaching a component into a strategy of its own are each checked against your plan. See [what each plan includes](/docs/account-security/what-each-plan-includes). ## What does it look like in practice? You compare a strategy against SPY, an ETP that tracks the S&P 500. Both start from the same capital on the same date, and Fincanva runs SPY as its own backtest, drawing the two equity curves together. Where your strategy's line sits above SPY it is ahead; where it dips below, it is behind. If your strategy ends higher but with deeper falls along the way, the side-by-side makes plain that the extra return came with more risk. What each comparison number means is covered in [the metrics guide](/docs/analysis/what-every-number-in-performance-metrics-means). *Beating a benchmark is not a reason to expect the same ahead.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/getting-started/combined # Combined A Combined is a strategy built from other strategies: it holds two or more of your strategies and splits capital across them instead of holding instruments directly. Each member keeps its own instruments, allocation, and rules, and the Combined adds one layer above them — the [Combined level](/docs/getting-started/combined-level) — that decides how much capital each member receives. It is what you build when one idea is not the whole book. **Also seen as:** Combined strategy, multi-strategy portfolio Earlier versions of Fincanva called a Combined a *portfolio*. That word now means something else entirely — a strategy you follow live, listed on the [Portfolios](/docs/getting-started/portfolio) page. ## Why does a Combined need at least two strategies? A Combined needs at least two member strategies because its whole job is to split capital between strategies, which one member cannot do — with only one it is an [Incomplete Combined](/docs/backtesting/incomplete-combined) and cannot run. ## What do you need before you can create a Combined? You need one strategy of your own before the **Create new** dialog will make you a Combined, and it checks before the Combined exists. One is enough: the **Combined strategy** tile creates the Combined and opens it, and you choose the strategies inside it. While you own none, the tile creates nothing — it opens a screen inside the Combined flow that reads "A Combined blends your own strategies — you have none yet. Create one to start." and offers a **Create a strategy first** button, which takes you on to the strategy-type tiles; a **Back** control on that step returns you to the screen you came from. The **+** in the strategy explorer's Combined section answers exactly the same way. The threshold is one rather than two because a Combined is allowed to hold a member you have not filled in yet. A single strategy has always been able to reach a full Combined through its own **Combine** button, which starts from that strategy and lets you leave the second member empty for now; at two, the tile refused the same person that button served — two doors, two answers. At zero the refusal stays, because a Combined with none of your strategies in it has nothing to blend. **This is not the number a Combined needs to run.** Running still takes two member strategies — see [Why does a Combined need at least two strategies?](#why-does-a-combined-need-at-least-two-strategies). Owning one strategy lets you *start* a Combined; it does not make that Combined backtestable. What counts is your own strategies that are not themselves Combineds. A Combined cannot be a member of another Combined, so one never counts. ## How is a Combined different from a strategy? A Combined holds strategies; a plain [strategy](/docs/getting-started/strategy) holds instruments. Both are strategies in the app's vocabulary, which is why they share one editor, one [backtest](/docs/getting-started/backtest), and one [run status](/docs/backtesting/run-status) model. Where both levels appear together the whole is always called the Combined, and destructive actions say which level they mean: "Remove this strategy from the Combined" removes one member, while "Delete Combined" deletes the whole thing. ## How does Fincanva handle it? - **Combined strategies start at the Advanced plan.** On Free and Starter the Combined tile is still shown and still clickable — pressing it answers with a plan wall naming the plan level you need, rather than creating anything; a Combined holds up to 5 strategies in use on Advanced, 10 on Ultimate and 20 on Professional — a strategy switched off inside it does not count, and no Combined holds more than 20 in total. Creating, copying or duplicating a Combined that would hold more strategies in use than your plan allows is refused with a message naming the plan that allows it — your own strategy included. An Advanced-or-above account can still be refused later, on the count, the same way any other creation is — see [plan compliance](/docs/backtesting/plan-compliance). See [what each plan includes](/docs/account-security/what-each-plan-includes). - Two or more members are required to run. A one-member Combined is a valid saved object, just not a runnable one. - A strategy joins as a snapshot copy taken when it is added, so later edits to the standalone original leave the copy inside untouched — see [strategy in a Combined](/docs/getting-started/strategy-in-a-combined). - The Combined carries its own rebalance, allocation, and risk settings at the [Combined level](/docs/getting-started/combined-level), separate from every member's own. - Combineds are listed under **Strategies** in the **Combined** section; you create one from the "Build a combined strategy" screen with **Combine**. - A Combined is backtested and can be followed live exactly like any other strategy. ## What does it look like in practice? You have two strategies: a momentum strategy on US large caps and a defensive strategy on bond ETPs. You combine them into one Combined with 50,000 of starting capital and **Equal Weights** at the Combined level, so each member is handed 25,000. Inside the momentum strategy, its own allocation divides that 25,000 across the stocks it selected; inside the defensive strategy, its own allocation divides the other 25,000 across its ETPs. One backtest covers the whole thing, and the Combined's result is the two members' paths held side by side in one book. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/getting-started/combined-level # Combined level The Combined level is the tier of settings that belongs to a [Combined](/docs/getting-started/combined) itself rather than to any of the strategies inside it — the layer that decides how capital is split across member strategies, how often that split is reset, and how the whole Combined de-risks. The app names its controls after it: **Combined rebalance**, **Combined allocation**, and **Combined risk**, grouped under "Combined — splits capital across strategies". Every member strategy keeps its own separate settings one level below. **Also seen as:** Combined-level allocation, Combined-level risk, Combined-level rebalance ## What settings live at the Combined level? Four groups live at the Combined level, and only these four: **Strategies** (which strategies are members, and their weights), **Combined rebalance** (how often the capital split is reset — see [rebalance](/docs/backtesting/rebalance)), **Combined allocation** ("How capital is split across strategies"), and **Combined risk** ("De-risk the whole Combined when markets turn"). Everything else — the instruments, the per-instrument weighting, the position exits — belongs to each member [strategy](/docs/getting-started/strategy), not to the Combined. ## How do the Combined level and the strategy level differ? They are two independent layers, applied one after the other: the Combined level splits capital *across* member strategies, and each member's own allocation then weights instruments *inside* its share. Fincanva applies both and never collapses them into one. So changing a member's own allocation does not change how much capital that member receives, and changing the Combined allocation does not change what any member holds. ## How does Fincanva handle it? - Combined allocation offers the methods the [allocation method](/docs/strategies/allocation-and-allocation-method) table marks for a Combined — among them [Equal Weights](/docs/strategies/equal-weights), Fixed Allocation, [Ranking-Based](/docs/strategies/ranking-based), Inverse Volatility, Risk Parity, [MPT (Markowitz)](/docs/strategies/modern-portfolio-theory) and the risk-focused methods such as [Minimum CVaR](/docs/strategies/minimum-cvar). Methods that exist only inside a single strategy, such as Market Cap or [Hierarchical Risk Parity](/docs/strategies/hierarchical-risk-parity), are not offered at the Combined level. - With [**Fixed Allocation**](/docs/strategies/fixed-weights) you set a weight per member under "Strategy weights"; the raw weights need not add up to 100, because they are normalized. - [**Invested portion**](/docs/backtesting/invested-portion) sets the share of capital the Combined deploys; whatever is not deployed stays as cash. - **Combined risk** switches the whole Combined to its [Risk-Off](/docs/strategies/risk-on-and-risk-off) allocation when its conditions are met — it does not pause or stop the Combined. See [risk conditions](/docs/strategies/risk-conditions). - The Combined level has no instruments and no position exits of its own; those exist only inside member strategies. ## What does it look like in practice? A Combined holds three member strategies and starts from 30,000. Its Combined allocation is **Equal Weights**, so the Combined level hands each member an equal third — 10,000 each. What happens to each 10,000 is decided one level down: the first member weights its five stocks equally at 2,000 apiece, the second uses [Inverse Volatility](/docs/strategies/inverse-volatility) across its holdings, and the third holds a single ETP for its whole 10,000. Switch the Combined allocation to [**Risk Parity**](/docs/strategies/risk-parity) and the three shares stop being equal, but each member's internal weighting is untouched — the two levels moved independently. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/getting-started/duplicate-and-copy-to-mine # Duplicate and Copy to Mine Duplicate and Copy to Mine are the two — and only two — ways to make a copy in Fincanva. **Duplicate** copies an item you already own; **Copy to Mine** copies a Public item into your own library so you can edit it. Both produce a fully independent new item that keeps the original's settings and none of its results, and neither ever changes the original. **Also seen as:** clone Earlier releases labelled Duplicate **Create a copy** or **Save as copy**. Both labels are retired; the app says Duplicate everywhere. ## What does a copy keep, and what does it drop? A copy keeps the configuration and drops the history — so it is the same idea with a clean slate: | Kept | Dropped | |---|---| | Every setting (allocation, risk, exits, rebalance cadence) | The run history and all backtest results | | The [strategy type](/docs/getting-started/strategy-type) | The Live state — a copy is never followed | | The benchmark and the simulation start year | Its folder placement — the copy lands at the top level of Mine | | The description | — | | For a screener: its filter rows and its universe | — | Because the results are dropped, a fresh copy has never been run: its [run status](/docs/backtesting/run-status) reads **To run** until you back-test it. Nothing you then do to the copy — editing, running, deleting — reaches the original. Which of the two you get depends on who owns the item, not on what you want to do with it. ## What does Duplicate do? Duplicate makes an independent copy of an item **you already own** — a variant of your own strategy, a second screener that starts from the first. It appears as **Duplicate** in the item's title menu, its row menu, and its page header, and it is the only copy action offered on something in your own library. Duplicate is not the same as **Save as new screener**, the button in a [Fin](/docs/getting-started/fin) suggestion review — that saves a suggested set of filters as a separate screener instead of overwriting yours. ## What does Copy to Mine do? Copy to Mine copies an item from the [Public](/docs/getting-started/mine-public) tab into your own library, and it is the **only** way to get an editable version of a Public item. The Public original is never touched — you are working on your own copy from the moment it lands. It refuses to run on anything else: use it on an item you already own and the app answers `Copy to Mine is only available for Public items.` That refusal is the clean statement of the split — Public items get Copy to Mine, your own items get Duplicate. ## Why does Fincanva sometimes refuse to copy a strategy? A copy is refused when the source holds **zero** components — not one, zero. Fincanva never lets you build or save a strategy at zero components, so the only way to reach this state is a handful of older documents that predate that guarantee; you cannot create one yourself. Trying Duplicate or Copy to Mine on one answers: `Nothing to copy: this strategy does not hold the minimum of 1 strategy, so the copy could not be saved or run.` **Duplicate has a second refusal, and it is about your plan rather than the source.** A copy is a new strategy, so it is checked like one: if the source is benchmarked against one of your own portfolios and your plan does not include that, Duplicate refuses rather than creating a strategy you would not be allowed to set up yourself. Detaching a component from a Combined into its own strategy is checked the same way, for the same reason. A public item is normally benchmarked against a market benchmark, which every plan includes. Whatever benchmark a copy arrives with, it keeps running; what you cannot do is point it at one of your own portfolios again unless your plan includes them. See [benchmark](/docs/getting-started/benchmark) for which portfolios each plan may use. **And a copy is counted like any other new strategy.** Each strategy you copy with Duplicate or Copy to Mine adds one to the strategies you hold, so a copy is refused once you are already at your plan's limit: one more would take you past what the plan allows. The Public original is untouched and nothing is created. Deleting a strategy you no longer need, or moving to a plan that allows more, is what makes room. See [plan limits](/docs/account-security/what-each-plan-includes) for what your plan allows. The zero-component refusal exists because a copy carries the source's components over unchanged: copying a zero-component source would produce a strategy that renders but can never be saved or run, with no way to fix it afterwards. A source with **one** component is not affected — an [Incomplete Combined](/docs/backtesting/incomplete-combined) copies exactly like any other strategy; only zero holds the copy back. ## Why is a screener copy refused when it holds too many filters? A screener copy is refused when the source holds more filter rows than the limit allows. **Duplicate** and **Copy to Mine** are both checked this way, and the app answers `One of the screeners you're copying holds more filters than your Free plan allows, so it can't be copied — nothing was created.`, naming the plan you are on. Nothing is created. **The limit is the same on every plan, and no upgrade raises it.** The sentence names the plan you are on, but changing plan will not let the copy through — there is no higher figure to buy. See [Screener](/docs/getting-started/screener) for the figure itself and for what happens to a screener you already hold that is over it. Nothing is trimmed to make it fit, and that is deliberate. A copy that quietly dropped the filters over the limit would screen a different set of instruments from the one you asked to copy, under the same name, with nothing telling you so. The source is never changed by the refusal. A screener you already hold that is over the limit keeps working and keeps its rows — see [plan limits](/docs/account-security/what-each-plan-includes) for what your plan allows and what happens to items you already hold. ## Where does the "Created from" line come from? The muted **`Created from {sources} — {date}`** line is provenance for a **Combined**: it appears when a Combined strategy was built out of existing strategies, and it names them and the date. A plain Duplicate or Copy to Mine does **not** stamp it — a copy carries no recorded link back to what it was copied from, and the only trace is the name the app suggests. ## How does Fincanva handle it? - The suggested name is the original's name with `(copy)` appended, and you can replace it before committing. - A copy uses the last **saved** version of the source, so unsaved edits are excluded — save before copying if you want them in. - On success the app confirms with `Copy created`. - A copy always starts with Live off, whichever way you made it, so it never joins your live book by accident (see [Mark Live](/docs/getting-started/mark-live)). - Any copy's name is auto-adjusted if it would collide with a strategy already in the folder it lands in: Fincanva appends ` (1)`, ` (2)` and so on. This applies to Duplicate as well as Copy to Mine, and to the name you type yourself in the prompt — two strategies in one folder can never share a name. ## What does it look like in practice? You own a strategy called "Momentum EU" and want to try a monthly rebalance without losing the quarterly version. You choose **Duplicate**; the prompt offers "Momentum EU (copy)" and you rename it to "Momentum EU monthly". The copy appears at the top level of Mine with every setting from the last saved "Momentum EU" — same instruments, same allocation, same benchmark — but with no results at all, so its status reads **To run**. You change the cadence to monthly, save, and back-test. You now have two independent strategies with comparable settings and separate result histories. "Momentum EU" never moved, was never re-run, and if it happened to be followed Live, the copy did not inherit that. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/getting-started/filter # Filter A filter is one screening rule inside a [screener](/docs/getting-started/screener) — a metric, a comparison mode, and the value or values it is tested against. Each filter is a single condition an instrument either passes or fails, and because filters combine with AND, an instrument has to pass every filter in the screener to become a [match](/docs/screeners/matches). You add filters from the **Add a filter** panel and edit each one in place. **Also seen as:** screening rule, screening criterion ## What is a filter made of? Three parts, plus an optional fourth. The **metric** is what the filter reads — Market Cap, P/E, a moving average. The **comparison mode** is the relation it applies: vs Value, Between, vs Lagged Self, Highest / Lowest, or [vs Aggregate](/docs/screeners/aggregate-comparisons) (see [comparison modes](/docs/screeners/comparison-modes)). The **value** is what the metric is tested against — one number, a range, a lag, or a rank, depending on the mode. Optionally the **Advanced** panel shifts or scales the reading with Lag, Period, and Multiplier (see [lag, period, and multiplier](/docs/screeners/lag-period-and-multiplier)). While you edit, a plain-language restatement appears under "You're saying", so you can read the rule back as a sentence before applying it. ## Where do filters come from? Filters come from a catalogue Fincanva maintains, grouped by category in the **Add a filter** panel. Today that catalogue holds 118 filters — 84 Fundamental, 20 Technical, and 14 Market & Sector — alongside the Universe filters that decide which instruments are eligible in the first place (see [universe](/docs/getting-started/universe)). Two categories are visible but not yet available: Macro is marked "Coming soon", and custom filters are "post-V1". Not every filter supports every comparison mode, and the editor offers only the relations the chosen filter supports. ## How does Fincanva handle it? - Filters are ANDed, never ORed, so adding one can only lower the match count or leave it unchanged; removing or loosening one can only raise it. - Each filter applies to the [asset types](/docs/getting-started/asset-type) it is defined for. Switching asset type hides the universe filters that no longer apply, and switching back restores them. - A filter's Advanced inputs carry the unit the filter counts in — Months Ago, Reports Ago, Quarters, Days, Bars, or Std Devs. You enter the number; the filter fixes the unit. - Deleting a filter changes only the screener you are editing; the filter stays in the catalogue for every other screener. ## What does it look like in practice? Take `P/E < 15`. The metric is P/E, the comparison mode is **vs Value**, the operator is `<`, and the value is 15 — read back under "You're saying" as "P/E is less than 15". An instrument passes when its latest P/E reading sits below 15. Switch the same filter to **Between** and the single value becomes a low–high pair, `P/E between 10 and 20`. Switch it to **Highest / Lowest** and the value becomes a rank rather than a threshold, keeping only the top or bottom N. The metric never moved — only the relation, and what that relation needs from you. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/getting-started/fin # Fin Fin is Fincanva's AI assistant, and Fin is its only name. Today Fin does one job: it proposes **screener filters** — either improving a [screener](/docs/getting-started/screener) you have already built, or building one from your current [universe](/docs/getting-started/universe) — and shows you the proposal side by side with your own before anything changes. Nothing Fin suggests is applied until you choose to apply it. ## What can Fin do today? Two actions, both on a screener's Backtest view: - **Improve filters** takes the screener you have and looks for a stronger version of it. It needs something to work from, so it stays disabled until the screener has at least one filter: "Add at least one filter first — there's nothing to improve yet." - **Suggest new filters** starts from your universe instead of your filters — the [asset type](/docs/getting-started/asset-type) you have active and the universe filters set on it — so it is available even on an empty screener. Fincanva also offers it from a never-run screener's empty state, as "let Fin suggest a stronger one". While Fin works, the app says what it is doing — "Fin is improving your screener…" or "Fin is building a screener…", with "Fin is testing thousands of filter combinations against market history to find a stronger setup." and a progress reading. You can cancel; your screener is untouched either way. ## What does Fin's suggestion review show? When Fin finishes, a review opens titled "Fin's suggestion is ready", with two columns — **Your screener** and **Fin's suggestion** — so you can compare them row by row. Each filter row in the suggestion is tagged **Kept**, **Added**, **Modified**, or **Removed** against your original, so you can see exactly what Fin changed rather than just the outcome. The review reports the suggestion's edge as an average, captioned "Avg annualized outperformance vs benchmark, across all six horizons", and carries its own disclaimer: "Backtested result — past performance doesn't guarantee future returns." From there you choose: **Use these filters** puts the suggestion into your editor as unsaved changes, **Save as new screener** keeps your original and saves the suggestion separately, and **Discard** leaves everything as it was. Fin can also come back with nothing. When it cannot beat what you built, the review reads "This is already a strong screener" and "Fin tested thousands of filter combinations against market history and couldn't improve on it." If the search itself fails, it reads "Fin couldn't finish" and "The search couldn't complete. Your screener is unchanged — try again." *A suggestion from Fin is a filter set that tested well on historical data, not a recommendation to invest.* ## Is there a Fin chat you can ask questions? Not today. The conversational Fin — a panel you open and ask questions in — is not available yet; where its surface would appear the app says "Fin is coming soon." Fin's only working capability right now is the screener suggestion described above. ## How does Fincanva handle it? - Fin never edits a screener on its own. Every suggestion goes through the review, and applying one arrives as **unsaved** changes you still have to save. - **Improve filters** requires at least one filter; **Suggest new filters** does not. - "Save as new screener" creates a separate screener, so accepting a suggestion never overwrites the one you built. - A failed or cancelled run leaves your screener exactly as it was. ## What does it look like in practice? You have a screener with four fundamental filters that matches about 80 instruments, and you want to know whether it can be sharpened. You select **Improve filters**. Fin runs, reporting "Fin is improving your screener…" with a progress reading, and comes back with "Fin's suggestion is ready". In the review, two of your filters are tagged **Kept**, one is **Modified** with a tighter threshold, one is **Removed**, and a new one is **Added** — five rows, so you can see the shape of the change and not just its score. You decide you want to keep your original as a reference, so you choose **Save as new screener**. You now have both screeners in your library and can back-test each one and compare the [matches](/docs/screeners/matches) yourself. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/getting-started/folder # Folder A folder is a named container in your **Mine** library that groups your own strategies or your own screeners, so a long library can be organised by theme, client or stage of work. Folders can hold subfolders, each strategy or screener sits in at most one folder, and an item in no folder lives at the top level of the library. Folders only organise: moving an item between folders never changes its settings or its results. **Also seen as:** subfolder, directory. ## What can a folder hold? A folder holds items of one kind, and its subfolders. Strategy folders and screener folders are separate trees, and strategy folders are shown separately for **Single** and **Combined** strategies — each library lists its own folders, so a Combined strategy is never filed in a folder of Single ones. Only your own items go in your folders. The folders under the **Public** tab are organised by Fincanva, and the app says so where you would create one: "Public folders are managed by Fincanva — copy items to Mine to organize." A **Copy to Mine** arrives at the top level of Mine, with no folder, so you file it yourself afterwards — see [Mine and Public](/docs/getting-started/mine-public). ## Can two folders have the same name? Not side by side. Two folders directly inside the same parent — or two folders at the top level — cannot share a name. For strategies, the top level counts as one place across both libraries: a top-level folder in **Single** and a top-level folder in **Combined** cannot have the same name either. Screener folders are checked only against other screener folders. A subfolder can reuse a name that exists somewhere else in the tree, so *Clients / Momentum* and *Research / Momentum* can both exist. Strategies follow the same rule inside a folder: two strategies in one folder cannot share a name, and a copy that would collide is renamed with a ` (1)` suffix — see [copies and duplicates](/docs/getting-started/duplicate-and-copy-to-mine). ## What happens when you delete a folder? Deleting a folder deletes **everything inside it**: its strategies or screeners and all of its subfolders, not only the folder. The confirmation says so before anything happens. For an empty folder it is a single question. For a folder that holds anything, it names how many items and subfolders will go with it and asks you to type `delete` to confirm, under the warning "This can't be undone." To keep an item, move it out of the folder before you delete the folder. ## How does Fincanva handle it? - Create a folder with **New folder** in the library, and a folder inside it with **New subfolder** on the folder's menu. The same menu holds **Rename** and **Delete** — on a screener folder the delete item reads **Delete folder**. - Move a strategy or screener with **Move to folder** on its menu, or by dragging it onto a folder; **(No folder)** returns it to the top level. A folder moves by dragging it onto another folder, and cannot be dropped into itself or into one of its own subfolders. - The **Strategies · Single** and **Strategies · Combined** pages can show each strategy's folder in a **Folder** column, with "—" for one at the top level. The column is hidden by default: switch it on from the **Columns** button in the table's toolbar, which lists every column with a checkbox. Their **Folder** filter lets you tick one or more folders, plus **No folder**, and shows only the strategies filed directly in them: a subfolder's strategies are not included when you tick its parent, and only folders that directly hold a strategy are offered — an empty folder, or one that holds only subfolders, is not in the list. - Home names the folder beside each strategy it lists — see [Home](/docs/getting-started/home-the-page-you-land-on-after-signing-in). - Search matches the names of strategies and screeners, not the names of folders, and finds an item wherever it is filed — see [search](/docs/getting-started/find-your-strategies-and-screeners-with-search). ## What does it look like in practice? You keep two families of strategies in the Single library and create two folders for them, *Income* and *Growth*. Inside *Growth* you add a subfolder, *Tests*, for drafts. A strategy you drag into *Tests* keeps every setting and result it had; only its folder changes, which the Strategies page shows as *Tests* once you switch its **Folder** column on. Months later you delete *Growth*. The confirmation tells you that the strategies in *Growth* and its one subfolder will be deleted with it, and waits for you to type `delete`. If one of those strategies is worth keeping, cancel, move it to *Income* or to **(No folder)** first, then delete *Growth*. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/getting-started/holdings # Holdings Holdings is the view that shows what a strategy would hold right now — the target positions its rules imply at a chosen [rebalance](/docs/backtesting/rebalance) date — rather than how it performed across history. It answers "what does this strategy hold today?", where the Analysis view answers "how did it do?". Holdings reads from a completed run, so a strategy has to have been run at least once before it can show anything. **Also seen as:** current state, target portfolio ## What does the Holdings view show? Holdings shows one rebalance date's target book, in five parts. Four KPIs summarise it — [**Target notional**](/docs/portfolio-holdings/target-notional), [**Cash**](/docs/portfolio-holdings/cash-and-capital-invested), **Positions**, and **Accuracy** (see [accuracy](/docs/portfolio-holdings/accuracy)). The **Order plan** lists what would be bought, sold, and adjusted to reach that book, grouped as Entering, Exiting, and Adjusted (see [order plan](/docs/portfolio-holdings/order-plan)). **Target allocation** shows the resulting weights, including any cash. **Rebalances** lets you move between past and upcoming rebalance dates. And the **Target positions & exits** sheet lists every position with its Qty, Target value, Deployed amount, and exits (see [target vs deployed](/docs/portfolio-holdings/target-vs-deployed)). ## How is Holdings different from the Analysis view? Holdings describes a single point in time; Analysis describes the whole path. Holdings also runs on its own fixed set of assumptions rather than the [simulation assumptions](/docs/backtesting/simulation-assumptions) toggles — see [Holdings forced assumptions](/docs/backtesting/holdings-forced-assumptions) for what that set is and why the two views can disagree on the same date. ## How does Fincanva handle it? - **Holdings on your OWN strategies is set by your plan: it opens from Starter upwards.** A Free plan still backtests its strategies and reads the Analysis surfaces its plan includes; what it does not open is this page's view of what one of your own strategies would buy today. Public strategies are unaffected — anyone can open the Holdings of a strategy from the public catalogue, on any plan and signed out. See [what each plan includes](/docs/account-security/what-each-plan-includes). - **The current-state output itself is a Free plan's to go without, not merely a page it cannot open.** From Starter upwards Fincanva computes this view's figures for a strategy; on Free they are never asked for, so there is nothing held back behind a lock. An out-of-plan Analysis tab works the same way — its figures are not computed either — and the two now look alike: each tab stays in place and opens, marked with the bars of the plan level that includes it, and where the figures would be the page shows a faded sample with the plan's button and one sentence on what the page shows. See [what each plan includes](/docs/account-security/what-each-plan-includes). - Holdings needs a completed run. With none it shows "No results yet" and "Backtest this strategy to see its target portfolio." - You choose which rebalance date to view; when it is not the most recent one the view warns "You're viewing `{date}` — not the latest rebalance". - **Refresh** recomputes the current state, showing "Refreshing…" while it works. It changes nothing about the strategy itself. - You can type your own figure into **Capital**, and the target values rescale to it. The saved strategy's own starting capital is unchanged. - A [Combined](/docs/getting-started/combined) with only one member strategy shows example results rather than its own — see [Incomplete Combined](/docs/backtesting/incomplete-combined). ## What does it look like in practice? A monthly-rebalanced strategy last rebalanced on 1 July and rebalances next on 1 August. Open Holdings and it shows the 1 July target book against 50,000 of capital: 12 positions, a Target notional of 48,000, 4% cash, and 96% Accuracy — the shortfall coming from whole-share rounding across the positions. The Order plan for that date reads 3 Entering, 2 Exiting, and 7 Adjusted, with an estimated turnover figure beside it. Switch the date to the previous rebalance and every panel re-reads that older book instead, with a warning that you are not looking at the latest one. *The Holdings view describes a paper target portfolio a strategy's rules imply, never real orders, and no position or figure on it is a recommendation to buy, sell, or hold.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/getting-started/instrument # Instrument An instrument is a single tradable or reference security, identified by a ticker — its short symbol — such as a stock, an ETP (an exchange-traded product like an ETF), or a crypto asset. It is the smallest thing a strategy can hold: strategies screen, rank, buy, and sell instruments. Each instrument carries its own price history, and that history is what a backtest replays. **Also seen as:** ticker, symbol, security ## How does Fincanva handle it? - Instruments are grouped by [asset type](/docs/getting-started/asset-type); today Fincanva offers three — Stocks, ETPs, and Crypto. - Each instrument is identified by its ticker symbol and carries its own price history and first available date, which set how far back a backtest that uses it can run. - Delisted instruments are kept and stay searchable, so a strategy can include securities that no longer trade — this is what keeps a backtest from seeing only today's survivors. ## What does it look like in practice? AAPL, SPY, and BTC are three instruments of different types. AAPL is a single company's stock; SPY is an ETP that itself tracks the S&P 500 index; BTC is a crypto asset. A strategy can hold any mix of them, and each brings its own price history — so a [backtest](/docs/getting-started/backtest) that includes BTC can only reach back as far as BTC's own history allows, even if AAPL's stretches decades further. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/getting-started/instrument-logo # Instrument logo Wherever Fincanva shows an [instrument](/docs/getting-started/instrument) with a small picture — the screener's results table, a strategy's Holdings and Positions, the instrument pickers, and the public screener embed — that picture is the instrument's own logo when Fincanva holds one, and a flag for the instrument's recorded origin when it doesn't. **Also seen as:** instrument icon, avatar ## What shows when an instrument has no logo? A flag for the instrument's recorded origin, not for where it happens to be listed: the US flag when the recorded origin is US, a globe when no origin is recorded (or the reference data carries its `GLO` marker for that), and the EU flag for any other recorded origin — today every other origin in the data is European. A US-listed instrument can still show the EU flag if its recorded origin is European. This still resolves for every instrument Fincanva's reference data holds; one that has since dropped out of the reference data entirely shows a letter avatar instead, because there is no record left to read an origin from. ## Where does the picture come from? From Fincanva's own storage. Both an instrument's own logo and the three flag images are served by the platform itself, so no third party is contacted from the reader's browser to show an instrument's picture. ## How does Fincanva handle it? - Not every instrument has its own logo. Measured 2026-09-19: 5,854 of 38,207 instruments in the reference data do — about 15%. - Logos are added over time: an instrument showing a flag today can show its own logo later, with nothing else about it changing. - The same rule decides the picture everywhere it appears — the screener's results table, a strategy's Holdings and Positions, the instrument pickers, and the public screener embed all show the same picture for the same instrument. ## What does it look like in practice? Two instruments sit side by side in a screener's Matches table. One is a widely covered US stock, and its Symbol cell shows the company's own logo. The other is a smaller instrument of European origin Fincanva has no logo for, and its Symbol cell shows the EU flag instead. Both cells identify their instrument; only one carries its own picture. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/getting-started/live-book # Live book The live book is the Portfolios page that lists every strategy you follow live, topped by a summary strip that reads the whole book at a glance. Each row is one live-followed [portfolio](/docs/getting-started/portfolio); the strip above them condenses all of those rows into a few numbers — the median return, the best and weakest performers, and how many of the portfolios are positive — for the return window you pick. It is the one screen where you judge your live-followed strategies together rather than one at a time. **Also seen as:** Portfolios ## What the summary strip shows The summary strip has three panels that summarise every live portfolio at once, all for the same return window. **Whole book** carries the headline numbers: the **Median return** (the middle portfolio's return, so half your book did better and half did worse), the **Best** and **Weakest** performers, and a positive count reading `{n} of {total} positive portfolios`. **Book health** reports how many portfolios are up to date. You switch the window between **MTD**, **YTD**, **1Y**, and **1M**, and every panel recomputes against that window. The median is used, not the average, because one runaway winner or loser cannot drag it — it always describes a typical portfolio in the book rather than an outlier. ## How does Fincanva handle it? - The strip summarises only strategies you have marked Live; a strategy you have merely backtested but not followed does not appear in the book. - Each panel reads the return window you select (MTD, YTD, 1Y, or 1M) — the number is a summary across portfolios, never a single portfolio's figure. - Before any returns exist the strip shows an empty state (`No returns computed yet`) rather than a zero. ## What does it look like in practice? You follow five strategies live, and for the 1Y window their returns are −4%, +2%, +6%, +9%, and +21%. The **Median return** panel shows +6% — the middle of the five, with two portfolios above and two below — so a single +21% outlier does not flatter the headline the way an average would. **Best** reads +21% and **Weakest** reads −4%, and the positive count reads `4 of 5 positive portfolios`. Switch the window to 1M and all three panels recompute from each portfolio's one-month return instead. *The median, best, and weakest figures describe what the strategies you follow have already returned, not what they will return, and no ranking in the strip is a recommendation to add to, trim, or drop a portfolio.* Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/getting-started/mark-live # Mark Live Mark Live is the action that starts following a strategy going forward instead of only over history. **Live means monitoring only: nothing is traded.** Fincanva keeps tracking what the strategy's rules would hold and how that paper book would perform, and it never places an order, never connects to a broker, and never moves real money. A strategy you have marked Live becomes a [portfolio](/docs/getting-started/portfolio) on the Portfolios page and joins your [live book](/docs/getting-started/live-book); **Unfollow** reverses it at any time. **Also seen as:** Go live ## Does marking a strategy Live trade anything? No. Marking a strategy Live places no orders and moves no money. Fincanva has no broker connection at all — there is nothing for an order to be sent to. Going Live starts paper monitoring: the app follows the positions the strategy's rules imply and shows how that paper book would have performed, exactly as a backtest does, but continuing forward from today instead of stopping at the end of history. The one place this can read like real trading is the [order plan](/docs/portfolio-holdings/order-plan), which lists what the strategy would buy, sell, and resize at its next [rebalance](/docs/backtesting/rebalance). That list is a plan on paper — Fincanva does not act on it, and you would have to place any of those trades yourself, with your own broker, entirely at your own discretion. *Following a strategy Live is not a prediction and not a recommendation.* ## What changes when a strategy is Live? Four things change, and none of them touch money: - **It appears in Portfolios.** The confirm dialog states it plainly: "It'll show in Portfolios and count toward your dashboard." - **Its results are kept current automatically.** Live strategies are refreshed for you as new market data arrives; a strategy that is not Live only recomputes when you press Run or Re-run. See [Run status](/docs/backtesting/run-status) for the states you will see. - **It is starred automatically, and the star locks.** Going Live adds the strategy to your favourites and keeps it there while it stays Live — trying to unstar it shows "Turn the strategy off first". The star locks yellow in the dashboard table and in the strategy's header; in the sidebar library the row shows a green **Live** badge in the star's place. [Starring strategies and screeners](/docs/strategies/starring-strategies-and-screeners) covers the star, the lock, and the favourites cap. - **It counts toward your dashboard**, where its own numbers feed the whole-book summary. Editing a Live strategy does not silently re-run it: an edited strategy waits for you to run it explicitly, so a change you make never triggers a backtest by itself. ## Who chooses which strategies keep being followed? You do. When your plan stops covering the strategies you follow Live, Fincanva asks you which ones keep being followed before it stops any of them — it does not decide that for you any more. The question arrives as a dialog on the Portfolios page and when you open a strategy you follow Live, and it is blocking: it has no close button, Escape and a click outside do nothing, and the only way past it is an answer. The dialog names the numbers and lists every strategy you follow, each with how long you have been following it where Fincanva has that date. On Starter, following three, its title reads "Choose the strategy to keep live" and under it "You follow 3 live strategies, Starter covers 1. Choose which one to keep." Where the plan covers one, the rows are radio buttons; above one they are checkboxes with a counter reading "2 of 5 chosen". **Confirm** commits, and it stays disabled until you have chosen exactly the number the plan covers — not at most that number, exactly it. Once you reach it the remaining rows lock and dim: to pick a different one, untick one you picked. **Where Confirm leaves you depends on where you answered.** On the Portfolios page you stay there. Inside a strategy, you stay on it if it is one you kept; if it is not, Fincanva takes you to the Portfolios page, because the strategy you were looking at has just stopped being followed. The same holds on a cancelled subscription, where nothing is kept. **Fincanva's own order arrives pre-selected, and the dialog states in words what applies if you choose nothing:** "If you choose nothing we keep Momentum EU, the last one you used." Most recently used is the order for the Live ceiling, and only for it: which strategies your library keeps active is a separate question, answered on [plan compliance](/docs/backtesting/plan-compliance). Under it the dialog says what the choice costs: the ones you leave out stop being followed — no live updates and no live signals — and stay in your library, ready to go live again when your plan covers them. **You are asked once, and the question cannot be reopened.** It is owed at the moment your plan stops covering your live book, and your answer puts the account back inside what the plan covers; from then on Fincanva refuses any attempt to answer it again, so there is no screen, no menu entry and no link that reopens it. You meet it a second time only if a later plan change stops covering your live book again, and that is a fresh question about the strategies you follow then. **If the question moves under you while the dialog is open, your answer is refused rather than applied — and Fincanva says which case it was.** Answer in a second tab after the first has already been saved and you are told "Your choice was already saved, in another tab. This is where you stand now."; answer a question your plan has changed in the meantime and you are told "Your plan changed while this was open, so the question changed too. Here it is as it stands now." Neither is a failure and neither loses anything of yours — the dialog re-reads the server, and either shows you the question as it now stands or closes because your account is covered. **A cancelled subscription is the same moment in a different shape.** Your plan then covers no Live strategies at all, so there is nothing to choose between and the dialog states what is happening instead of offering a choice. It reads "Your subscription has ended", then "The 3 strategies you were following stop." It lists them, each marked **STOPPED**, and closes with "They all stay in your library, with their history: they go live again as soon as you take a plan. There is nothing to redo." There are no controls and no counter — only **See the plans**, and **Got it** to acknowledge. ## What happens when your plan stops covering a Live strategy? Following stops and the strategy is set aside — not deleted, not edited, not hidden. It keeps its place in your library and its settings stay editable; what it loses is the following, and the results that came with it. Two different shortages stop a following, and only one of them is yours to decide. When your plan covers fewer Live strategies than you follow, you choose which ones keep being followed, in a dialog Fincanva puts in front of you at the Portfolios page or when you open a Live strategy. When a strategy instead falls outside what your plan keeps active in your library, it is set aside and its following stops as a consequence: that set is decided for you, once, at the moment the plan stops covering your library, and the strategies you follow Live rank ahead of every other, so one of them is set aside that way only when you follow more than your plan keeps active. **The two can meet on one screen.** A strategy that is already set aside is still listed when the Live question is asked, marked **SET ASIDE** and with no control beside it: its following stops whatever you answer, so it is not one of the strategies you are choosing between. The dialog says so under the list — "One of these is set aside, so it stops being followed whatever you choose." — and the number you are asked to keep is spent on the strategies that can actually keep being followed. If setting them aside already leaves your live book inside what the plan covers, no question is asked at all. **Fincanva does not mark the interruption anywhere.** There is no line on the row saying when following stopped, no dated record of the stretch it was off, and no separate control for starting again. A set-aside strategy's row carries the bars of the plan level that would bring it back before its name and shows its Live switch off and dimmed, and clicking that switch opens **Your plan is full** instead of toggling — an account cannot follow more strategies than its plan keeps active. Starting again therefore means bringing the strategy back inside the plan, and there are only two routes: a plan that covers what you hold, or — if you deleted an active strategy and a seat is genuinely vacant — **Activate this one** on that strategy's own panel. There is no free way to re-choose which strategies your library keeps active: that verdict is settled once, and it is discarded only when your plan covers your whole library again. The Live ceiling's one-time question is a different question, and answering it does not move the library verdict. [Plan compliance](/docs/backtesting/plan-compliance) covers the two reasons a strategy ends up outside a plan and how each clears. **A strategy followed again after months is not the same as one followed throughout, and nothing in the app will tell you so.** Months of [rebalances](/docs/backtesting/rebalance) never happened: its current positions are what its rules imply today, not what someone following it throughout would be holding, and the [order plan](/docs/portfolio-holdings/order-plan) it now shows is the move from those positions rather than from theirs. Reading it as an unbroken Live track would overstate what it is — and because the interruption is not recorded, keeping track of it is yours. ## How does Fincanva handle it? - **How many strategies you may follow Live is set by your plan:** none at all on Free, 1 on Starter, 5 on Advanced, and no limit on Ultimate and Professional. See [what each plan includes](/docs/account-security/what-each-plan-includes). - Only your own strategies can be marked Live — a Public strategy has no Live control, because it is not yours to follow. - Both directions ask for confirmation. Going Live asks "Mark this strategy as Live?" and commits with **Mark as Live**; turning it off asks "Stop following this strategy?" and commits with **Stop following**. - There are two ways in: the **Live / Off** switch on the strategy itself (labelled **Go live** while off), and **Mark Live** in the strategy's row menu, which reads **Unfollow** once the strategy is live. - A copy is never followed automatically: **Duplicate** and **Copy to Mine** both produce a strategy whose Live switch starts **Off**. - Unfollowing changes nothing about the strategy itself — it leaves Portfolios, stops counting toward your dashboard, and can be marked Live again later. ## What does it look like in practice? You have backtested a strategy and want to watch how it behaves from here. You open it and flip the **Off** switch; a dialog asks "Mark this strategy as Live?" and you confirm with **Mark as Live**. The switch turns green and reads **Live**, the strategy appears on the Portfolios page, its star turns gold and locks, and Fincanva starts keeping its numbers current as new market days arrive. No broker was connected and no trade was sent. Two months later you decide to stop: you flip the switch back, confirm "Stop following this strategy?" with **Stop following**, and the strategy leaves Portfolios. Its star unlocks, its saved settings and its whole backtest history are untouched, and you can mark it Live again whenever you want. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/getting-started/mine-public # Mine / Public Mine and Public are the two halves of your library, shown as two tabs above every strategy and screener list. **Mine** holds the items you own — the only ones you can edit, save, delete, or mark Live. **Public** holds a read-only catalogue that Fincanva curates and that every user sees the same way. The split is about ownership, not visibility: a Public item is not something you shared, it is something Fincanva published. ## Can you edit a Public strategy or screener? No — and this is the rule that surprises people most: **editing a Public item forces a copy first.** You can open a Public strategy or screener and read every setting, but you cannot save a change to it. The app blocks the save and tells you the way round: `Public strategies can't be saved. Use "Copy to Mine" to make an editable version.` On the screener side it reads `Public screener — use Copy to Mine to create your own version.` Once you have used **Copy to Mine**, you own the copy outright and can change anything in it. The Public original is untouched and stays in the catalogue for everyone — see [Duplicate and Copy to Mine](/docs/getting-started/duplicate-and-copy-to-mine) for what the copy keeps. ## What is the difference between Mine and Public? | | Mine | Public | |---|---|---| | Who owns it | you | Fincanva (no owner) | | Can you edit and save it | yes | no — Copy to Mine first | | Can you create items or folders in it | yes | no — `Create (disabled on Public tab)` | | Can you delete it | yes | no | | Can you mark it Live | yes | no | | Can you favourite it | yes | yes — a plain bookmark that never locks | ## How does Fincanva handle it? - **Your plan caps how many saved strategies Mine may hold on Free alone:** Free holds two, and Starter, Advanced, Ultimate and Professional do not cap the library. The 999 you see beside those plans is a safety maximum that stops runaway creation, not an allowance a plan buys you. See [what each plan includes](/docs/account-security/what-each-plan-includes). - **Saved screeners are not limited by your plan.** Every plan carries the same 999 safety maximum, so the two counts no longer move together: saved strategies are capped by your plan on Free, screeners are not capped by any plan. They are still counted separately, and Public is a catalogue you do not own, so nothing in it counts against either number. - The Public tree's folders are organised by Fincanva, not by you: `Public folders are managed by Fincanva — copy items to Mine to organize.` - Everything you create lands in Mine — a new strategy or screener, a Duplicate, a **Copy to Mine**, and a screener saved from a [Fin](/docs/getting-started/fin) suggestion. - A Copy to Mine arrives at the top level of Mine with no folder, so you file it wherever you want afterwards. - Copy to Mine on something that is not Public is refused with `Copy to Mine is only available for Public items.` — an item you already own is Duplicated instead. - Starring works on both tabs. A Public item's star is only a bookmark; the star lock that comes with going Live applies only to your own strategies (see [Starring strategies and screeners](/docs/strategies/starring-strategies-and-screeners)). ## What does it look like in practice? You find a Public strategy in the catalogue and want it to rebalance monthly instead of quarterly. You open it, change the rebalance cadence, and try to save — the save is blocked with `Public strategies can't be saved. Use "Copy to Mine" to make an editable version.` So you choose **Copy to Mine**. A copy appears at the top level of the Mine tab, owned by you and no different from anything else you built. You set it to monthly, save, and back-test it. The Public original still rebalances quarterly and still sits in the catalogue exactly as it was, for you and for everyone else. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/getting-started/portfolio # Portfolio A portfolio, on the Portfolios page, is a single strategy you have chosen to follow live — one of the strategies that make up your [live book](/docs/getting-started/live-book). [Marking a strategy Live](/docs/getting-started/mark-live) adds it to Portfolios and starts paper monitoring: Fincanva keeps following what the strategy would hold and how it would perform, but nothing is ever traded and no orders are placed. In Fincanva "portfolio" always means a live-followed strategy; a strategy built out of other strategies is a [Combined](/docs/getting-started/combined), which is what "portfolio" used to mean in earlier versions. **Also seen as:** paper portfolio ## How does Fincanva handle it? - Marking a strategy Live uses the "Go live" control; it then shows in Portfolios and counts toward your dashboard. - Going live starts paper monitoring only — Fincanva tracks the strategy's holdings and performance and never places an order or moves real money. - Choosing "Stop following" removes the strategy from Portfolios; the strategy itself is unchanged and can be followed again later. ## What does it look like in practice? You have a screener-based strategy you have [backtested](/docs/getting-started/backtest) and like. You open it and choose Go live, and it moves to the Portfolios page to be tracked day to day. No broker is connected and no trade is ever sent — Fincanva simply follows the positions the strategy's rules imply and shows how that paper book would perform. Later you choose Stop following, and the strategy leaves Portfolios with no effect on the saved strategy itself. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/getting-started/screener # Screener A screener is a saved set of filters over a universe of instruments that returns every instrument passing all of them. You build one by choosing a [universe](/docs/getting-started/universe) — "All" is the whole market — and adding [filters](/docs/getting-started/filter) that narrow it; whatever survives is the screener's [matches](/docs/screeners/matches). A screener picks instruments by rule instead of by hand, and the same saved screener can be reused, backtested, and attached to a strategy. **Also seen as:** screen, stock screener ## What is a screener made of? A screener is a universe plus a list of filters, and nothing else. The universe decides which instruments are eligible at all — by [asset type](/docs/getting-started/asset-type), country, exchange, index, sector, and asset subtype — and each filter is one testable condition on a metric. The **Matches** tab carries the live count of instruments passing every filter at once, and it updates as you add, edit, or remove filters. ## What can you do with a screener? Three things: read its matches, backtest it, or attach it to a strategy. [Backtesting a screener](/docs/screeners/screener-backtest) measures how its picks would have performed over six holding horizons — 1, 2, 3, 6, 12, and 24 months — against a benchmark built from the same universe with no filters applied, so the comparison isolates what the filters contributed rather than what the market did. That same Backtest view is where [Fin](/docs/getting-started/fin) offers to improve your filters or suggest new ones. [Attaching it to a strategy](/docs/getting-started/screener-attach) makes the [strategy](/docs/getting-started/strategy) buy what the screener selects; see [Attaching a screener to a strategy](/docs/strategies/attaching-a-screener-to-a-strategy) for the steps. Backtested figures describe the past only — see [Is this financial advice?](/docs/investing-theory/is-this-financial-advice). ## How does Fincanva handle it? - **A screener may hold up to 10 filters, on every plan.** The figure is the same whichever plan you are on, and no upgrade raises it — there is no higher figure to buy. It is still enforced where a strategy is concerned: a strategy carrying a copy of a screener with more than 10 filters reads [outside the plan](/docs/backtesting/plan-compliance) until you remove filters from that strategy's own copy, or detach it. Trimming the screener in your library does not clear it — attaching copies the filters into the strategy, and the two are independent from then on. - **A screener that already holds more than 10 keeps working, and says so.** Until recently nothing checked how many filters a screener carried when you saved it, on any plan — and on one plan the limit itself was higher before it was levelled — so a screener saved then may still carry, say, 15 filters. It reads, returns matches and backtests. Opening it on its own screener page, where it is yours to edit, shows a note above its filters — *"This screener holds 15 filters; the limit is now 10. It goes on running, and your changes to it save normally while it holds no more than the 15 filters it was saved with. You cannot go above that number. No plan raises this limit."* (A screener in a public folder is not yours to save, so it carries no note.) You can rename it, change its universe, edit a filter you already have, and remove filters — all of that saves normally. **What is measured is what it was SAVED with, not the figure of 10**: an edit to this screener is refused only when it would leave it holding more filters than it already has. Add a sixteenth and the note changes to say the draft cannot be saved and how many rows to take out; that wording goes as soon as the editor is back to the 15 it was saved with. Bring the editor down to 10 or fewer and the note goes altogether, before you save anything — reload without saving and it is back, because what it reads is the screener as SAVED. And every save below your old number becomes the new one: save at 12, and 12 is what the next edit may carry. Nothing is deleted, and no plan is being withheld from you — there is no higher figure to buy. - A new screener opens as "Untitled screener" over the widest universe, and **Save** stays disabled until you change something: "Add a filter or change the universe to enable Save." - Filters combine with AND, so an instrument has to pass all of them to be a match. - A screener's matches refresh daily as new market data arrives, so the same screener can return a different set from one day to the next with no edit from you. - Public screeners are read-only. To change one you use **Copy to Mine**, which puts your own editable copy in your library. - Editing filters makes a screener's last backtest stale rather than deleting it: the app keeps showing the previous run under "Out of date — filters changed since the last backtest. Showing the previous run." ## What does it look like in practice? You want cheap, sizeable US stocks with strong returns on equity. You set the universe to US-listed stocks, then add three filters: `P/E < 15`, `Market Cap > 2B`, and `ROE > 15`. The **Matches** count falls with each one — from the whole universe, to a few thousand, to a few hundred, to 38. Those 38 instruments are the screener's matches: the set a backtest measures and an attached strategy buys. Loosen `P/E < 15` to `P/E < 20` and the count rises again, because one condition became easier to pass. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/getting-started/screener-attach # Screener attach A screener attach is a [screener](/docs/getting-started/screener) embedded inside a strategy so that a rule, rather than a hand-picked list, decides which instruments the strategy may hold. An attached screener is re-evaluated at every rebalance, and it sits in one of two pools: a **qualifying** pool, which brings instruments in, and a **rejecting** pool, which takes them out. Attaching copies the screener into the strategy, so from that moment the attachment is independent of the saved screener it came from. **Also seen as:** In and Out screeners, entry screener / exit screener, Qualify and Reject, Attach to In / Attach to Out ## What do the two screener pools do? The qualifying pool decides who is considered, and the rejecting pool decides who is thrown out — the app states each rule where the pool is: "Instruments must match an In screener to be considered." and "Instruments matching any Out screener are excluded." Within a pool, membership is **any**, not all: the pool header reads "Match any" with the count of screeners in it, so an instrument that matches one qualifying screener is a candidate even if it fails the others, and an instrument that matches one rejecting screener is out even if it fails the others. Filters *inside* a single screener still combine with AND — see [matches](/docs/screeners/matches). The two pools are only available together in **Compose**; the other [asset-selection modes](/docs/getting-started/asset-selection-modes) carry a single screener with no rejecting pool. ## How do the qualifying and rejecting pools combine? The candidate set is the union of what the qualifying screeners match, minus the union of what the rejecting screeners match: $$ S = \left( \bigcup_{i=1}^{n} Q_i \right) \setminus \left( \bigcup_{j=1}^{m} R_j \right) $$ where: $S$ is the set of instruments the strategy may hold at that rebalance; $Q_i$ is the set of instruments in the working scope that match the $i$-th qualifying screener; $R_j$ is the set that match the $j$-th rejecting screener; $n$ and $m$ are how many screeners sit in each pool; the working scope is the basket if it has instruments in it, and the whole market otherwise; and when $n = 0$ the first union is the whole working scope, because nothing is narrowing it. Union (∪) is why "Match any" behaves the way it does inside a pool, and set difference (∖) is why one rejecting match is enough to remove an instrument no matter how many qualifying screeners liked it. ## What does it look like in practice? A strategy's basket holds ten tickers, so that basket is the working scope: `AAPL · MSFT · NVDA · TSLA · JNJ · PFE · KO · WMT · XOM · GE` Two screeners sit in the qualifying pool and one in the rejecting pool. Suppose at this rebalance they match: | Pool | Screener | Matches | |---|---|---| | Qualify | $Q_1$ | JNJ · PFE · KO · WMT · XOM | | Qualify | $Q_2$ | AAPL · MSFT · NVDA · TSLA | | Reject | $R_1$ | TSLA · XOM | The qualifying union $Q_1 \cup Q_2$ is nine tickers — everything except **GE**, which matched neither, so it is never a candidate. Subtracting $R_1$ removes **TSLA** (a candidate via $Q_2$) and **XOM** (a candidate via $Q_1$), leaving seven: `AAPL · MSFT · NVDA · JNJ · PFE · KO · WMT` Those seven are what the strategy may hold at this rebalance. A [**Max positions**](/docs/strategies/max-positions) cap applies on top: with the cap at 5, the strategy holds five of the seven rather than all of them. At the next rebalance the same three screeners are re-evaluated and the seven can be a different seven. ## Does editing the saved screener change strategies that already use it? No — attaching copies the screener's filters into the strategy at that moment, so a later edit to the saved screener in your library does not reach strategies that already have it attached. Each attachment is its own copy: you edit that copy's filters from inside the strategy, and the change affects only that strategy, never your library screener or another strategy that attached the same one. This is the same copy-on-use rule that governs [Duplicate and Copy to Mine](/docs/getting-started/duplicate-and-copy-to-mine). Fincanva does remember which library screener an attachment came from, but only to support one manual, one-directional action: **Update source screener** pushes the strategy's copy back onto the saved screener, overwriting its filters and universe. Nothing pushes the other way. When the attachment has no library origin — one inserted empty, or one whose original was deleted — the option is unavailable and reads "No source screener tracked — use Save as new instead". ## How does Fincanva handle it? - **Attaching a screener to a strategy is not included on the Free plan.** Free attaches none — a screener still runs on its own there — while Starter attaches 1, Advanced 2, and Ultimate and Professional 8. See [what each plan includes](/docs/account-security/what-each-plan-includes). - An attached screener is shown by name with its filter count, and can be opened and edited without detaching it. - Adding a second screener to a pool widens that pool, because a pool matches on *any* of its screeners — it does not tighten it the way adding a filter to one screener does. - A rejecting screener with no qualifying screener leaves the working scope as the candidate set and only subtracts from it; Fincanva flags that case as something to check rather than blocking it — see [strategy alerts](/docs/backtesting/strategy-alerts). - A strategy on the screener path needs at least one attached screener before it can be saved and run: "Add at least 1 screener." - The full step-by-step is in [Attaching a screener to a strategy](/docs/strategies/attaching-a-screener-to-a-strategy). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/getting-started/simulation-engine # Simulation engine The simulation engine is the computation service that runs your backtests — it replays each strategy over historical data and returns the equity curve and metrics you see. A small status indicator reports its current state, and that state signals how fresh your results are: while the engine is refreshing market data, newly requested results may lag until the refresh finishes. **Also seen as:** backtesting engine, compute engine ## How does Fincanva handle it? - The status indicator shows three states, worded in the app as "Engine healthy", "Engine updating data", and "Engine unavailable". - "Engine healthy" means backtests run normally and results reflect the latest available market close. - "Engine updating data" means new market data is loading; existing results stay usable, but the very latest figures may not be in until the refresh completes. - "Engine unavailable" means the engine cannot be reached right now, so new backtests and refreshes wait until it returns — already-computed results still display. - **This indicator is about the engine; it is not a strategy's status.** Your strategies keep their own [run status](/docs/backtesting/run-status), which always describes the strategy and never Fincanva — no strategy ever reads "unavailable" because the engine could not be reached. ## What does it look like in practice? You open a strategy and the indicator reads "Engine updating data". Your existing results still show, but a run you request now may take longer or reflect data from just before the refresh. You wait a few minutes; the indicator returns to "Engine healthy", you run the [backtest](/docs/getting-started/backtest) again, and the results now include the most recent market close. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/getting-started/step-by-step # Step by step **Step by step** is Fincanva's strategy walk-through: it puts one decision on screen at a time, from naming the strategy to running its first [backtest](/docs/getting-started/backtest). **Step by step** and [All at once](/docs/getting-started/all-at-once) are the product's official pair of editing views — they edit exactly the same [strategy](/docs/getting-started/strategy) and differ only in how much of it they show you at once. A single strategy walks a rail of up to six steps; a [Combined](/docs/getting-started/combined) walks a four-step rail of its own, at the [Combined level](/docs/getting-started/combined-level). **Step by step** is the view you meet when you create a strategy, and an existing strategy can be reopened in it at any time. **Also seen as:** the walk-through ## What are the six steps in the Step by step view? A single strategy's walk has six steps, each titled as a task. The order below is the full rail — the one a **Full setup** strategy runs end to end. A [Combined](/docs/getting-started/combined) walks a shorter rail of its own instead; see [Which steps does a Combined walk?](#which-steps-does-a-combined-walk). | # | Step | What it sets | |---|---|---| | 1 | **Set up your strategy** | the strategy's name and how often it [rebalances](/docs/backtesting/rebalance) | | 2 | **Pick assets** | the instruments and screeners the strategy will trade | | 3 | **Set risk conditions** | the [risk conditions](/docs/strategies/risk-condition) that switch the strategy to its Risk-Off allocation | | 4 | **Distribute capital** | how capital is weighted across the instruments | | 5 | **Define exit rules** | the [take-profit](/docs/strategies/take-profit) and [stop-loss](/docs/strategies/stop-loss) rules applied to each position | | 6 | **Review & backtest** | a last check of the whole configuration, including any [strategy alerts](/docs/backtesting/strategy-alerts), then the first run | ## Why does the step counter say fewer than six? The step counter counts only the configuring steps your walk requires, and it never counts the final step — so a **Full setup** strategy reads `Step 1 of 5` on its first step, and the final step shows a **Review** badge instead of a number. The six-step rail is the maximum; each [strategy type](/docs/getting-started/strategy-type) walks a shorter required path through it, and a [Combined](/docs/getting-started/combined) walks a different rail altogether. **The progress strip beside the step counts something different, on purpose.** The step counter answers *where am I*; the strip answers *what have I looked at*. So the strip counts the whole required path **including the final step** — which its own row labels **Recap** — giving 2 for **Single instrument**, 4 for **Multiple instruments** and **Screener**, 6 for **Full setup**, and 4 for a **Combined**. A step counts as soon as you **move on** from it — with **Continue**, with **Back**, or by switching to [All at once](/docs/getting-started/all-at-once) — never when you arrive; the final **Recap** step is the one exception and counts on arrival. Leaving the walk any other way does not count the step you were on: the workspace navigation, the section tabs and your browser's Back button all leave it as it was, ready to be counted when you next move on from it. A decision taken out of order counts just the same. Optional steps are listed with their values but never counted: if they were, a strategy you want no risk conditions on could never reach the end. ## Which steps does each strategy type require? Each strategy type has its own required path; the steps it does not require are still available, offered as **Optional add-ons** on the final step rather than as screens you walk through. | Strategy type | Required steps | Offered as optional add-ons | |---|---|---| | **Single instrument** | Pick assets · Review & backtest | Rebalance, Allocation (sizing only — there is one instrument), Risk, Position exits | | **Multiple instruments** | Set up your strategy · Pick assets · Distribute capital · Review & backtest | Risk, Position exits | | **Screener** | Set up your strategy · Pick assets · Distribute capital · Review & backtest | Risk, Position exits | | **Full setup** | all six | none — every step is required | A **Combined** is not in this table because it has no strategy type at all: strategy type belongs to each member strategy, never to the Combined that blends them. Its rail is the next section. ## Which steps does a Combined walk? A [Combined](/docs/getting-started/combined) walks four required steps, and every one of them acts on the Combined itself rather than on any one member strategy. Its progress strip therefore reads 4 — the same number as **Multiple instruments** and **Screener**, only counted at the [Combined level](/docs/getting-started/combined-level) — and its step counter starts at `Step 1 of 3`, because the counter never counts the final step. | # | Step | What it sets | |---|---|---| | 1 | **Set up your Combined** | the Combined's name and how often the Combined [rebalances](/docs/backtesting/rebalance) | | 2 | **Choose the strategies** | which of your strategies this Combined blends | | 3 | **Split the capital** | how capital is split across those strategies | | 4 | **Review & backtest** | a last check of the whole Combined, then its first run | **Choose the strategies** occupies the same slot **Pick assets** holds on a single strategy: at the Combined level what you pick is strategies, not instruments. Two things set the Combined's rail apart from every strategy type's: - **Set Combined risk** is optional — offered, never counted, exactly like every other optional step. It defines the [risk conditions](/docs/strategies/risk-condition) that de-risk the whole Combined when they trigger. - **Exit rules are absent entirely**, not optional. [Take-profit](/docs/strategies/take-profit) and [stop-loss](/docs/strategies/stop-loss) rules live on each member strategy, which keeps its own; the Combined has none of its own to set. The Combined's allocation and risk are a separate layer above each member strategy's, and the walk states it beside the progress strip: "Combined allocation and risk sit above each strategy's own — the backtest applies both." Neither layer merges into the other. An [Incomplete Combined](/docs/backtesting/incomplete-combined) — one still holding fewer than two strategies — opens this same walk. Its **Choose the strategies** step is exactly where that is fixed. ## How does Fincanva handle it? - On a single strategy the strategy type is chosen first, on the "How do you want to build this strategy?" screen, and it is what shapes the required path; the screen states that you can change anything later. A Combined never sees that screen and has no strategy-type switch inside the walk, because the Combined level has no strategy type. - A **progress strip** sits beside the step, listing every step in the walk's order together with its current value. Each counted step carries a **Seen** mark that fills as soon as you move on from that step — whether the move succeeds or not — and the strip's title states the count — *"0 of 2 steps seen"*, and *"All 6 steps seen"* once none are left. Steps the walk does not require sit below an **Optional** divider: they state their values and carry no mark. On a Combined the strip names the walk **Combined** where a single strategy's names its strategy type. - **A Seen mark belongs to the walk it was earned in.** A single strategy's walk and a [Combined](/docs/getting-started/combined)'s walk keep their marks separately, so a strategy sitting at *"All 6 steps seen"* opens its Combined walk at *"0 of 4 steps seen"* and has to walk it — choosing the strategies and splitting the capital are Combined steps, and they had never been on screen. Nothing is thrown away: the marks it earned as a single strategy stay with it and are all still there if it is a single strategy again. Inside one walk, marks survive a [strategy type](/docs/getting-started/strategy-type) change — switch a **Full setup** strategy to **Screener** and every mark it already has still counts. - **Every row always states a value**, including when a setting is off or empty — *"no conditions"*, *"no rules"*, or the volatility ranking the engine falls back to when nothing is picked. No row is ever blank. - On a single strategy, a step is gated when the strategy does not yet match its type — for example "Pick exactly 1 instrument." on a Single instrument strategy — and stays blocked until you fix the content or change the [strategy type](/docs/getting-started/strategy-type). A Combined has no strategy type, so no gate of this kind applies to its walk. - The final step commits with **Backtest** — it saves and starts the first backtest in one action, and reads **Backtesting…** while it runs, adding the percentage once progress is known; see [Saving, running, and copying a strategy](/docs/strategies/saving-running-and-copying-a-strategy). - **Backtest leaves you on Review & backtest.** The walk does not navigate away from its final step: the run works while you stay there, and once it finishes and a result exists, a **View results** button appears next to **Back** and opens the strategy's **Analysis** section. If the strategy saves but the run doesn't start, Fincanva shows "Saved, but the backtest didn't start. Try again." and leaves you on the step. - **Step by step** opens **inside the strategy workspace** — the same navigation, library pane and header **All at once** uses, with **Settings** showing as the active section. The two views are one place seen two ways. - A saved strategy reopens in the walk-through from **Step by step** in its **Settings** header — a Combined included, since its walk is the Combined level that page already edits. In the other direction, an **All at once** control switches the same strategy into that view without losing anything. There is no shortcut out of the strategy-type picker itself — you choose a type first, then switch. - A public strategy opens in **Step by step** but cannot be saved from it — see [Mine / Public](/docs/getting-started/mine-public). ## What does it look like in practice? You want a two-instrument strategy that rebalances monthly. You pick **Multiple instruments**, so **Step by step** gives you a four-step path and the counter reads `Step 1 of 3`. On **Set up your strategy** you name it and set the cadence to one month; on **Pick assets** you add two tickers; on **Distribute capital** you leave the default weighting; **Review & backtest** shows the whole thing and you press **Backtest**. You never see a Risk or Exit-rules screen — both sit on the final step under **Optional add-ons**, ready to add later. Doing the same build in [All at once](/docs/getting-started/all-at-once) would put all of those settings on one page instead, in any order you like. Now blend that strategy with two others. The [Combined](/docs/getting-started/combined) walks its own four steps and the counter again reads `Step 1 of 3`: **Set up your Combined** names it and sets how often the Combined rebalances, **Choose the strategies** picks the three strategies, **Split the capital** decides how much each receives, and **Review & backtest** runs it. No exit-rules screen appears at any point — each of the three strategies still carries its own — and **Set Combined risk** waits under **Optional add-ons** if you want a risk layer over the whole thing. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/getting-started/strategy # Strategy A strategy is a saved set of instruments together with the rules for how capital is weighted across them and when positions change — the unit you backtest, keep in your library, and follow over time. A strategy holds instruments directly, and it is what every [backtest](/docs/getting-started/backtest) runs on. It is also the building block of a [Combined](/docs/getting-started/combined), which holds strategies instead of instruments. **Also seen as:** trading strategy, investment strategy Earlier versions of Fincanva called this object a *model* or a *component*. Both names are retired — the app says strategy everywhere now. ## What does a strategy contain? A strategy contains its instruments plus the rule groups that decide how those instruments are held. **Asset selection** sets which instruments it trades — picked by hand or chosen for it by an attached [screener](/docs/getting-started/screener). **Allocation** sets how capital is split across them. **Rebalance every** sets how often the weights are reset (see [rebalance](/docs/backtesting/rebalance)). **Risk** and **Position exits** are optional and add conditions that change the allocation or close a position. [What is a strategy in Fincanva?](/docs/strategies/what-is-a-strategy-in-fincanva) covers each part in full. ## How is a strategy different from a Combined? A strategy holds instruments; a Combined holds strategies and splits capital across them. The pieces inside a Combined are themselves strategies — deliberately the same object you build on its own — so "strategy" covers both a standalone strategy and a [strategy in a Combined](/docs/getting-started/strategy-in-a-combined). Where the whole and its pieces appear together the whole is always called the Combined, never a generic "strategy", and destructive actions name their level: "Remove this strategy from the Combined" versus "Delete Combined". ## How does Fincanva handle it? - A strategy needs at least one instrument before it can run, and a strategy that selects instruments through a screener needs at least one screener attached. The editor's own setup checks are listed under [strategy alerts](/docs/backtesting/strategy-alerts). - Strategies are listed under **Strategies**, split into **Single** and **Combined** — a Combined is a strategy too, just one whose members are strategies. - Four strategy types shape what you fill in when you create one; they change which steps you see, not what the backtest computes. See [Choosing a strategy type](/docs/strategies/choosing-a-strategy-type). - A strategy can be followed live with [Mark Live](/docs/getting-started/mark-live), which lists it as a [portfolio](/docs/getting-started/portfolio) on the Portfolios page. Nothing is traded and no order is placed. - Editing a saved strategy leaves its last result in place until you run it again; the [run status](/docs/backtesting/run-status) chip reads **Needs re-run** until then. ## What does it look like in practice? You start from an idea: hold the strongest recent performers among S&P 500 stocks and refresh the list every month. As a strategy that becomes one saved object — a [universe](/docs/getting-started/universe) of S&P 500 stocks, an attached screener that ranks them on recent price change, **Ranking-Based** allocation so the highest-ranked receive the most capital, and **Rebalance every** set to 1 month. You run it, read the equity curve and metrics, then change the rebalance to 3 months and run again. Both runs describe the same strategy — one object, two settings — which is exactly why it is worth saving as one. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/getting-started/strategy-in-a-combined # Strategy in a Combined A strategy in a Combined is one of the strategies that a [Combined](/docs/getting-started/combined) holds and allocates capital across — the pieces of a Combined are themselves strategies, the same object you build on its own. Each piece keeps its own rules, instruments, and allocation, and the capital it receives is set one level above it, at the [Combined level](/docs/getting-started/combined-level). A strategy joins a Combined as a snapshot copy taken at the moment it is added, so later edits to the standalone original do not change the copy that now lives inside the Combined. **Also seen as:** member strategy, sub-strategy Earlier versions of the product called these pieces a *model* or a *component*. Both names are retired — they are strategies. ## How does Fincanva handle it? - A strategy joins a Combined as a snapshot copy taken when it is added; from that point the original and the copy are independent. - Editing the standalone strategy afterwards does not update the copy inside the Combined, and editing the copy does not change the standalone. - Where the whole and its pieces appear together, the whole is called the Combined; destructive actions name their level — "Remove this strategy from the Combined" versus "Delete Combined". - A strategy inside a Combined can be closed on its own if it loses enough of the capital allocated to it, and can resume at a later rebalance — the permanent-versus-restartable difference is covered in [bankruptcy rules](/docs/backtesting/bankruptcy-rules). - A strategy inside a Combined can be kept aside — switched off without being removed — and switched back on later with its settings and its weight unchanged; see [Can you switch a strategy in a Combined off without removing it?](#can-you-switch-a-strategy-in-a-combined-off-without-removing-it). ## Can you switch a strategy in a Combined off without removing it? Yes — a strategy in a Combined can be kept aside: switched off, still inside the Combined, and left out of every backtest until you switch it back on. On the Combined's **Strategies** card each strategy in use has a pause button ("Keep … aside") beside its remove ×. A kept-aside strategy moves to a group under the table titled "Kept aside (n) — left out of the simulation", with a play button ("Switch … back on") and the same remove ×. - **Nothing is lost while it is kept aside.** Its own settings and its weight at the [Combined level](/docs/getting-started/combined-level) stay exactly as they were, and switching it back on brings both back unchanged. Removing it, by contrast, takes it out of the Combined. - **It is left out of the run.** The Combined's capital is split across the strategies in use only; the table on the card lists those, and its weight total covers those alone. - **Its own page says so.** Opening a strategy kept aside shows "This strategy is kept aside: it stays in the Combined but is left out of the simulation." with **Switch back on**, which follows the same plan limit as the play button. - **It does not count toward your plan's limit** on strategies in use in a Combined — only the ones switched on do, and a Combined always counts as at least two. Its own settings (positions, attached screeners, risk conditions, allocation method) are still held to the plan; see [plan compliance](/docs/backtesting/plan-compliance). - **At the plan's limit it cannot be switched back on.** Pressing play leaves the strategy kept aside, and the card says "The Advanced plan allows 5 strategies in use. To switch another one back on, keep one aside first, or switch to Ultimate." — naming your own plan, its limit and the first plan that allows the number you asked for, or leaving the last clause out when no plan does. A Combined saved with more strategies in use than your plan allows — one carried over from the previous platform, say — can still switch strategies back on up to the number it was last saved with; only going beyond that is refused. - **On a plan without Combined strategies nothing can be switched back on.** A Combined always counts as at least two, so on a plan allowing one strategy in use the card says "The Starter plan does not include Combined strategies. To use one, switch to Advanced." instead. - **Adding a strategy counts too.** A strategy you add joins in use, so at the plan's limit choosing one to add leaves the roster as it is, and the card says "The Advanced plan allows 5 strategies in use. To add another one, keep one aside first, or switch to Ultimate." The **Add a strategy** window opened from the + beside the Combined's tabs follows the same rule: choosing a strategy or **Create a blank strategy** there adds nothing and shows the same sentence. - **A Combined still needs two strategies in use to run.** With fewer switched on, **Backtest** is refused with "Running this needs 2 strategies switched on." - **Kept aside or in use, a Combined holds at most 20 strategies.** At 20, choosing one more to add leaves the roster as it is, and the card says "A Combined holds at most 20 strategies, in use or kept aside." ## What does it look like in practice? You build a momentum strategy and run it on its own. You then add it to a Combined alongside two other strategies, and the Combined takes a snapshot copy of the momentum strategy exactly as it stood at that moment. A week later you change the standalone strategy's rebalance cadence. The copy inside the Combined keeps the old cadence — it was frozen at add time — so the standalone and the in-Combined copy now [backtest](/docs/getting-started/backtest) differently. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/getting-started/strategy-type # Strategy type Strategy type is the shape you pick when you create a strategy — **Single instrument**, **Multiple instruments**, **Screener**, or **Full setup**. It decides which build steps you walk through and what the strategy must contain before it can be backtested; it never changes how a [backtest](/docs/getting-started/backtest) is computed. There are exactly these four types, and you can change a strategy's type later. ## What are the four strategy types? Each type describes *what you are building*, and each carries a content requirement the app enforces before you can continue: | Strategy type | Described in the app as | Must contain | |---|---|---| | Single instrument | "Trade a single instrument." | exactly 1 instrument | | Multiple instruments | "A basket of instruments you choose." | 2 or more instruments | | Screener | "Let a screener pick the instruments." | at least 1 screener | | Full setup | "Every setting, built from scratch." | no count requirement | If the content does not match the type, the app blocks you and says which way to fix it: "Pick exactly 1 instrument.", "Pick 2 or more instruments.", or "Add at least 1 screener." The message offers **Change strategy type** as the alternative to changing the content. **Full setup** is the only type with no content requirement, because it exposes every setting rather than trimming the build to a shape. ## Can you change a strategy's type later? Yes, and it works the same way wherever you do it. The **Strategy type** row in **All at once** and the type picker in the walk-through both open the same four tiles and switch the strategy to another type, after the same confirmation spelling out the consequence. The tiles are the same four you saw at creation, but the line above them is not: when you are changing an existing strategy's type it reads "Changing the type is not a conversion — the sections the new type has no place for are reset. You'll see exactly what changes before it happens." The confirmation then spells out what the switch changes: - Any section you had configured that the new type does not require is reset to its defaults. The type is one setting for the whole strategy, so on a [Combined](/docs/getting-started/combined) that reset lands on every strategy inside it, not only the one you were editing — the confirmation says so, and the sections it lists are the ones configured anywhere in the Combined. - If the new type's Asset selection surface cannot hold what you have already selected, it says how much will go — for example "5 selected instruments will be removed" when you switch a hand-picked basket to **Screener**. - If your setup needs more than the new type offers, it says that instead: nothing further is removed, and the strategy keeps showing as the wider type. - It says how the switch moves your walk through [Step by step](/docs/getting-started/step-by-step), because each type requires a different set of steps. Steps that join the walk have not been reviewed yet, so a walk you had finished stops being complete — "You had reviewed every step. 2 steps you have not reviewed join the guided build, so it is no longer complete." — while a switch that takes the unreviewed steps out of the walk can leave nothing to review. In **Step by step** the backtest opens only once every required step has been reviewed, so it is that walk the movement changes. Nothing you already reviewed is discarded: each step keeps its mark, so switching back costs you no progress. Nothing is removed until you save — switching back before saving keeps everything. The strategy type shapes what a strategy can hold, not only which steps you see: each type offers exactly one Asset selection surface — a basket you pick, or a screener that picks for you — and only **Full setup** offers all of them. That is why narrowing to **Screener** drops a hand-picked basket: a Screener strategy builds its selection from rules, so it has nowhere to keep one. Fincanva never trims your setup just to make a narrower type fit. Two Include screeners will not survive as a **Screener** strategy, and five instruments will not survive as **Single instrument** — so rather than delete the extras, the strategy stays as the wider type and keeps everything. The confirmation tells you which type that will be before you commit. For how each type reshapes the walk-through, see [Choosing a strategy type](/docs/strategies/choosing-a-strategy-type). ## How does Fincanva handle it? - You pick the type at creation, under the question "How do you want to build this strategy?", and there the picker's subheading reads: "You can change anything later — this just shapes the next few steps." That reassurance belongs to creation alone — the same four tiles, opened to change an existing strategy's type, say something different. - The type shows as a **Strategy type** column value in your strategies list. A [Combined](/docs/getting-started/combined) is not one of the four — it displays as **Combined** in that column instead. - The type does not change what a backtest computes, and it hides no *section*: in [All at once](/docs/getting-started/all-at-once) every section is either required by your type or offered as an optional add-on, whichever type you started from. - What the type does constrain is the Asset selection surface. **Compose** and its **Include**/**Exclude** screener pools exist only on **Full setup**, and [max positions](/docs/strategies/max-positions) is not a control anywhere you pick instruments by hand — on Single instrument, on Multiple instruments and on Full setup's **Basket** surface it is simply the number you picked. ## What does it look like in practice? You have a list of five stocks and you want to see how holding all five would have done. That is the **Multiple instruments** type: it wants 2 or more instruments, so five qualifies, and it gives you the Allocation step you need to decide how capital is split across them. Picking **Single instrument** instead would block you at Asset selection with "Pick exactly 1 instrument.", because that type holds exactly one. If you later replace your hand-picked five with a screener that chooses the holdings each period, switch the type to **Screener** — it requires at least 1 screener, and your fixed basket is no longer what defines the strategy. The confirmation warns that those five instruments will be removed, because a Screener strategy has no basket to keep them in. They are still there until you save, so you can back out. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/getting-started/universe # Universe A universe is the set of instruments a [screener](/docs/getting-started/screener) or strategy is allowed to draw from. "All" means the whole market; you narrow it with [filters](/docs/getting-started/filter) — on things like country, exchange, index, sector, [asset type](/docs/getting-started/asset-type), and asset subtype — until only the instruments you want to consider remain. Everything a strategy screens, ranks, or buys comes from this universe, and anything outside it can never be selected. The universe is the boundary; the filters inside a screener then choose from within it. **Also seen as:** investable assets The filters that narrow a universe were previously surfaced under the label "Restrictions"; that name is retired. ## How does Fincanva handle it? - "All" is the widest universe — the whole searchable market, including instruments that have since delisted, so a backtest is not limited to today's survivors. - Each filter you add (country, exchange, index, sector, asset type, asset subtype) shrinks the universe, and combining filters narrows it further. - A screener and its strategy draw only from the resulting universe; changing the universe changes what can be selected and can change results. ## What does it look like in practice? You start from "All" — roughly the whole catalogue of tradable [instruments](/docs/getting-started/instrument), tens of thousands of them. You add a country filter for the United States and an asset-type filter for stocks. The universe shrinks to US-listed stocks only. From then on the screener ranks, and the strategy buys, solely within that reduced set — a non-US stock or an ETP can no longer appear, however well it would have scored. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/changelog # Fincanva documentation hub is live **2026-07-21** · getting-started · 2026.07 The Fincanva documentation hub is now live on the site, replacing the previous knowledge base. It hosts guides, concepts, a glossary, FAQs, and this changelog, all authored and versioned alongside the product. New to Fincanva? Start with [Get started with Fincanva in five steps](/docs/getting-started/get-started-with-fincanva-in-five-steps). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/changelog # The sidebar is regrouped, and its plan tile shows your Live count **2026-09-24** · getting-started · 2026.09 The main sidebar's groups now follow the order of the work: Home and Screener first, then **Strategies** — Portfolios, Single, Combined — then **Other**, with Simulation settings, Learn and Documentation. The plan tile at its foot is one card: your plan and how many strategies you have [live](/docs/getting-started/mark-live), reading, for example, "Live 3/5". Its panel lists those live strategies and, wherever a plan above yours would let you keep more live, invites you to switch. See [what your Usage page tells you](/docs/account-security/what-settings-usage-tells-you). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/changelog # Two new ways to look something up in the docs **2026-08-01** · getting-started · 2026.08 The documentation now has two lookup surfaces of its own, both reachable from the docs subject tree. **Glossary**, at `/docs/glossary`, lists every term the docs define, A–Z — [Backtest](/docs/getting-started/backtest) and [CAGR](/docs/analysis/cagr) are two of them. **Questions**, at `/docs/questions`, indexes the questions the corpus answers, built from the pages themselves rather than maintained by hand, so it stays current as pages are written. The hand-written FAQ is retired in the same change: its answers now live on the pages that own them, and an old `/docs/faq/` page link redirects to the question index. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/investing-theory/is-this-financial-advice # Is this financial advice? No. Fincanva is a research and simulation tool: it lets you build, backtest, and follow strategies. Nothing in the app or these docs is a recommendation to buy, sell, or hold any instrument. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) ## What Fincanva does and does not tell you Fincanva shows you what a strategy would have done on historical data and how its rules behave; it does not tell you what to invest in or what will happen to your money. Decisions about your money are yours, and you are responsible for them. ## Does a good backtest mean the strategy will make money? No. A backtest shows what would have happened over a past period, not what will happen next. A strong historical result is not a promise of future gains — Fincanva will not tell you whether a strategy is a good investment, because that is advice and Fincanva gives none. ## Related For a headline result metric that describes the shape of a backtest, see [CAGR](/docs/analysis/cagr). --- URL: https://fincanva.com/docs/investing-theory/cherry-picking-bias # Cherry-picking bias Cherry-picking bias is the practice of quoting only the periods, instruments, or runs that flattered a strategy while leaving the rest out, so every number reported is true and the picture they add up to is not. Nothing has to be falsified — a good year really was a good year — but the reader is shown a slice of the evidence that was chosen *because* it was favorable, and has no way to see what was left out. Cherry-picking bias is an error of **reporting**: the underlying test can be entirely correct, and the distortion enters only when its results are described. **Also seen as:** Cherry picking, selective reporting ## What gets cherry-picked in a backtest? Four things are usually picked, and each is picked the same way — after the results are already known: - **The window.** A start and end date chosen because the stretch between them went well. This is the most common form, because a backtest makes any window one setting away. - **The instruments.** The names in the report are the ones that contributed; the ones that dragged get described as "not really part of the idea". - **The metric.** The return is quoted and the worst [drawdown](/docs/analysis/max-drawdown) is not, or the [gross](/docs/analysis/gross-vs-net) curve is shown while the net-of-costs one — the number a real account would have kept — is not (see [cost-ignoring bias](/docs/investing-theory/cost-ignoring-bias)). - **The run.** One configuration out of many tried is presented as *the* strategy, with no mention of the others. One test catches all four: could someone reproduce the claim without knowing which slice you chose? If the claim only holds on your slice, the slice is doing the work, not the strategy. ## What changes when you report 2019 and omit 2022? A strategy is backtested over the ten calendar years 2015–2024. Two of those years stand out: **2019 returned +31%** and **2022 returned −29%**. A report built around 2019 — the year label, the rising curve, the +31% — states a fact. Here is what the same run also says: | Figure from the same run | Value | |---|---| | 2019 calendar year | +31% | | 2022 calendar year | −29% | | Full period, total return | +72% | | Full period, annualized ([CAGR](/docs/analysis/cagr)) | 5.6% a year | | Worst peak-to-trough fall in the period | −34% | Quoting 2019 alone invites the reader to treat +31% as what the strategy does in a year; the run's own annualized figure is about a fifth of that. Put the omitted year back and the pair alone leaves the strategy below where it started: 1.31 × 0.71 = 0.93, or −7% across the two years together. None of those five numbers contradicts the others — they all come from one run. The distortion is entirely in which of them got quoted. {/* VISUAL: chart — the same equity curve shown twice, once cropped to the flattering window and once over the full period, with the omitted years shaded — tracked in VISUAL_BACKLOG */} ## How is cherry-picking bias different from selection bias and data-snooping bias? The three differ by **which step goes wrong**: cherry-picking bias is about what you *report*, [selection bias](/docs/investing-theory/selection-bias) is about what you *tested*, and [data-snooping bias](/docs/investing-theory/data-snooping-bias) is about *how many* things you tested before something looked good. They also stack, in that order. A researcher who tries fifty variants (data-snooping), keeps the one with the most flattering instrument list (selection), and then presents its best three years (cherry-picking) has committed all three, and the final report shows no trace of the first two. ## What does Fincanva do about cherry-picking bias? A Fincanva backtest reports the whole period it ran rather than a chosen stretch of it, and reports the falls alongside the gains: the same run that produces the return also produces its worst peak-to-trough [drawdown](/docs/analysis/max-drawdown), so the bad part of the history arrives attached to the good part. Because the run is a [walk-forward replay](/docs/investing-theory/walk-forward-replay) of the full span, there is no version of the result that covers only the years that worked. [Start-date sensitivity](/docs/analysis/start-date-sensitivity) is the direct answer to the window form of cherry-picking: it re-runs the same strategy across many entry dates and several holding windows and reports the *range* of outcomes — the best start against the worst start, and the share of start dates that ended positive. A claim that survives only one entry month shows up immediately as a wide range. What the product cannot do is decide what you tell other people, or yourself. Choosing one favorable screenshot out of a run that offers the full picture is still available to anyone, which is why cherry-picking is usually discussed next to [confirmation bias](/docs/investing-theory/confirmation-bias) — the same selection applied inwards. See [the nine biases Fincanva helps you avoid](/docs/getting-started/the-nine-biases-fincanva-helps-you-avoid) for the product behavior in context, and [data-quality bias](/docs/investing-theory/data-quality-bias) for the case where the numbers themselves, not their selection, are the problem. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/investing-theory/confirmation-bias # Confirmation bias Confirmation bias is the tendency to read evidence in favor of a conclusion you already hold — accepting the results that agree with your idea at face value while finding reasons to discount the ones that disagree. It is the most human of the backtesting biases, because it needs no bad data, no broken test, and no intent to mislead: the same person can run a technically flawless backtest and still come away believing something the run did not say. Confirmation bias is an error of **interpretation**, so it survives every fix applied to the data and the rules. **Also seen as:** Confirmatory bias, my-side bias ## How does confirmation bias show up when you read a backtest? It rarely feels like bias from the inside. It feels like judgment. The recognizable patterns are: - **Stopping when it agrees.** The first run that supports the idea ends the investigation; a run that contradicted it would have prompted three more. - **Asymmetric scrutiny.** A confirming result is accepted as-is. A disagreeing one gets audited — wrong universe, wrong period, "something's off with the data" — and the audit stops as soon as a reason is found. - **Reasons produced after the result.** The objection to a run is invented once its number is known. If a disagreeing run had come out well, the same objection would never have been raised. - **Reading only the flattering metric.** The return is read and the worst [drawdown](/docs/analysis/max-drawdown) is skipped, or the strategy's own figure is read without the [benchmark](/docs/getting-started/benchmark) beside it. - **Remembering the run that agreed.** Weeks later the memory is "it worked" — the version of the test that agreed, not the version that didn't. A useful check is a single question asked *before* a run finishes: what result would make me abandon this idea? An idea with no such result is not being tested. ## How do the run you kept and the run you explained away compare? You believe a twelve-month momentum rule works, and you test it over 2015–2024. - **Run 1** applies the rule to twenty large, familiar companies. It returns **9.1% a year**. This matches what you expected, so you save it. - **Run 2** applies the identical rule to a broad four-hundred-name [universe](/docs/getting-started/universe). It returns **3.4% a year**. You conclude the wider universe has too many low-quality names in it, and you set the run aside. Now put the [benchmark](/docs/getting-started/benchmark) next to both. Over the same period it returned **7.8% a year**, so run 1's [excess return](/docs/analysis/excess-return) is +1.3pp and run 2's is −4.4pp. Two things follow. First, even the run you kept beat its benchmark by a much thinner margin than "9.1%" suggested on its own. Second, and more important: the reason you gave for discarding run 2 was produced *after* you saw its number. Had run 2 returned 12%, the four-hundred-name universe would not have been "too junky" — it would have been "a broader, fairer test". That asymmetry, not the numbers, is the bias. ## What separates confirmation bias from cherry-picking bias? The difference is the audience. [Cherry-picking bias](/docs/investing-theory/cherry-picking-bias) is selective reporting **outwards** — you have the full result and you show someone else a favorable part of it. Confirmation bias is the same selection turned **inwards** — you show it to yourself, usually without noticing, and there is no moment of deciding to omit anything. The two feed each other. Confirmation bias decides which run you believe; cherry-picking decides which run you present. And a disagreeing result blamed on "bad data" without anyone checking the data is confirmation bias borrowing the language of [data-quality bias](/docs/investing-theory/data-quality-bias) — as is switching costs off because the net curve "looks wrong" (see [cost-ignoring bias](/docs/investing-theory/cost-ignoring-bias)). ## What does Fincanva do about confirmation bias? A [backtest](/docs/getting-started/backtest) applies your rules mechanically across the whole history regardless of what you hoped would happen, and reports the result whole — the return, the worst peak-to-trough [drawdown](/docs/analysis/max-drawdown), the losing months, and the [benchmark](/docs/getting-started/benchmark) run over the identical period beside it. That gives the rules a standing chance to disagree with you, and it puts the disagreeing evidence on the same screen as the agreeing evidence rather than one search away. It cannot make you read it. Nothing in a backtest stops you from dismissing an inconvenient run, and no tool can supply the intent to be proved wrong. See [the nine biases Fincanva helps you avoid](/docs/getting-started/the-nine-biases-fincanva-helps-you-avoid) for the product behavior in context. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/investing-theory/cost-ignoring-bias # Cost-ignoring bias Cost-ignoring bias is judging a strategy on returns that leave out what trading actually costs — commissions, the bid-ask spread, [slippage](/docs/backtesting/slippage), financing, and tax — so a strategy that loses money once those are paid can look like a clear winner before them. The gross figure is not wrong; it is simply answering a different question from the one an investor asks, which is what an account would have *kept*. Cost-ignoring bias grows with how often a strategy trades, so it hits the most active strategies hardest — exactly the strategies whose gross results tend to look most impressive. **Also seen as:** Cost blindness, gross-only reporting ## Which costs does a cost-blind backtest leave out? Five separate charges are all missing from a gross figure, and they are missing for different reasons: - **Commissions and fees** — a per-trade or per-value charge paid on entry and again on exit; see [transaction cost](/docs/backtesting/transaction-cost) for how the charge itself is defined. - **The bid-ask spread** — you buy at the higher quote and sell at the lower one, so a round trip pays the spread even if the price never moves. - **[Slippage](/docs/backtesting/slippage)** — the gap between the price an order is quoted at and the price it actually fills at, which widens for larger orders and thinner instruments. - **Financing and interest** — the cost of borrowed money and the [markups](/docs/backtesting/interest-rate-markups) applied to interest rates, which apply to leveraged and short positions. - **Tax** — withholding on dividends and tax on realized [capital gains](/docs/backtesting/capital-gains-tax), which depends on your [tax regime](/docs/backtesting/tax-regime). The first three are paid per trade. That is what makes turnover, not cost per trade, the dominant term. ## How does turnover multiply a small cost into a large one? The drag a strategy pays each year is its all-in cost per round trip multiplied by how many round trips it makes — so a cost too small to notice on one trade becomes a large annual number for a strategy that trades often. $$ r_{\text{net}} \approx r_{\text{gross}} - T \times c $$ where $r_{\text{gross}}$ is the annual return before costs, $r_{\text{net}}$ is the annual return after them, $T$ is annual turnover (how many times a year the portfolio's value is fully traded), and $c$ is the all-in cost of one round trip as a fraction of the value traded. The relation is an approximation — it ignores compounding within the year and any tax — but it is the right first estimate, and it shows the shape of the problem: halving $c$ helps once, while halving $T$ helps every year. A [rebalance](/docs/backtesting/rebalance) is the main source of turnover. A strategy that rebalances annually has $T$ near 1; one that rebalances fortnightly has $T$ in the twenties. ## How can a gross winner be a net loser? A strategy rotates its whole portfolio roughly every two weeks — about **24 full rotations a year**, so $T = 24$. Its all-in round-trip cost is **0.30%** of the value traded, combining commission, spread, and slippage. Before costs it compounds at **+6.0% a year**. | | Calculation | Result | |---|---|---| | Annual cost drag | 24 × 0.30% | **7.2% a year** | | Net annual return | 6.0% − 7.2% | **−1.2% a year** | | \$10,000 over 10 years, gross | 10,000 × 1.060¹⁰ | **\$17,908** | | \$10,000 over 10 years, net | 10,000 × 0.988¹⁰ | **\$8,863** | The gross curve nearly doubles the starting capital while the net curve ends below it — a difference of about \$9,000 on a \$10,000 start, produced entirely by a cost of three tenths of one percent per round trip. Tax would land on top of this for a strategy that did finish in profit, since it applies to realized gains and a strategy that rotates fortnightly realizes them constantly. Cut $T$ from 24 to 2 and the same 0.30% cost produces a 0.6% drag instead of 7.2%, turning the same gross 6.0% into roughly 5.4% net. Nothing about the strategy's ideas changed — only how often it acted on them. {/* VISUAL: chart — the same strategy's gross and net equity curves on one axis, diverging as turnover accumulates, with the shaded gap labelled as cumulative costs — tracked in VISUAL_BACKLOG */} ## How does Fincanva handle it? - Costs and tax are two of the three [simulation assumptions](/docs/backtesting/simulation-assumptions) applied to a backtest: **[Costs & interests](/docs/backtesting/costs-toggle)** covers trading costs, financing, and interest, and **[Taxes](/docs/backtesting/taxes-toggle)** covers tax on dividends and realized gains. - By default a result is shown with **Costs & interests** and **Taxes** off, so the figures you first see are gross of both — a cost-blind view by construction, which is why it is worth knowing which view you are reading. - Switching **Costs & interests** on applies modelled trading costs including [slippage](/docs/backtesting/slippage) to every fill; with it off, modelled costs and slippage are zero. - The costs actually paid appear in the result's [P&L breakdown](/docs/analysis/p-l-breakdown), so the drag is readable as an amount rather than inferred from the gap between two curves. ## How do you read the gap between the gross and net figures? The gap is a measure of how much the conclusion depends on the cost assumptions rather than on the strategy. A strategy whose [gross and net](/docs/analysis/gross-vs-net) figures sit close together is largely insensitive to those assumptions, so its result stands or falls on its own rules; one whose figures diverge sharply is telling you that most of the gross result is being consumed on the way through, and that its conclusion changes with any change to turnover, instrument liquidity, or fee schedule. Reading only the gross figure is a metric-level [cherry-pick](/docs/investing-theory/cherry-picking-bias), and reaching for the gross figure because the net one contradicts an idea you already hold is [confirmation bias](/docs/investing-theory/confirmation-bias). Neither is a statement about which figure is correct — both are correct answers to different questions. See [the nine biases Fincanva helps you avoid](/docs/getting-started/the-nine-biases-fincanva-helps-you-avoid) for the product behavior in context. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/investing-theory/data-quality-bias # Data-quality bias Data-quality bias is a backtest conclusion driven by errors, gaps, or unadjusted events in the underlying data rather than by the strategy's own rules. It is the hardest bias to notice, because nothing in the result looks broken: the metrics are computed correctly, the equity curve is drawn correctly, and the arithmetic is right — it was simply performed on the wrong numbers. A single mishandled corporate action can produce a price move that never happened, and every rule and metric downstream will treat that move as real. **Also seen as:** Bad-data bias, data-error bias ## What kinds of data problems distort a backtest? Six problems account for most of it, and they fail in different directions: - **Unadjusted corporate actions.** A split, reverse split, spin-off, or dividend changes the quoted price without changing what a holder owns. An unadjusted series reads that as a return. - **Missing or stale prices.** A gap filled by repeating the last price makes an instrument look motionless, which understates its volatility and hides any fall that happened inside the gap. - **Currency mismatches.** A price quoted in one currency compared with a value in another produces a difference that is an exchange rate, not a return. - **Coverage that starts later than you assumed.** An instrument whose history begins part-way through the tested period contributes nothing before that point, so the early years of the test quietly describe a smaller portfolio than you specified. - **An instrument list that has already dropped the failures.** This is [survivorship bias](/docs/investing-theory/survivorship-bias) reaching the test through the data rather than through your choices. - **Revised or restated figures.** A value corrected after its first release, used as though the corrected version had been known on the original date, is [look-ahead bias](/docs/investing-theory/look-ahead-bias) with a data cause. For a backtest to mean anything, corporate actions such as [splits and dividends](/docs/analysis/dividends-and-splits) have to be handled correctly, because they are the events where the quoted price and the holder's actual wealth come apart. ## Why splits and dividends have to be adjusted A **split** multiplies the number of shares and divides the price by the same factor. A holder's position is worth exactly what it was worth a moment before, so the correct return across a split is zero — which the data can only show if every price before the split is restated onto the post-split scale. A **dividend** takes cash out of the company and hands it to the holder, so the price typically drops by roughly the dividend on the ex-dividend date. A price-only series records that drop as a loss and never records the cash, which systematically understates [total return](/docs/analysis/total-return). The size of the omission compounds: on a stock yielding about 3% a year, reinvested dividends multiply the outcome by roughly 1.03²⁰ ≈ 1.8× over twenty years, so the dividend component accounts for something like 45% of the total return that a price-only series leaves out entirely. Not every surprising number is a data error, though. A dividend that appears as a **cost** rather than income is the expected behavior on a short position, not a defect — see [negative dividends](/docs/analysis/negative-dividends). ## How can a stock split look like a 50% crash? A stock trades at **\$200**. It carries out a **2-for-1 split**, and the next session's quote prints at **\$100**. | | Before the split | After the split | |---|---|---| | Shares held | 100 | 200 | | Price | \$200 | \$100 | | Position value | \$20,000 | \$20,000 | | True return | — | **0%** | | Return an unadjusted price series reports | — | **−50%** | The holder lost nothing. But a series that keeps the \$200 next to the \$100 hands every downstream rule a one-day −50% move, and each of them reacts as designed: - A 10% [stop loss](/docs/strategies/stop-loss) fires and sells a position that never lost money — and the strategy's history now contains a trade that would never have happened. - The [max drawdown](/docs/analysis/max-drawdown) records a −50% peak-to-trough fall that did not occur, making the strategy look far riskier than it was. - A momentum or trend rule ranks the stock at the bottom of the [universe](/docs/getting-started/universe) and rotates out of it. Correcting the data fixes all three at once, which is the point: the errors here are not in the rules. Reverse splits do the same thing in the other direction, and are worse, because a fabricated one-day gain attracts no suspicion at all. {/* VISUAL: chart — one instrument's price series drawn twice, unadjusted and split-adjusted, with the phantom −50% day marked on the unadjusted line — tracked in VISUAL_BACKLOG */} ## What does Fincanva do about data quality? - Backtests run on market and fundamental data sourced from **multiple established data providers**, updated daily, and a run goes to the latest available market close rather than to today's calendar date. - Corporate actions such as splits and dividends are reflected in the price history a backtest reads, so a split does not appear as a price fall and dividends are not silently dropped from returns. - Instruments that were delisted stay in the catalogue and remain searchable, so a strategy can include names that later failed instead of them disappearing from the [universe](/docs/getting-started/universe). - Each [instrument](/docs/getting-started/instrument) carries a permanent identifier separate from its ticker symbol, so a price history stays joined when the symbol changes rather than splitting into two unrelated series — see [permanent instrument identifier](/docs/data-methodology/permanent-instrument-identifier). - Coverage varies by instrument: an instrument's [coverage window](/docs/data-methodology/coverage-window) — the span between its first and last available price dates — is the only history a backtest holding it can use, so a strategy's earliest usable date can be later than the [simulation start year](/docs/backtesting/simulation-start-year) you set. That last point is the one to check before reading a long backtest. The rest reduces data-quality bias; none of it removes the need to know what the data behind a particular run covers, and none of it prevents the two related failures where the data is fine and the *reporting* is not — see [cherry-picking bias](/docs/investing-theory/cherry-picking-bias) — or where the timing of otherwise-correct data is what leaks, which is what [walk-forward replay](/docs/investing-theory/walk-forward-replay) addresses. See [the nine biases Fincanva helps you avoid](/docs/getting-started/the-nine-biases-fincanva-helps-you-avoid) for the product behavior in context. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/investing-theory/data-snooping-bias # Data-snooping bias Data-snooping bias is the error of testing many strategy variants against the same data until one of them looks good, then reporting that winner as though it were a genuine finding. The winner's headline figures are real; what has been lost is the information needed to judge them, because the result was not one test but the best of many, and the best of many looks impressive even when nothing at all is there. Data-snooping bias is a property of the *search that produced a result*, not of the result itself — which is why it is invisible in the report and can only be assessed by knowing how many candidates were tried. **Also seen as:** Data mining bias, multiple-testing bias, p-hacking ## Why does testing many ideas produce a false winner? Testing many ideas produces a false winner because each individual test carries its own chance of looking good purely by luck, and those chances accumulate across the search. If every test has a probability $\alpha$ of appearing significant when there is no real effect, then the chance that *at least one* of $N$ independent tests does so is: $$ P(\text{at least one false positive}) = 1 - (1 - \alpha)^{N} $$ where: $\alpha$ is the false-positive rate of a single test, $N$ is the number of independent tests run, and the result is the familywise error rate — the chance the search produces at least one apparently significant result from pure noise. The consequence is that the meaning of a threshold depends on how many times it was applied. A result that would be notable as the outcome of one pre-registered test is unremarkable as the best of two hundred, and the same numbers on the page therefore support very different conclusions depending on a fact the page does not contain. In quantitative finance the standard corrections either raise the bar for significance as the number of trials grows (as the Bonferroni correction does) or test the surviving candidate on data it has never seen. ## How do 100 ideas produce one winner? Take $\alpha = 0.05$ — a one-in-twenty chance that any single test looks good on noise alone. | Ideas tested ($N$) | Chance at least one looks good by luck | |---|---| | 1 | 5% | | 14 | 51% | | 100 | 99.4% | Run 100 unrelated strategy variants and it is effectively certain — 99.4% — that at least one clears the bar for no reason at all. Report only that variant and you have a page of strong figures produced by a coin-flipping exercise. The arithmetic also shows how quickly this arrives: by the fourteenth variant the odds are already worse than even. Note what is *not* recorded anywhere in the winner's own results: the other 99 runs. A reader given only the winner cannot compute the row of this table that applies. ## How is data-snooping bias different from overfitting? Data-snooping bias and [overfitting](/docs/investing-theory/overfitting) are the same problem approached from opposite directions. Overfitting is about the *strategy* — it has enough degrees of freedom to absorb noise, so it describes one sample too precisely. Data-snooping is about the *search* — many candidates were evaluated and only the survivor is shown, so the survivor's quality partly measures the size of the search. A single hand-tuned twelve-parameter strategy is overfitted with no search at all; a one-parameter strategy picked as the best of 500 tests is data-snooped without being complex. It is also distinct from its reporting-stage neighbour: [cherry-picking bias](/docs/investing-theory/cherry-picking-bias) is quoting the favorable part of *one* result, while data-snooping is quoting the favorable *result* out of many. And it differs from [selection bias](/docs/investing-theory/selection-bias), which is about an unrepresentative sample of instruments or periods rather than a repeated search. ## What does Fincanva do about data-snooping bias? Fincanva does not prevent data-snooping, and no backtesting tool can: the app lets you run as many variants as you like, and a completed backtest carries no record of how many other variants you tried before it. Keeping track of the size of your own search is therefore left to you, and it is the only input that makes a winner interpretable. That count also has to survive [confirmation bias](/docs/investing-theory/confirmation-bias), which is the pull to remember the runs that agreed with the idea and quietly discount the rest. Two product behaviors bear on it. A backtest reports the full-period result with its [drawdowns](/docs/analysis/max-drawdown), not only the favorable stretch, so a lucky winner is at least shown in full. And the [start-date sensitivity](/docs/analysis/start-date-sensitivity) view re-runs one strategy across many entry dates and reports the spread of outcomes, which tends to expose a result that survived only one particular window. See [the nine biases Fincanva helps you avoid](/docs/getting-started/the-nine-biases-fincanva-helps-you-avoid) for the product behavior in context. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/investing-theory/look-ahead-bias # Look-ahead bias Look-ahead bias is the use of information in a historical test that was not yet available at the moment the simulated decision was made. A test that reads a company figure before its real publication date, or fills an order at a price that had not yet printed, is effectively letting the strategy see the future — and a strategy that can see the future is almost impossible to beat, so its results are flattering and cannot be repeated with real money. Look-ahead bias is a *timing* error in the data feeding the decision, not a flaw in the strategy's logic: the same rules, given only what was knowable at the time, would have produced a different and usually far worse result. **Also seen as:** Lookahead bias, information leakage, peeking ## What causes look-ahead bias in a backtest? Look-ahead bias appears whenever the date a value is *stamped with* differs from the date it *became public*, and the test uses the stamp. The recurring sources are: - **Publication lag on reported fundamentals.** A quarterly figure describes a quarter that ended weeks or months before the filing appeared. Attaching that figure to the quarter-end date lets a decision act on it before anyone could have read it. - **Restatements and revisions.** Many series are revised after first release. Using the final, revised value as though it had been known on the first-release date imports information that did not exist yet. - **Same-moment execution.** Deciding on a day's closing price and then filling at that same day's open, or using a session's high or low before it had printed, gives the fill a price the decision could not have known. Which price a fill uses is set by the [execution time](/docs/strategies/execution-time). - **Today's membership applied to yesterday.** Running a test on the [constituents of an index](/docs/data-methodology/index-lists-and-point-in-time-constituents) *as it stands now* over a period when the membership was different mixes look-ahead with [survivorship bias](/docs/investing-theory/survivorship-bias). ## What happens when earnings are used before they were published? A screen ranks companies on their latest reported earnings and rebalances on 1 February. Company A's fiscal quarter ended 31 December, but its results were only published on 20 February. A test that files the December figure under 31 December can see it on 1 February and buys on it; a test that files it under 20 February cannot see it yet and buys something else. Repeat that across every filing for ten years and the strategy has enjoyed a three-week head start on every earnings surprise — a systematic advantage no real account had. This is why a filter lag counted in **Reports Ago** rather than calendar months matters: filings, not the calendar, decide when a figure was knowable. See [lag, period, and multiplier](/docs/screeners/lag-period-and-multiplier) for how those units work. {/* VISUAL: svg-diagram — timeline contrasting a figure's information date (quarter end) with its decision date (publication), and the window where look-ahead lives — tracked in VISUAL_BACKLOG */} ## How does walk-forward replay avoid look-ahead bias? Walk-forward replay reduces look-ahead bias by moving through history one step at a time and letting each decision use only what had already happened by that step. Fincanva backtests replay your rules in chronological order and run to the latest available market close, never past it, so a decision dated in 2015 cannot draw on 2016 data. What that removes is the *computation's* opportunity to look ahead; what it cannot remove is a rule that reads a figure the market did not yet have on that date, which is why the verb here is reduce and not eliminate. See [walk-forward replay](/docs/investing-theory/walk-forward-replay) for the mechanic and [the nine biases Fincanva helps you avoid](/docs/getting-started/the-nine-biases-fincanva-helps-you-avoid) for the product behavior behind it. ## How is look-ahead bias different from the other backtest biases? Look-ahead bias is about *when* the information was available; its neighbours are about *what* you tested and *how you read the result*. [Survivorship bias](/docs/investing-theory/survivorship-bias) is a sample missing the names that did not last. [Selection bias](/docs/investing-theory/selection-bias) is a sample chosen with hindsight. [Data-snooping bias](/docs/investing-theory/data-snooping-bias) is many tests with only the winner reported. [Overfitting](/docs/investing-theory/overfitting) is a strategy shaped so tightly to past data that it captures noise. [Data-quality bias](/docs/investing-theory/data-quality-bias) is the nearest neighbour of all: a conclusion driven by the stored data itself being wrong, which is where restatements and revisions land when the corrected value is the only one you have. A test can be entirely free of look-ahead bias and still suffer every one of the others. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/investing-theory/overfitting # Overfitting Overfitting is the error of tuning a strategy so tightly to a particular stretch of past data that it captures the noise in that data rather than a durable effect. An overfitted strategy is not a strategy that was wrong about the past — it described the past extremely well, which is exactly the problem: it encoded accidents that will not recur, so it looks excellent on the history it was fitted to and performs poorly on data it has never seen. The gap between those two performances is the measurable signature of overfitting. Overfitting is an error of the *fitting step*: it lives in the strategy's own complexity, not in the sample you chose to test or the number of variants you tried before this one. **Also seen as:** Curve-fitting, curve fitting ## Why does an overfitted strategy fail out of sample? An overfitted strategy fails out of sample because every historical price series contains two components — a repeatable one and an unrepeatable one — and fitting cannot tell them apart. As you add rules, thresholds, and exceptions, the strategy gains the flexibility to describe finer and finer detail in the sample. Some of that detail is a real effect that will show up again; the rest is coincidence specific to those particular dates. Past a certain point, each extra degree of freedom buys mostly coincidence, so in-sample performance keeps improving while out-of-sample performance flattens and then deteriorates. This is the standard bias–variance trade-off applied to trading rules: a very simple rule may systematically miss part of the real effect, while a very flexible one reproduces the sample almost exactly and generalises badly. The complexity that performs best on the fitted sample is therefore almost never the complexity that performs best afterwards. ## How many parameter combinations does a search really cover? The number of distinct strategies a parameter search covers is the product of the values tried for each parameter, so it grows multiplicatively, not additively. $$ N = v_1 \times v_2 \times \cdots \times v_k $$ where: $k$ is the number of tunable parameters, $v_i$ is the number of values tried for parameter $i$, and $N$ is the number of distinct strategy variants the search covers. Four parameters with ten candidate values each is not forty tests — it is $10^4 = 10{,}000$ distinct strategies, of which the best-looking one will look very good on that sample whether or not any real effect exists. This is the mechanical link between overfitting and [data-snooping bias](/docs/investing-theory/data-snooping-bias): the more variants a search covers, the more the winner's apparent quality is explained by the size of the search. ## How can a 12-parameter strategy be perfect in sample and dead out of sample? Consider two versions of the same idea, both fitted on 2000–2012 and then run unchanged on 2013–2025. | | Rules / parameters | 2000–2012 (fitted) | 2013–2025 (unseen) | |---|---|---|---| | Simple version | 2 | +11% [CAGR](/docs/analysis/cagr), −28% max [drawdown](/docs/analysis/max-drawdown) | +9% CAGR, −31% max drawdown | | Tuned version | 12 | +19% CAGR, −14% max drawdown | +2% CAGR, −39% max drawdown | On the fitted window the tuned version is clearly the better strategy on every figure, and that is the result a single backtest would have shown. On the unseen window it collapses, while the simple version behaves roughly as it did before. The 12 parameters did not discover a better strategy; they described 2000–2012 more precisely — including the parts of it that were accidents. Note also which figure moved most: the tuned version's drawdown nearly tripled, because tuning had quietly removed the specific historical declines it was fitted to avoid rather than teaching the strategy to avoid declines in general. {/* VISUAL: svg-diagram — in-sample vs out-of-sample split chart: as rule count rises, the in-sample curve keeps improving while the out-of-sample curve peaks and then falls — tracked in VISUAL_BACKLOG */} ## What is an in-sample / out-of-sample split? An in-sample / out-of-sample split is the standard defence against overfitting: the history is divided in two, the strategy is designed and tuned on the first part only (in sample), and the second part (out of sample) is then run once, unchanged, as a test of whether the result survives on data that played no part in shaping it. The out-of-sample result is the one that carries information, because it is the only one the rules were not fitted to. Two conditions make the split meaningful. The out-of-sample period must be genuinely untouched — each time you look at it, adjust the rules, and look again, it becomes part of the fitting sample and stops being a test. And the split must be chronological rather than random, so the earlier data trains and the later data tests, which also keeps the exercise free of [look-ahead bias](/docs/investing-theory/look-ahead-bias). Repeating the split as a series of rolling train-then-test windows is [walk-forward](/docs/investing-theory/walk-forward-replay) validation, the sequential form of the same idea. ## What counts as a robust result? Robustness is about stability rather than a level: a result is described as robust when it does not depend on one exact set of parameter values, one start date, or one sample of instruments. Practically, that shows up as a broad plateau instead of a sharp peak — small changes to a threshold move the outcome slightly rather than destroying it — plus a narrow spread of outcomes across many start dates, which is what the [start-date sensitivity](/docs/analysis/start-date-sensitivity) view reports. A strategy whose result exists only at one precise parameter setting is the textbook profile of an overfitted one. One perturbation is easy to forget: a result that only survives with costs left out is carrying [cost-ignoring bias](/docs/investing-theory/cost-ignoring-bias) on top of everything else, so a robustness check is worth repeating on the net figures. Robustness is a statement about how a result behaves under perturbation, and no level of it makes a strategy safe or a future return likely. ## What does Fincanva do about overfitting? - You define the rules. Fincanva has no automatic optimizer: it does not search parameter values or tune your thresholds against history for you, so a backtest reports what your exact stated rules would have done and nothing else. - The [start-date sensitivity](/docs/analysis/start-date-sensitivity) view re-runs one strategy across many entry dates and holding windows and reports the spread, which is a direct robustness check on a single flattering run. - A backtest always runs to the latest available market close, so the most recent history is never held back automatically. A chronological in-sample / out-of-sample split is something you construct yourself from the periods you compare, primarily via the [simulation start year](/docs/backtesting/simulation-start-year). See [the nine biases Fincanva helps you avoid](/docs/getting-started/the-nine-biases-fincanva-helps-you-avoid) for the product behavior in context. ## How is overfitting different from data-snooping bias? Overfitting and [data-snooping bias](/docs/investing-theory/data-snooping-bias) are the same statistical problem seen from two ends. Overfitting describes the *strategy*: it has too many degrees of freedom for the data, so it has absorbed noise. Data-snooping describes the *search*: many candidates were tried and only the winner is being reported, so the winner's apparent quality partly reflects the number of attempts. A single strategy with twelve hand-tuned parameters can be overfitted with no search at all, and a single-parameter strategy chosen as the best of 500 tests can be data-snooped without being complex. Most real cases are both. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/investing-theory/selection-bias # Selection bias Selection bias is the error of drawing a general conclusion from a sample of instruments or periods that is not representative of the population you mean to describe — typically a small, favorable subset chosen with the benefit of hindsight. The resulting figures are arithmetically correct; they simply describe that sample rather than the strategy. Selection bias is the bias of the *sampling step*: it enters before any rule is applied, and once the sample is chosen no analysis performed on it can undo the distortion. **Also seen as:** Sample selection bias, sampling bias ## What makes a sample unrepresentative? A sample is unrepresentative when membership in it correlates with the outcome being measured, which in backtesting happens in three ways: - **Hindsight-informed instruments.** You already know which names did well over the period, and those are the names in the test. The knowledge that shaped the sample was not available at the start of the period being tested. - **Hindsight-informed periods.** The test covers a stretch of market history that suited the strategy's style, chosen because it suited it. A trend-following rule tested only across a long uninterrupted trend is a sample of one favorable regime. Choosing that stretch and then reading its result as support for the idea is where selection bias shades into [confirmation bias](/docs/investing-theory/confirmation-bias). - **Too small a sample.** A handful of instruments or a couple of years cannot distinguish a durable effect from noise, so the result is dominated by whichever few positions happened to dominate. The clearest symptom is that the conclusion does not survive a change of sample: run the same rules on a wider list of instruments, or on a different span of years, and the effect disappears. ## What goes wrong when you hand-pick the assets that happened to work? Consider a strategy tested on five instruments. You know, in 2026, that those five were among the strongest performers of the previous decade, and you chose them for that reason. The backtest reports a high return — but the return is a property of the five names, not of the rules, and the same rules applied to five names chosen without hindsight would have produced something ordinary. The test cannot tell you which of the two it measured, because it only ever saw the favorable sample. Running the identical rules over a broad [universe](/docs/getting-started/universe) instead of the five separates the two questions: if the effect holds across hundreds of names it is at least a property of the rules, and if it collapses it was a property of the five. ## What does Fincanva do about selection bias? Fincanva lets a strategy draw from a broad [universe](/docs/getting-started/universe) narrowed by explicit filters rather than a hand-typed list of names, and lets a backtest run from an early [simulation start year](/docs/backtesting/simulation-start-year) across many market regimes. The [start-date sensitivity](/docs/analysis/start-date-sensitivity) view re-runs the same strategy across many entry dates and holding windows, which reveals directly whether a result depended on one favorable starting point. None of this chooses a sample for you. A universe you narrow down to the instruments you already know worked, or a start year you moved because the earlier years looked bad, carries selection bias whatever the tool does. See [the nine biases Fincanva helps you avoid](/docs/getting-started/the-nine-biases-fincanva-helps-you-avoid) for the product behavior in context. ## How is selection bias different from survivorship bias and cherry-picking? The three biases attach to three different steps, and each one can occur without the others: | Bias | Where it enters | Who introduces it | |---|---|---| | [Survivorship bias](/docs/investing-theory/survivorship-bias) | the instrument list itself, before any choice is made — the failures are already gone | the data | | **Selection bias** | choosing which instruments or which period to *test* | the researcher, at test time | | [Cherry-picking bias](/docs/investing-theory/cherry-picking-bias) | choosing which of the results already produced to *report* | the researcher, at reporting time | Read together: survivorship bias means the losers were never on the list; selection bias means you picked the sample that suited you; cherry-picking means you ran the full test and then quoted only the good part of it. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/investing-theory/survivorship-bias # Survivorship bias Survivorship bias is the error of testing only on the instruments that survived until today, so the companies that went bankrupt, were acquired, or were delisted never appear in the test at all. Because the sample has been cleaned of its worst outcomes before the test begins, returns come out too high and risk too low — the bias is built into the *list of names*, so no amount of care in the strategy's rules removes it. It is one of the largest and most easily overlooked distortions in backtesting, precisely because a list of today's tradable instruments looks like a perfectly reasonable starting point. **Also seen as:** Survivor bias ## Why does survivorship bias make results look better than reality? Survivorship bias inflates results because failure is the one outcome that removes a name from the list. Every company that fell to zero, was taken over at a discount, or was delisted for non-compliance leaves the surviving set, while every company that merely did well stays in it. The test therefore samples from a population that was defined *by having done well enough to still exist* — a condition that could not be known in advance. Two things follow: average return is overstated, and the depth and frequency of large losses are understated, because the events that produce the very worst losses have been filtered out. The same logic applies to funds and strategies, not just single stocks: a study of the funds available today has quietly excluded every fund that closed after poor performance. ## What goes wrong in an S&P backtest on today's index members? Consider a ten-year backtest that buys "the S&P 500" but sources its instrument list from the index as it stands today. Every name in that list has, by definition, survived a decade and still met the index's inclusion criteria at the end of it. The companies that were in the index at the start and were removed after collapsing — the ones that would have produced the worst positions in the run — are simply absent. The equity curve rises more smoothly than the real index did, the maximum [drawdown](/docs/analysis/max-drawdown) is shallower than the real index's, and the strategy looks as though it beat the market when in fact it was handed a list of winners. Running the same rules on the index's membership *as it stood on each historical date* produces a materially lower result. {/* VISUAL: svg-diagram — two equity curves on one axis, one run on today's surviving names and one including the delisted names, showing the gap the bias creates — tracked in VISUAL_BACKLOG */} ## How does Fincanva's data handle delisted companies? Fincanva's market data includes [delisted](/docs/data-methodology/delisted) instruments and [point-in-time index membership](/docs/data-methodology/index-lists-and-point-in-time-constituents), so names that later failed or were removed from an index remain available to a backtest rather than disappearing from history. Each instrument is used only across the span in which it actually existed — a company that listed in 2011 and delisted in 2018 is present for those years and absent on either side — which is what makes a run measurable against the market as it stood on each historical date. The widest [universe](/docs/getting-started/universe) — "All" — therefore still contains instruments that have since delisted, and an [instrument](/docs/getting-started/instrument) that no longer trades can still appear in a historical run. Data that retains its failures does not by itself make a given test unbiased: the universe and the period you choose still decide which names the test can hold. A hand-typed list of instruments you know today, for example, reintroduces the bias regardless of what the underlying data contains. See [the nine biases Fincanva helps you avoid](/docs/getting-started/the-nine-biases-fincanva-helps-you-avoid) for the product behavior in context. ## How is survivorship bias different from selection bias? Survivorship bias and [selection bias](/docs/investing-theory/selection-bias) both produce an unrepresentative sample, but for different reasons. Survivorship bias is imposed *by the data*: the failures were already missing before you made a single choice, so it happens even to a careful researcher who picks names at random from the list in front of them. Selection bias is introduced *by the researcher*: the sample is narrowed by a hindsight-informed choice. [Cherry-picking bias](/docs/investing-theory/cherry-picking-bias) is a third, later step — choosing which of your existing results to *report*. A single test can carry all three at once. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/investing-theory/walk-forward-replay # Walk-forward replay Walk-forward replay is the way a backtest moves through history: forward one step at a time, in strict chronological order, with each simulated decision using only the information that existed on that date and never anything later. The simulation holds a position in time — a cursor — and at every step it can read the past and the present but not the future, because from the cursor's point of view the future has not happened yet. This is the structural defence against [look-ahead bias](/docs/investing-theory/look-ahead-bias): a decision dated 2015 cannot draw on 2016 data, not because a rule forbids it but because the replay has not reached 2016. **Also seen as:** Forward replay, chronological replay, point-in-time replay ## Why does replaying forward prevent look-ahead bias? Replaying forward takes look-ahead out of the computation by making future data unavailable rather than merely off-limits. The distinction matters, because look-ahead bias is almost never deliberate — it slips in when a value carrying a later date is joined to an earlier one, and a test that has the whole history in hand at once has no way to notice. Formally, the constraint is that the decision at each date is a function of that date's information only: $$ w_t = f(\mathcal{F}_t) $$ where $w_t$ is the set of target weights the strategy holds at date $t$, $f$ is the strategy's rules, and $\mathcal{F}_t$ is the information available up to and including $t$ — prices already printed, filings already published, indicators computable from both. A test whose decision at $t$ uses any part of $\mathcal{F}_{t+k}$ for $k > 0$ has look-ahead bias, however small the leak. Walk-forward replay enforces the constraint by construction: at step $t$, nothing after $t$ has been read. ## What happens at each step of the replay? Each step is the same four operations, repeated for every date in the period: 1. **Advance the cursor** to the next date in the period. 2. **Read what is knowable** at that date — the prices and reported figures already available on it. 3. **Apply the rules** to that information: derive target weights, check exit conditions, decide whether this date is a [rebalance](/docs/backtesting/rebalance) date. 4. **Record the outcome** — the resulting positions, the trades, and the portfolio value that becomes one point on the equity curve. Then the cursor moves on, carrying the positions it just recorded and nothing else. Because step 2 always precedes step 3, the information a decision uses is fixed before the decision is made, and because step 4 only writes, no later date can reach back into an earlier one. ## What can the replay cursor see on one rebalance date? A strategy rebalances monthly, and the replay's cursor reaches the close of **28 February 2018**. | At that step the replay | | |---|---| | **can** read | every price printed up to and including the 28 February close; every company filing published on or before 28 February; any indicator computable from those | | **cannot** read | the 1 March price; a filing dated 20 March that describes the quarter ending 31 December; anything at all from 2019 | From that information it derives the month's target weights. The resulting rebalance trades are modelled to fill at the **Open of the first trading day after the rebalance date** — so the decision is taken on the 28 February close and the fill happens at the 1 March open, a price the decision did not know. See [execution time](/docs/strategies/execution-time) for which bar price a fill books at. The cursor then advances to 1 March and repeats. When it reaches December 2018 it still knows nothing about 2019, even though the run as a whole will continue to the present — the strategy meets each year for the first time, in order, exactly once. {/* VISUAL: animation — a replay cursor moving left to right along an equity curve, with the region to its right greyed out to show what the simulation cannot see at that step — tracked in VISUAL_BACKLOG */} ## How is walk-forward replay different from walk-forward optimization? They are different things that share a name, and confusing them is common: - **Walk-forward replay** is *how one simulation moves through time*. No parameters are chosen and nothing is fitted; the rules are fixed before the run and applied at every step. Every honest backtest is a walk-forward replay. - **Walk-forward optimization** — also called walk-forward analysis — is a *research procedure* that repeatedly fits a strategy's parameters on one window of history and then tests those parameters on the window immediately after it, rolling both windows forward. It contains replay, but it adds parameter fitting on top. The two answer different questions. A replay answers "what would these rules have done?"; walk-forward optimization answers "would parameters chosen from the past have held up in the period after?" A Fincanva backtest is the first: it replays the rules you stated and does not auto-tune or optimize your parameters against the past, so the result reflects your rules rather than a fit to the history they ran on. ## How does Fincanva handle it? - A [backtest](/docs/getting-started/backtest) replays your rules in chronological order, from the earliest year your chosen instruments allow, to the latest available market close — never into the future. - The end point follows the newest data rather than today's calendar date, and results refresh daily as new market data arrives, so the cursor's finish line moves forward as the data does. - Rebalance-driven trades are modelled to fill at the Open of the first trading day after the rebalance date, which keeps the decision date and the fill date distinct. - The rules replayed are the ones you stated: Fincanva does not tune or optimize your parameters to fit the past for you. - Screener analysis re-centres each match on its own selection date instead of the calendar — see [event-time path](/docs/screeners/event-time-path) — which is a different alignment of the same forward-only data, not an exception to it. ## What does walk-forward replay not protect you from? Walk-forward replay fixes *when* information reaches a decision. It does nothing about what you tested, how many times you tested it, or how you read the answer: | Still possible after a clean replay | Why the replay does not touch it | |---|---| | [Selection bias](/docs/investing-theory/selection-bias) | you chose the instruments and the period; the replay honours that choice faithfully | | [Cherry-picking bias](/docs/investing-theory/cherry-picking-bias) | the replay produces the full result; which part of it gets quoted happens afterwards | | [Confirmation bias](/docs/investing-theory/confirmation-bias) | the replay reports; reading is yours | | [Cost-ignoring bias](/docs/investing-theory/cost-ignoring-bias) | a correctly ordered replay of a cost-free world is still cost-free | | [Data-quality bias](/docs/investing-theory/data-quality-bias) | replaying wrong numbers in the right order still gives a wrong answer | A backtest can therefore be entirely free of look-ahead bias and still be misleading, which is why the replay is a floor rather than a guarantee. See [how a backtest works in Fincanva](/docs/backtesting/how-backtesting-works) for the run in more detail and [the nine biases Fincanva helps you avoid](/docs/getting-started/the-nine-biases-fincanva-helps-you-avoid) for the product behavior in context. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/data-methodology/what-data-your-backtests-run-on # What data your backtests run on Every backtest in Fincanva reads one shared market-data catalogue: daily price history for the [instruments](/docs/getting-started/instrument) a strategy can hold, plus reference-only series it can measure but never buy. The catalogue is maintained so that a run reads history **as it actually stood** — companies that later disappeared are still in it, and index membership is recorded per date rather than as it looks today. That property, not the size of the catalogue, is what makes a backtest result worth reading. ## What is in the catalogue a backtest reads Three things, and the difference between them decides what a strategy can do with each. {/* VISUAL: svg-diagram — the catalogue split three ways (tradable instruments · reference-only instruments · special data series) and which of them a strategy can hold — tracked in VISUAL_BACKLOG */} - **Tradable instruments** — the ones a strategy can actually hold, spanning several asset classes. Each carries a [permanent identifier](/docs/data-methodology/permanent-instrument-identifier) and a [coverage window](/docs/data-methodology/coverage-window): the first and last dates for which it has prices. - **Reference-only instruments** — indices and macro series that exist for measurement, not ownership. They carry the **Not tradable** badge in instrument search, and the pickers that decide what a strategy *holds* are restricted to tradable ones, so a reference series cannot become a position by accident. See [Tradable and Not tradable](/docs/data-methodology/tradable-and-not-tradable). - **Special data series** — market-wide references kept beside instrument prices, such as interest rates, inflation and valuation indicators. See [special data series](/docs/data-methodology/special-data-series). The catalogue is refreshed daily, and a backtest ends at the latest available market close rather than at today's calendar date — so the data, not the clock, closes a run. See [data freshness and frontier](/docs/backtesting/data-freshness-and-frontier). ## Why does the catalogue keep companies that no longer trade? Because dropping them would quietly rig every backtest in your favour. An instrument that stopped trading — acquired, taken private, or failed — stays in the catalogue with the history it had, and stays usable for the period it did trade. It carries the **Delisted** badge in instrument search. A catalogue that kept only today's survivors would let a strategy be tested exclusively on names that made it, which is [survivorship bias](/docs/getting-started/the-nine-biases-fincanva-helps-you-avoid#how-does-fincanva-handle-survivorship-bias) — the single most flattering error a backtest can contain. Keeping delisted names is what removes it. [Delisted](/docs/data-methodology/delisted) covers the term itself. ## Why an instrument keeps its history when its ticker changes Because the catalogue identifies an instrument by a [permanent identifier](/docs/data-methodology/permanent-instrument-identifier) rather than by its ticker. Tickers get reassigned and renamed; an identity that changed with them would split one company's price history into two unrelated fragments, or silently join two different companies under one symbol. Lists and index membership are recorded against that identifier too, so a member that renamed mid-membership stays one continuous entry. You never type this identifier, but you can see its absence: a strategy that references an instrument the library cannot resolve fails with "Referenced instruments do not exist in the platform data library". Add the instrument again from the search field in **Asset selection** so the strategy points at an entry that exists. ## What does the catalogue know about index membership? It knows who was in an index **on each past date**, not just who is in it now. Membership is stored per index as a joined/left history, so a run can read the index as it stood at the time rather than as it stands today — the same reason delisted names are kept, applied to lists instead of instruments. In the app this reaches you as one of the universe filters rather than as a data screen: alongside **Asset type**, **Country**, **Exchange**, **Sector** and **Currency**, the **Index** filter is hinted "Index membership". [Index lists and point-in-time constituents](/docs/data-methodology/index-lists-and-point-in-time-constituents) covers what that record contains. ## Limits and edge cases - **Nothing in the app shows you an instrument's coverage window.** There is no first-price-date column, and Fincanva does not move your simulation start year forward to match a short history — so a run can span two decades while one of its instruments only existed for the last three years. This matters enough to read before trusting a long-history number: [coverage window](/docs/data-methodology/coverage-window). - **Instruments from exchanges with different holidays share one date axis.** How they are placed onto it is covered in [market-day and trading-calendar alignment](/docs/data-methodology/market-day-and-trading-calendar-alignment). - **Your plan sets how far back a run may start** — Free, Starter and Advanced each have an earliest start year, Ultimate and Professional reach every year there is data for — while the per-instrument data level the catalogue records is not applied yet. See [data-tier gating](/docs/data-methodology/data-tier-gating). - **[SymbolsLists](/docs/data-methodology/symbolslist) ship with the market data and are not yours to create or edit**, and unlike index lists they record membership as it stands now, with no joined/left history. ## Related To choose which of these instruments a strategy holds, see [choosing the instruments your strategy holds](/docs/strategies/choosing-the-instruments-your-strategy-holds); for what a run does with them, see [how backtesting works](/docs/backtesting/how-backtesting-works). A catalogue free of survivorship bias makes a backtest honest, not predictive — Fincanva does not tell you what to hold, see [Is this financial advice?](/docs/investing-theory/is-this-financial-advice#is-this-financial-advice). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/data-methodology/what-fincanva-s-data-coverage-figures-count # What Fincanva's data coverage figures count Fincanva's coverage figures — how many instruments, on how many exchanges, from how many countries, reaching how far back — are measurements of its market-data catalogue, each taken at a point in time, and each counts one specific thing. They count the **investable** universe: the stocks, ETPs and crypto a strategy can hold, delisted ones included. Reference series that can be measured but not held are counted separately or not at all. This page says what each figure includes and excludes, and states how far back the history reaches for the asset-class index series, stocks and ETPs; it does not repeat the counts, because they move as the catalogue does. ## Which instruments do the coverage figures count? The instrument count covers the three [asset types](/docs/getting-started/asset-type) a strategy can hold — **Stocks**, **ETPs** and **Crypto** — and nothing else. Two choices decide what that means: - **Delisted instruments are counted.** A company that stopped trading stays in the catalogue with the history it had, and a backtest can hold it for the period it traded, so it belongs in the universe a backtest runs on. Leaving it out would describe a survivors-only catalogue, which is exactly the bias the catalogue is kept to avoid — see [delisted](/docs/data-methodology/delisted). - **Reference series are not counted.** Indices, macro indicators, long-run asset-class return series and currency series are in the catalogue to measure against or to feed a simulation, not to be held, so they are outside the investable universe the figure describes. See [Tradable and Not tradable](/docs/data-methodology/tradable-and-not-tradable) and [special data series](/docs/data-methodology/special-data-series). ## What counts as an exchange? An exchange, in the coverage figure, is a **trading venue on which at least one investable instrument is listed**. The rule that decides it is whether an instrument trades on a venue at all: - **Crypto and macro series trade on no venue.** The data still gives them an exchange label so every record has one, but those labels mark the absence of a venue, and they are not counted. - **The OTC market is counted.** Over-the-counter instruments do trade on a venue, even though OTC is a market rather than an exchange in the strictest sense. The rule is "trades on a venue", and OTC meets it, so it is one of the exchanges the figure counts. The screener's **Exchange** filter shows fewer options than the exchanges counted, because it groups every European venue into a single **EU listed** option — see [universe facets](/docs/screeners/universe-facets). ## What counts as a country? A country, in the coverage figure, is the **country an investable instrument originates in**. Crypto belongs to no country: the data gives it a global origin instead, and that is not counted as a country. The countries counted are the United States and a group of European countries. ## How far back does the data reach? How far back the data reaches depends on what you are looking at: the asset-class index series start in 1793, stocks in 1962 and ETPs in 1978, and each instrument's own history starts at its first price in the data. Three distinctions decide how to read any depth figure: - **Each instrument's history starts at its first price in the data.** That is its listing date or the start of the data, whichever is later: an instrument listed before the data begins starts where the data starts, and one listed later has history only from its own listing. A figure for the depth of the catalogue is the start of its deepest histories. The app does not show that first date for an instrument, which matters for a long backtest — see [coverage window](/docs/data-methodology/coverage-window). - **The asset types start at different points.** Stocks, ETPs and crypto each have their own earliest date, and a figure stated for one type is not true of the others. - **Reference series reach much further back than any tradable instrument.** A long index or asset-class history is the history of a series you can measure against, not of a stock or ETP you can hold, so its depth never describes the investable universe. The depth of the data is also not the length of a backtest. A backtest runs from its [simulation start year](/docs/backtesting/simulation-start-year) to the latest market close the data holds — see [data freshness and frontier](/docs/backtesting/data-freshness-and-frontier). ## Which coverage figures does the documentation print? The documentation prints only the history floors in the section above — where the asset-class index series, stocks and ETPs start — and leaves the counts out. The floors are not typed into the page: they come from the same measurement the Fincanva website publishes, so the two always state the same years, and when that measurement is re-run and finds a different start, the page and the website change together. The counts — instruments, exchanges, countries — change with the catalogue itself: it is refreshed daily, instruments list and delist, and a count copied into a page is wrong from the day the next measurement differs. This page carries the part that does not change — what each figure counts — so that any figure you meet can be read correctly. ## Limits and edge cases - **A coverage count is not a match count.** The instrument figure covers the whole investable universe; a screener only ever considers what its universe filters leave, so no single screener reaches all of it. - **Counting an exchange says nothing about how many instruments trade there.** A venue with one listed instrument counts once, exactly like one with thousands. - **The figures describe the catalogue, not a guarantee about any one instrument.** Whether a particular instrument has prices for the dates your backtest covers is a question about that instrument's own coverage window, not about the catalogue's totals. ## Related For what the catalogue keeps and why — delisted names, dated index membership, permanent identifiers — see [what data your backtests run on](/docs/data-methodology/what-data-your-backtests-run-on). For why a survivors-only catalogue would flatter every result, see [the biases Fincanva helps avoid](/docs/getting-started/the-nine-biases-fincanva-helps-you-avoid#how-does-fincanva-handle-survivorship-bias). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/data-methodology/coverage-window # Coverage window A coverage window is the span of dates for which Fincanva has price data for a given [instrument](/docs/getting-started/instrument), running from its first available price date to its most recent one. It is the only history that instrument can contribute to a [backtest](/docs/getting-started/backtest): no strategy can read prices from before an instrument existed, however early the run starts. An ETF launched three years ago therefore has three years of coverage, even inside a run that reaches back to 2000. **Also seen as:** first price date, last price date, price history depth ## Why can one recent instrument shorten a whole backtest? Because an instrument has no prices to contribute on the dates before its coverage window begins. Nothing about the run is invalid, but only the stretch that sits inside *every* instrument's coverage window tests the full set you designed on real prices for all of them. The shortest coverage window among your instruments is therefore the real limit on any strategy that depends on all of them. This is easy to miss because Fincanva does not move your chosen [simulation start year](/docs/backtesting/simulation-start-year) forward to match a short coverage window — the year you enter is the year the run starts, so the mismatch is not announced at the moment you choose it. Metrics are still computed across the whole window you asked for, which is exactly why a long-history headline figure can belong to a strategy that could only have existed for part of it. Check the first price date of anything recent before reading a long-history result. ## How does Fincanva handle it? - Every instrument carries a first price date and a last price date; together they are its coverage window. - A backtest's end date follows the newest available market data rather than today's calendar date, so the catalogue's latest price date — not the clock — closes a run. See [data freshness and frontier](/docs/backtesting/data-freshness-and-frontier). - A [delisted](/docs/data-methodology/delisted) instrument's coverage window ends at its last traded date. The instrument stays in the catalogue and stays usable for the period it did trade. - A run only reads an instrument from its own simulation start year onward, so history deeper than the year you pick sits outside the run — the setting defaults to 2000 but reaches back further; see [simulation start year](/docs/backtesting/simulation-start-year). ## What does it look like in practice? A strategy pairs a broad US equity ETP whose prices reach back to 1993 with a thematic ETF that launched in March 2021, and the start year is set to 2000. Inside the run the equity ETP has 26 years of coverage; the thematic ETF has just over five, all of it after March 2021. Roughly four-fifths of the backtest's calendar therefore predates the second instrument's coverage window entirely, and only the stretch from 2021 onward tests the pair as designed. The headline CAGR and max [drawdown](/docs/analysis/max-drawdown) are still reported over the full window, so a reader who does not check the ETF's first price date will attribute two decades of behavior to a combination that could only have run for five years of it. Reading the coverage windows first tells you which figure you are actually looking at. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/data-methodology/data-tier-gating # Data-tier gating Data-tier gating is the rule that ties the market data a strategy can reach to the plan attached to your account: Fincanva's catalogue records, for each [instrument](/docs/getting-started/instrument), the data level required in order to use it, and your plan determines which levels are available to you. It governs what a run can *reach* — which instruments, and how much history — and is separate from what a run can *do*. The history half is applied: your plan sets the earliest year a [backtest](/docs/getting-started/backtest) may start from. The per-instrument half is not applied yet — see below. **Also seen as:** data entitlement, required data product, plan-gated data ## Why is market data gated by level at all? Because market data is licensed from data providers, and depth is the expensive part of it. Broad recent coverage costs far less to supply than decades of deep history across many exchanges, so access is tiered rather than uniform. Gating is how that difference reaches the product, and it is the reason two accounts running byte-identical strategies can be offered different earliest start years. ## What does data-tier gating control today? How far back a run may start. Your plan sets the earliest [simulation start year](/docs/backtesting/simulation-start-year) — Free, Starter and Advanced each have one, Ultimate and Professional have none — and Fincanva applies it: the starting-year picker lists no earlier year, a save asking for one is refused, and a strategy that already starts earlier after a plan change is set aside by [plan compliance](/docs/backtesting/plan-compliance) rather than moved. [What each plan includes](/docs/account-security/what-each-plan-includes#what-sets-the-backtests-starting-year) owns the details. The per-instrument side of the rule lives in the data rather than in a check you will hit: each instrument records the data level it needs, and no per-account data level is applied against it today. This page therefore describes the concept and where it currently stands — not an entitlement matrix, and not a limit you will meet. ## How does Fincanva handle it? - The catalogue records a required data level per instrument. It is a property of the data, not a badge on screen. - 2000 is the setting's default, lifted to your plan's floor where that is later; on a plan with no floor the starting-year picker reaches back to 1793. - Your plan's earliest-year floor is applied: the picker, the save and the run all hold a strategy to it, and a strategy that starts earlier is set aside, never moved to the floor for you. - A shorter reachable window changes results: the same rules measured over a shorter period produce different metrics — see [coverage window](/docs/data-methodology/coverage-window). ## What does it look like in practice? Take two accounts whose plans have different floors, one a decade later than the other. A strategy started at the later floor leaves that decade of market history — a major decline included, if one fell inside it — outside its run entirely, while the same strategy on the other plan may start ten years earlier. Every metric is computed only over the years a run actually covers, so the same rules produce a different CAGR and max [drawdown](/docs/analysis/max-drawdown) from the later start than from the earlier one. Fincanva does not shorten a run for you: a strategy set to start before its plan's floor is set aside until its start moves to the floor or later, or the plan reaches its year. Nothing about the strategy changed between the two cases. Only the data it could reach did — which is why two results that look comparable are not, unless they cover the same window. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/data-methodology/delisted # Delisted Delisted marks an instrument that no longer trades — the company failed, was acquired, or was taken private — but whose price history Fincanva keeps and still lets a strategy use. A **Delisted** badge appears on the instrument in search results and the instrument stays selectable, so a strategy can include a security that does not exist any more. Fincanva's historical data includes delisted instruments and point-in-time index membership. **Also seen as:** delisting, dead ticker ## Why does Fincanva keep delisted instruments? Because a backtest that can only pick from instruments still trading today is a backtest of the winners. Every company that went bankrupt, was bought out, or was dropped from an index vanishes from a survivors-only catalogue, and every loss it caused vanishes with it. Keeping the delisted instrument means a [backtest](/docs/getting-started/backtest) running through 2008 can hold a bank that did not come out of 2008, and record the damage where it actually happened. The distortion this guards against is called [survivorship bias](/docs/investing-theory/survivorship-bias): the results you get when history is judged only through the companies still around to be judged. Instruments leave the market for opposite reasons — some fail, others are acquired at a premium — so a survivors-only dataset does not simply shift results down or up. What it does is quietly remove the outcomes a strategy would have had to live through, which is why a backtest built on one cannot be trusted as a record of what the rules would have done. ## What does point-in-time index membership mean? Point-in-time index membership means an index's constituents are recorded as they stood on each date, not only as they stand today. For each index, Fincanva's data keeps when an instrument joined it and when it left, so reading the same index at 2010 and at 2026 returns two different lists — the earlier one containing companies later removed from the index, and leaving out companies that had not yet joined it. That recorded history is what separates an index as it really was from the index as it looks now, which is the distinction [survivorship bias](/docs/investing-theory/survivorship-bias) turns on. [Index lists and point-in-time constituents](/docs/data-methodology/index-lists-and-point-in-time-constituents) is the full account of how that membership history is kept and why it changes a backtest. ## What happens to a position when its instrument delists mid-backtest? The whole position is closed at the **close** of the last bar of that instrument's own price history, and the trade is dated on that series' own last date, with the [exit reason](/docs/strategies/exit-reason) **Price history ended**. It is a full liquidation — there is no partial unwind and no dead ticker left sitting in the portfolio — and it does **not** wait for the next [rebalance](/docs/backtesting/rebalance): the exit lands on the day the data ends, wherever that day falls in the strategy's schedule. From that date the proceeds are cash, and the strategy redeploys them under its ordinary rules. This is why a delisted holding never silently freezes at its last known value for the rest of a run. The loss, or the gain, is realized where the history actually stops. ## How does Fincanva handle it? - Delisted instruments stay in the catalogue and stay searchable and selectable; the **Delisted** badge is how you tell them apart in search results. - The badge is tinted as a caution rather than an error — it is information about the instrument, not a problem with your strategy. - Delisted is independent of [Tradable and Not tradable](/docs/data-methodology/tradable-and-not-tradable): an instrument can have been perfectly tradable for years and still be delisted now. - The whole-market [universe](/docs/getting-started/universe) includes delisted instruments, so a screener is not silently limited to today's survivors. - A delisted instrument has a last price date, and no data exists after it — its history simply ends there. ## What does it look like in practice? You backtest a US large-cap screen across 2007–2009, and in 2007 the screen picks up a large financial company that meets its rules. That company fails in 2008 and is delisted; its ticker does not exist today. Because Fincanva keeps the [instrument](/docs/getting-started/instrument) and its price history, the backtest holds it through the collapse and the loss lands in the results — the drawdown you see includes it. Now imagine the same screen run against a catalogue containing only companies still listed today. The failed bank is simply absent, so the identical rules appear to have produced a smoother, better outcome — not because the strategy was better, but because the loser had been deleted from history. That gap between the two runs is exactly what keeping delisted instruments removes. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/data-methodology/index-lists-and-point-in-time-constituents # Index lists and point-in-time constituents An index list is Fincanva's record of which [instruments](/docs/getting-started/instrument) belonged to a market index, kept as of each historical date rather than only as the index stands today. Its constituents are therefore *point-in-time*: asked who was in the S&P 500 in 2010, an index list answers with the 2010 membership, including companies that have since been acquired, removed, or delisted. A list built from today's membership answers a different question — which companies are in the index *now*, having already survived the intervening years. **Also seen as:** index constituents, index membership, point-in-time constituents ## What makes index membership point-in-time? Point-in-time membership means the membership is stored as a history rather than as a snapshot: for each index, Fincanva records when each instrument joined it and when it left. Reading that history at a date returns the members as of that date, so the same index can be resolved for 2010 and for 2026 and give two different lists. Over a decade the difference is large. Index committees add and remove names continuously — a company leaves when it is acquired, when it falls below the index's size or liquidity criteria, or when it delists after failing — so a decade-old membership list contains dozens of names absent from today's, and today's contains dozens that were not in the old one. ## Why does point-in-time membership matter for a backtest? Because a backtest that draws its instruments from *today's* index membership has been handed a list of names selected partly for having survived, which is exactly [survivorship bias](/docs/investing-theory/survivorship-bias). Point-in-time membership removes that particular shortcut: a run can hold what the index actually held on each date, including the names that later left it. Point-in-time data does not make a test unbiased on its own. The universe and the period you choose still decide what a run can hold, and a hand-typed list of names you know today reintroduces the bias regardless of what the underlying data contains. Nor does it address distortions in the data itself — see [data-quality bias](/docs/investing-theory/data-quality-bias) for those, and [survivorship bias](/docs/investing-theory/survivorship-bias) for the distortion this page is about. ## How does Fincanva handle it? - Fincanva's market data includes [delisted](/docs/data-methodology/delisted) instruments and point-in-time index membership, so names removed from an index remain available to a historical run. - Membership is recorded per index as a joined/left history, so it can be read at a past date rather than only as it stands now. - Index membership is one of the filters that narrow a [universe](/docs/getting-started/universe), alongside country, exchange, sector, and asset type. - An index and its members are different things: the members are instruments a strategy can hold, while the index itself is a reference series — see [Tradable and Not tradable](/docs/data-methodology/tradable-and-not-tradable). - Membership is recorded against [permanent instrument identifiers](/docs/data-methodology/permanent-instrument-identifier) rather than ticker symbols, so a member that renamed mid-membership stays one continuous entry. ## What does it look like in practice? Take a ten-year backtest of "the S&P 500" starting in 2016. Sourced from today's membership, the instrument list contains only companies that are in the index in 2026: every name dropped during the decade — acquired, or removed for falling below the criteria — is absent, and so are their worst stretches. Sourced from an index list, the same run holds the index's membership as it stood on each date. A company that was a member in 2016 and was removed in 2019 is held for the period it was genuinely in the index and then leaves the run, exactly as the index did. Both runs use identical rules and produce different results; the gap between them is the size of the survivorship effect for that index over that period. {/* VISUAL: svg-diagram — membership-over-time strip for one index, showing members entering and leaving across a decade against a "today's members" row — tracked in VISUAL_BACKLOG */} Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/data-methodology/market-day-and-trading-calendar-alignment # Market-day and trading-calendar alignment Market-day and trading-calendar alignment is how Fincanva places instruments that trade on different exchanges — each with its own holidays and session days — onto the single shared date axis a [backtest](/docs/getting-started/backtest) runs on. A simulation advances one date at a time and needs every holding to sit on the same timeline, but no two exchanges are open on exactly the same set of days. Alignment is what makes a strategy mixing a US-listed and an Italy-listed instrument computable at all, and it is why a multi-exchange strategy can show dates on which only part of the book had a fresh price. **Also seen as:** trading calendar, market days, exchange holidays ## Why don't two exchanges share the same trading days? Every exchange keeps its own calendar, and the differences are larger than they look. Weekends mostly coincide, but public holidays do not: US markets close for Independence Day and Thanksgiving, Italian and other continental European markets close for Ferragosto and Santo Stefano, and the UK adds its own bank holidays. Some markets also run half-days or close for local events that the others trade straight through. Over a single year this produces a dozen or more dates on which one exchange is open and another is shut. Fincanva tracks each exchange's closing days as part of its market data, so the simulation knows which dates were genuine sessions for each [instrument](/docs/getting-started/instrument) rather than reading a missing price as a data error. ## What a mixed-exchange strategy looks like on one date axis On a shared axis, each date either was or was not a session for a given instrument. In a single-exchange strategy every holding always agrees; in a mixed-exchange strategy it does not, so some dates carry a fresh observation for only part of the book. That is the source of the small oddities you can see in a multi-exchange run: a day's portfolio move can be driven entirely by whichever part of the book was actually trading, and a rebalance date placed on the shared calendar may not be a trading session for every holding. ## How does Fincanva handle it? - A backtest runs on one shared date axis, and every holding is evaluated against the same sequence of dates. - Exchange closing days are part of Fincanva's market data, so a market holiday is recognised as a closed session rather than a gap in a price series. - Rebalance dates are placed on that shared calendar, not on each instrument's own exchange calendar, so one rebalance date applies to every holding — see [rebalance](/docs/backtesting/rebalance). - Annualized figures count trading days rather than calendar days — see [annualization](/docs/analysis/annualization). - The date a run stops at is a market date rather than a calendar date, which is the same market-day-versus-calendar-day distinction one step further out — see [data freshness and frontier](/docs/backtesting/data-freshness-and-frontier). ## What does it look like in practice? A strategy holds one instrument listed on NYSE and one on Borsa Italiana. On **4 July** the US market is closed for Independence Day while Borsa Italiana trades normally: that date exists on the shared axis, but only the Italian instrument had a session on it. On **15 August** the reverse happens — Borsa Italiana is closed for Ferragosto while NYSE is open. Across a year the two exchanges disagree on roughly a dozen dates, in both directions. The consequences show up at the edges rather than in the headline numbers: a rebalance date on the shared calendar may not be a session for every holding, and a single day's move in the strategy can reflect only the half of the book that was open. A strategy built entirely on one exchange never meets any of this. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/data-methodology/permanent-instrument-identifier # Permanent instrument identifier A permanent instrument identifier is the identity Fincanva assigns to every [instrument](/docs/getting-started/instrument) in its catalogue, and unlike a ticker symbol it never changes. Ticker symbols are labels an exchange can reassign: a company rebrands and takes a new symbol, and a symbol freed by a delisting can later be given to an unrelated company. The permanent identifier is the identity underneath that label, so an instrument's price history stays one continuous series across a rename. **Also seen as:** permanent instrument ID, permanent identifier ## Why does an instrument need an identifier other than its ticker? A ticker symbol says where an instrument trades today, not which instrument it is. Three ordinary events break a ticker-based identity: - **Renames** — a company rebrands and its symbol changes, splitting one price history into two records that look unrelated. - **Reuse** — after a delisting a symbol becomes available again and can be assigned to a different company, so one symbol can cover two unrelated histories. - **Cross-listings** — the same company can trade under different symbols on different exchanges. A permanent identifier removes all three problems at once. The symbol becomes a display label that is free to change, while every price, filing, and index-membership record stays attached to the same underlying instrument. ## How does Fincanva handle it? - Every instrument in the catalogue carries a permanent identifier; the ticker you search on and read on screen is a label attached to it. - Fincanva references instruments by their permanent identifier rather than by ticker string — a strategy's benchmark instrument, for example, is stored that way, and a screener's matches come back identified the same way — see [screener execution and caching](/docs/screeners/screener-execution-and-caching). - [Delisted](/docs/data-methodology/delisted) instruments keep their permanent identifier, so their history stays reachable after trading has stopped and a [backtest](/docs/getting-started/backtest) can still hold them for the period they traded. - These identifiers are internal rather than readable codes. You never need to type or know one: you search by ticker or name, and Fincanva resolves it. ## What does it look like in practice? A company listed as **ABC** rebrands, and its shares begin trading as **XYZ**. Under a ticker-based identity this looks like two instruments — ABC with history up to the rename date, XYZ with history from it — and a ten-year backtest spanning the rename would either stop at the old symbol or start late at the new one. Because Fincanva keys the instrument by its permanent identifier, both stretches are one series on one instrument: a strategy that held it before the rename still holds it after, and the run reads a full ten years of prices instead of two truncated fragments. The same protection applies in reverse — if the freed symbol **ABC** is later assigned to a different company, that company is a separate instrument with its own permanent identifier, so the two histories never merge. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/data-methodology/special-data-series # Special data series Special data series are the market-wide reference series Fincanva keeps alongside instrument prices — interest rates, an inflation series, and broad valuation indicators — used as inputs to a simulation or as comparison series rather than as things a strategy holds. They are not [instruments](/docs/getting-started/instrument): you cannot buy an inflation rate. Six of them exist today, and each has a defined behavior when a requested date falls outside the data it covers. **Also seen as:** reference series, macro series, special symbols ## Which special data series does Fincanva keep? | Series | What it measures | Where it is used | |---|---|---| | Risk-free rate | The 3-month US Treasury Bill secondary-market rate, published by FRED as `DTB3` | The near-riskless baseline that risk-adjusted metrics subtract — see [risk-free rate](/docs/analysis/risk-free-rate) | | Margin-loan rate | A short-term reference interest rate — today the same 3-month US Treasury Bill series as the risk-free rate | The base rate that the borrowing markups sit on top of, and the rate idle cash is credited from — see [interest-rate markups](/docs/backtesting/interest-rate-markups) | | Inflation | A long-history monthly US inflation series | Inflation-adjusted figures and inflation-based comparisons | | Shiller PE | The cyclically adjusted price-to-earnings ratio of the US market: price divided by the average of the last ten years of inflation-adjusted earnings | A market-wide valuation reference | | Buffett Indicator | Total US market capitalisation divided by US GDP | A market-wide valuation reference | | Buffett Deviation | A proprietary Fincanva variant of the Buffett Indicator | A market-wide valuation reference | Two of the six are worth a note on how they are produced. The **Shiller PE** is taken exactly as its public reference series publishes it rather than recomputed, so Fincanva's value matches the widely quoted figure instead of a private recalculation. The **Buffett Indicator** is computed inside Fincanva as the standard ratio above, from market-capitalisation and GDP data. The **Buffett Deviation**'s construction is proprietary and is not published — only the existence of the series is documented here. ## What happens when a date falls outside a series? A date outside a series' coverage — before its first data point or after its last — falls back to a fixed assumed value rather than failing the run. The rule is the same for the three rate and inflation series; what differs is the value and how it enters your results. | Series | What stands in outside the series | |---|---| | Risk-free rate | A flat 2% a year for each month of the backtest window outside the series, blended into the window's period average — see [risk-free rate](/docs/analysis/risk-free-rate) | | Margin-loan rate | A fixed assumed rate on each date outside the series. Its value is not published. | | Inflation | A fixed assumed rate on each month outside the series. Its value is not published. | The fallback covers dates outside a series, not a missing series. These series are loaded before any backtest runs, and if one of them could not be loaded no backtest would run at all. You will rarely meet the start-of-series case, because the simulation start year defaults to 2000 and these series reach back decades further. The end-of-series case can occur: when a series ends before your backtest window does — because it is published less often, or later, than prices — the dates past its end use the fallback. ## How does Fincanva handle it? - Six special data series exist today: risk-free rate, margin-loan rate, inflation, Shiller PE, Buffett Indicator, and Buffett Deviation. - The risk-free rate is a live market series matched to your backtest's own dates, not a constant — see [risk-free rate](/docs/analysis/risk-free-rate). - The risk-free fallback is a flat 2% a year; the margin-loan and inflation fallbacks are fixed values that are not published. - Special data series are references rather than holdings: they are not tradable instruments a strategy buys, so they never appear as a position in a [backtest](/docs/getting-started/backtest). - They refresh alongside instrument prices, so a series' last data point moves forward as new data lands — see [data freshness and frontier](/docs/backtesting/data-freshness-and-frontier). ## What does it look like in practice? Suppose a backtest window runs 120 months and its first 12 fall before the risk-free series begins. The risk-free rate for that window is then a month-weighted blend: 2% a year for those 12 months and the series' own average for the other 108. If the series averaged 4% over its part, the window's rate is (12 × 2% + 108 × 4%) ÷ 120 = **3.8%**, and the [Sharpe ratio](/docs/analysis/sharpe-ratio) for that window subtracts 3.8%. Those 12 months are held to a 2% bar whatever short-term rates actually were then, and the longer the window, the smaller the share of it they can move. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/data-methodology/symbolslist # SymbolsList A SymbolsList is a named group of [instruments](/docs/getting-started/instrument) that Fincanva's market data maintains as a single unit, so a set of tickers that belong together can be referred to by one name instead of listed one by one. The curated groups cover recurring cuts of the market — sectors, countries, currencies, industries, commodities, fixed income, real estate and a few others. A SymbolsList is a data-layer grouping rather than a control you build: the lists ship with Fincanva's market data and refresh with it. **Also seen as:** symbols list, named ticker group ## What is inside a SymbolsList? A SymbolsList holds a name and its member instruments, and nothing else — no weights, no rules, no dates. Members are referenced by their [permanent instrument identifier](/docs/data-methodology/permanent-instrument-identifier) rather than by ticker symbol, so a list keeps the same membership when one of its members is renamed. Sizes vary widely: some lists hold under ten instruments, others several dozen. Not everything in the catalogue is holdable, though — some entries are reference-only series — so see [Tradable and Not tradable](/docs/data-methodology/tradable-and-not-tradable) for that distinction. ## How is a SymbolsList different from a universe or an index list? The three are separate ideas that all describe a set of instruments. | Concept | What defines the set | Does it carry history? | |---|---|---| | SymbolsList | A curated group that ships with Fincanva's market data, referred to by name | No — membership is current only | | [Universe](/docs/getting-started/universe) | Your own filters (country, exchange, index, sector, asset type) | No — it is resolved for the run you are setting up | | [Index list](/docs/data-methodology/index-lists-and-point-in-time-constituents) | Membership of a real market index | Yes — membership is recorded as of each historical date | So a SymbolsList is the simplest of the three: a stable, named bundle of tickers with no history attached to the grouping itself. If you need to know who belonged to a group *on a past date*, that is an index list, not a SymbolsList. ## How does Fincanva handle it? - SymbolsLists ship with Fincanva's market data and refresh with it; they are not created or edited by you. - A list stores its members by their permanent instrument identifier, so a ticker rename never drops a member. - Membership is current, not point-in-time: a SymbolsList records the group as it stands, with no record of when a member joined or left. - SymbolsLists are part of the data layer and are not surfaced as a pickable control in the app today. The term is documented here because docs and Learn material use it. ## What does it look like in practice? "Sectors" is one of the shipped lists: rather than naming one instrument per sector every time a sector-by-sector comparison is needed, the group is referred to by its list name and resolves to its members. If one of those members is renamed — its ticker changes while the company continues — the list still resolves to exactly the same instruments, because membership is stored by permanent instrument identifier and not by the ticker symbol that changed. A list built by hand from ticker strings would quietly lose that member instead. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/data-methodology/tradable-and-not-tradable # Tradable and Not tradable Tradable and Not tradable say whether a strategy can actually hold an instrument. A tradable instrument can be bought and held; a **Not tradable** instrument exists only as a reference series — your rules can read its price, but no position can ever be taken in it. Fincanva labels only the exception: instrument search results carry a **Not tradable** badge on reference-only instruments and no badge at all on tradable ones, so the absence of a badge is what "tradable" looks like. **Also seen as:** reference-only, non-tradable ## Where does the Not tradable badge appear? The **Not tradable** badge appears in instrument search results, next to the instrument's exchange code — and only on the surfaces where reference-only instruments can be searched at all. Fincanva searches two separate slices of the catalogue depending on what you are choosing: - **Choosing what a strategy holds.** The pickers for a strategy's instruments and for a benchmark search only tradable instruments, so a Not tradable instrument never appears there in the first place. - **Choosing a series for a risk condition.** That picker searches the reference slice, which is where indices and macro series live. This is the surface where you actually see the badge. A separate **Delisted** badge marks an instrument that no longer trades. The two are independent: [Delisted](/docs/data-methodology/delisted) is about a history that has ended, Not tradable is about never having been holdable. ## Why can't you buy an index? An index is a calculated number, not a security — nobody issues shares in the S&P 500, so there is nothing for a strategy to hold. What you can buy is a fund that tracks the index: an ETF whose price follows it. That fund is a separate, tradable [instrument](/docs/getting-started/instrument) with its own ticker, its own costs, and its own small difference from the index it tracks. That is why the index itself is Not tradable while the fund tracking it carries no badge. ## How does Fincanva handle it? - Tradable is the unbadged default; only Not tradable is labelled, because it is the exception. - Instrument pickers that decide what a strategy holds are restricted to tradable instruments, so a reference-only instrument cannot be added to a portfolio by accident. - The reference slice used by risk conditions contains both kinds: ordinary tradable instruments appear there unbadged, and indices and macro series appear with the **Not tradable** badge. - Tradable status is a property of the instrument itself — independent of whether it still trades today (that is Delisted), of its [asset subtype](/docs/screeners/asset-subtypes), and of which [universe](/docs/getting-started/universe) you are screening. The facets you set are how you narrow that same catalogue — see [universe facets](/docs/screeners/universe-facets). ## What does it look like in practice? You want a strategy driven by the S&P 500. Searching the index itself in a risk-condition series picker finds it with a **Not tradable** badge: the strategy can compare the index's level against its own moving average to decide when to de-risk, but it can never hold it. To take that exposure instead, you search the instrument picker for an ETF that tracks the index — an ordinary tradable instrument, no badge — and add that. Same market, two entirely different roles: one is a reference series your rules read, the other is a position your strategy takes. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/changelog # Every instrument shows its own logo **2026-09-19** · data-methodology · 2026.09 Every instrument now shows its own logo wherever Fincanva has one, instead of one picture shared by every instrument on the same exchange. Where an instrument has no logo of its own, it falls back to the flag of its recorded origin, exactly as before — see [instrument logo](/docs/getting-started/instrument-logo) for the full fallback rule. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/account-security/how-cookie-consent-works-on-fincanva # How cookie consent works on Fincanva Fincanva asks for your consent to optional cookies and similar tracking technologies through a banner run by Iubenda, a consent-management service, and it asks the same way everywhere: every optional purpose starts switched off, for every visitor in every country, so no optional cookie is set until you switch its purpose on. You can accept all purposes, reject them, or choose one purpose at a time — and change or withdraw that choice whenever you like, from **Cookie preferences** in the website footer or **Manage cookie preferences** in the app's security settings. ## Before you start No prerequisites. The banner appears on its own, on the website and in the app, until you answer it. Changing your answer later from the website footer needs no account; the app's route needs you to be signed in. ## Steps 1. When the banner appears, accept all purposes, reject them, or open the preferences to decide purpose by purpose. 2. In the preferences, switch each optional purpose — **Functionality**, **Experience**, **Measurement**, **Marketing** — on or off. **Necessary** stays on. 3. To change your answer later, open **Cookie preferences** in the website footer, or **Manage cookie preferences** under **Settings** → **Security** in the app — see [How do I change or withdraw my cookie consent?](#how-do-i-change-or-withdraw-my-cookie-consent). ## What you should see The banner goes away once you have answered it, and only the purposes you switched on set cookies. Your answer is stored in the browser you gave it in, so the banner comes back in a different browser or device, in a private window, after you clear your cookies, or when Fincanva updates its [Cookie Policy](/cookie-policy). ## What does the cookie banner ask? The cookie banner asks which purposes you allow Fincanva to use cookies and similar technologies for. It lists the purposes and offers three answers: accept, reject, or open the preferences and decide purpose by purpose. The banner has no close button, so it stays until you give one of those answers. ## What are the five cookie purposes? The banner groups every optional cookie under one of five purposes, named in the banner as follows: | Purpose | What it covers | Can you switch it off? | |---|---|---| | **Necessary** | What the website and the app need in order to work at all | No — always on | | **Functionality** | Basic interactions and features | Yes | | **Experience** | Improvements to how pages look and behave | Yes | | **Measurement** | Measuring traffic and how the site is used | Yes | | **Marketing** | Advertising, and measuring whether advertising works | Yes | **Necessary** is shown already ticked and cannot be unticked, because nothing in it is optional. The other four are independent: allowing **Measurement** does not allow **Marketing**, and the reverse. ## Are optional cookies on before I choose? No. Every purpose except **Necessary** starts switched off and stays off until you switch it on, so no optional cookie is set before you choose. That default is the same for every visitor, wherever they are: Fincanva applies the strictest standard — opt-in — to everyone, rather than a different rule per country. One thing does run before you choose: Google's tag loads for every visitor in a cookieless mode. Until you allow **Measurement** or **Marketing**, it sets no cookies, and the pings it sends Google carry none. The one thing geography changes is which extra controls you see. A visitor covered by US state privacy law also gets a sale-and-sharing opt-out and a notice at the point of sign-up, described under [Your Privacy Choices and Notice at Collection](/docs/account-security/your-privacy-choices-and-notice-at-collection). The consent rules themselves do not change. ## How do I change or withdraw my cookie consent? Reopen your cookie preferences and change your answer — withdrawing is as quick as giving consent was. Two places open them: - **On the website**, including every page of these docs: **Cookie preferences**, in the **Company** column of the footer. For a visitor covered by US state privacy law, the same link reads "Your Privacy Choices" instead. - **In the app**: open **Settings**, then **Security**, and press **Manage cookie preferences** in the **Cookie consent** section. It is there for every signed-in user, in every country. Either one opens your cookie preferences, where you can switch any optional purpose on or off. ## Will Fincanva ask me again? Yes. Fincanva's banner is set to ask for your consent again when Fincanva updates its [Cookie Policy](/cookie-policy). And because your choice is stored in the browser you made it in, a different browser, a different device, a private window, or clearing your cookies starts you from the banner again. Cookie consent is separate from accepting the Terms: answering the banner does not accept the Terms, and accepting the Terms does not answer the banner — see [why Fincanva asks you to accept the Terms](/docs/account-security/why-fincanva-asks-you-to-accept-the-terms). ## Where do I read which cookies Fincanva uses? In the [Cookie Policy](/cookie-policy), on Fincanva's website. It is the full document behind the banner; this page explains how the banner and your choices work, not the individual cookies. ## Common problems ### "We could not open your cookie preferences. Please reload the page and try again." The app could not reach the consent service that shows your preferences. The usual cause is a content or ad blocker in your browser that stops that service from loading: allow Fincanva in the blocker, reload the page, and press **Manage cookie preferences** again. If nothing is blocking it, reloading the page is usually enough. ### The banner no longer appears You have already answered it, and your choice is stored in this browser. To change it, use **Cookie preferences** in the website footer or **Manage cookie preferences** in the app instead of waiting for the banner. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/account-security/how-to-manage-your-account-security-settings # How to manage your account security settings Everything that protects your Fincanva account lives on one page: open **Settings**, then **Security**. From top to bottom it holds your sign-in methods under **Access** (password, two-factor authentication, and [passkeys](/docs/account-security/passkeys)), **Connected accounts**, **Active sessions** — the list of signed-in browsers, explained under [active sessions](/docs/account-security/active-sessions) — **Cookie consent**, a **Privacy** section shown only to visitors covered by US state privacy law, and **Delete account**. Each section below says what you can do there and links the page that explains it in full. ## Before you start You need to be signed in. Changing your password asks for your current one, and turning two-factor authentication on or off asks you to confirm it's you first — with your password, or by an emailed link if your account has none. ## Steps 1. Open **Settings**, then **Security**. 2. Go to the section for what you want to change — each one is described below, in the order the page shows it. ## What you should see The **Security** page, with its sections from top to bottom: **Access**, **Connected accounts**, **Active sessions**, **Cookie consent**, **Privacy** (only for a visitor covered by US state privacy law), and **Delete account**. ## Where do I change my password? Under **Access**, on the **Password** row: **Change password** asks for your **Current password** and the new one twice. An account that has never had a password — whether it was created with Google or with an emailed link or code — shows "You signed in with Google. We'll email you a link to set a password." with a **Send reset link** button instead; the sentence names Google even when you signed up by email. Open the emailed link and choose a password. What a password must contain, and how resets and emailed sign-in links work, is on [passwordless sign-in](/docs/account-security/passwordless-sign-in). Changing your password also signs out every other browser signed in to your account — see [active sessions](/docs/account-security/active-sessions). ## Where do I turn on two-factor authentication? Under **Access**, on the **Two-factor authentication** row: **Enable 2FA** starts a three-step setup that pairs an authenticator app and hands you your backup codes. Once it is on, the same row offers **Generate new backup codes** and **Disable 2FA**. How the second step works at sign-in, and what to do if you lose your phone: [two-factor authentication](/docs/account-security/two-factor-authentication). ## How do I disconnect my Google account? In **Connected accounts**, press **Disconnect** on the **Google** row. With no Google account linked, the section reads "You haven't connected any external accounts." Disconnecting is refused when Google is the only sign-in method linked to your account — see ["You can't unlink your last account"](#you-cant-unlink-your-last-account) below. Signing in with Google in the first place is covered under [passwordless sign-in](/docs/account-security/passwordless-sign-in). ## Where do I change my cookie consent? In **Cookie consent**, press **Manage cookie preferences**. It opens your cookie preferences, where you can switch any optional purpose on or off, and it is there for every signed-in user in every country. What each purpose covers: [how cookie consent works](/docs/account-security/how-cookie-consent-works-on-fincanva). ## How do I delete my account? In **Delete account**, at the bottom of the page. Deletion is scheduled 14 days ahead rather than immediate, and during that window you can cancel it with **Keep my account** — signing back in alone does not cancel it. What is deleted, what is anonymized, and how to cancel: [account deletion](/docs/account-security/account-deletion). ## Common problems ### "You can't unlink your last account" You pressed **Disconnect** on the **Google** row while Google is the only sign-in method linked to your account. Set a password first, on the **Password** row under **Access**, then press **Disconnect** again. ### Why is there no Privacy section on my Security page? The **Privacy** section appears only for a visitor covered by US state privacy law, and holds the "Your Privacy Choices" opt-out that law grants. Anyone else never sees it — not even an empty heading. Who sees it and why: [Your Privacy Choices and Notice at Collection](/docs/account-security/your-privacy-choices-and-notice-at-collection). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/account-security/how-to-read-your-plan # How to read your plan Your plan is shown in two places — the account menu and profile header carry a short **Upgrade plan** link, and **Settings → Billing** carries the full status: which plan, which billing interval, and what state your subscription is in right now. ## Before you start No prerequisites. Settings → Billing is available to every account, including one with no active subscription. ## What does the billing card show? Your plan's name (Starter, Advanced or Ultimate — a Free account reads **Free**, and a Professional subscriber reads **Custom**, since Professional has no entry in Fincanva's own price catalogue), the **Billing interval** you pay on (Monthly, Quarterly or Yearly), and one status line that names exactly where your subscription stands: | Status | What it means | |---|---| | Trial | Running on the 30-day trial; the first charge has not happened yet. See [the 30-day trial](/docs/account-security/the-30-day-trial). | | `Renews on {date}` | Active and will renew automatically at the date shown. | | Payment failed | A renewal payment was declined; you keep your plan while it retries. See [what happens if a payment fails](/docs/account-security/what-happens-if-a-payment-fails). | | Payment pending | A first payment has not been collected yet; some methods take a few days to clear. | | `Ends on {date}` | Cancelled: your plan stays active until that date, then stops. Nothing is charged again. | | Change queued | A plan switch is scheduled and will take effect at the date shown. | | `Your {plan} plan ended` | The subscription is over and paid access has stopped; everything you built is still there. The card itself then reads Free — see [what the plan card shows once the subscription has ended](/docs/account-security/what-happens-if-a-payment-fails#what-does-the-plan-card-show-once-the-subscription-has-ended). | ## Steps to cancel your plan 1. Open **Settings** → **Billing**. 2. Select **Cancel plan** on the plan card. 3. Confirm in the dialog: `Cancel your plan? Your subscription will end on {date}. You will keep access until then.` Your plan stays active until that date; nothing is charged again after you confirm. Cancelling does not delete anything you built — see [plan compliance](/docs/backtesting/plan-compliance) for exactly what happens to a strategy that ends up beyond your (now lower) plan. ## What you should see The status line reads `Ends on {date}`, and a **Restore plan** button replaces **Cancel plan**. A cancellation toast confirms it in one line: `Access until {date}.` ## Steps to undo a cancellation 1. Open **Settings** → **Billing**. 2. Select **Restore plan** on the plan card. 3. Confirm: `Restore your plan? Your subscription will continue and renew on {date}.` This is available for as long as your access has not yet ended. Once the status line reads `Ends on {date}` and that date has passed, there is nothing left to restore — subscribing again starts a fresh subscription instead. ## What's the difference between "Upgrade now" and "Switch at renewal"? Two different moments a plan change can take effect, offered side by side whenever a paying subscriber chooses a different plan: **Upgrade now** changes it immediately, prorated against what you have already paid this period; **Switch at renewal** queues the change for your next billing date instead, so today's plan runs out its paid period first. A queued switch shows as **Change queued** on the status line until it lands, and can itself be cancelled with **Cancel scheduled change** before then, which leaves you on your current plan. During a trial, the **Change plan** dialog offers neither: it moves the trial itself, to Starter, Advanced or Ultimate on any billing interval, as often as you like. Each move takes effect immediately, charges nothing, and does not change the trial's end date. With no card on file the dialog is titled `Which plan do you want to try?` and each other plan carries `Try {plan}`; with a card on file it is titled `Change plan` and each other plan carries `Switch to {plan}`, with `Starts now. Still free until {date}.` What each version says in full is in [the 30-day trial](/docs/account-security/the-30-day-trial#how-do-i-change-the-plan-of-my-trial). ## Is the "Upgrade plan" link tied to a specific plan? No — this is a known limitation, not a recommendation. The **Upgrade plan** link in the account menu and profile header opens the same `/settings/billing` page for every account and is shown identically on every plan today, including plans it would not make sense to upgrade from further; the account menu also carries an **Upgrade plan** entry tagged `Coming soon` beside it. It does not point at any one level above yours, and its presence is not Fincanva suggesting a particular next plan. ## Where are my billing details and active sessions? **Billing details** — the name, address and VAT/tax ID that appear on your invoices — is its own section on the same **Settings → Billing** page, beside the plan card. **Active sessions** is a different page entirely: it lives under **Settings → Security**, and lists the devices signed in to your account rather than anything about your plan. ## Can I cancel anytime? Yes. There is no minimum term and no cancellation fee on any plan: **Cancel plan** is always available on the billing card, takes effect at the end of your current billing period, and can itself be undone with **Restore plan** for as long as that period has not yet ended. Fincanva does not tell you which plan to be on, and this page is not a recommendation to subscribe — see [Is this financial advice?](/docs/investing-theory/is-this-financial-advice#is-this-financial-advice). ## Common problems ### "To change plan during your trial, add a payment method first." This appears when a plan switch is queued for the end of a trial with no payment method on file (toast: `Add a payment method to change plan`), and nothing about your subscription changes. It is not the way to change plan during a trial: the trial's **Change plan** dialog does not queue anything, it moves the trial immediately, with or without a card — see [how do I change the plan of my trial?](/docs/account-security/the-30-day-trial#how-do-i-change-the-plan-of-my-trial). To stay on a plan after the trial ends, add a card. ### There is no Restore plan button Your access has already ended: once the `Ends on {date}` date has passed there is nothing left to restore, and subscribing again starts a fresh subscription. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/account-security/the-30-day-trial # The 30-day trial Every Fincanva account gets a 30-day trial of a paid plan, once, and it starts by itself: the first time a new account opens the app, after its email is confirmed, it is already on the trial — no checkout, no card. The trial runs on Advanced, or on the plan you chose on the website's pricing page before signing up; you can move it to another plan as often as you like, and on day 31 you go back to Free and pay nothing, unless you have added a card. ## How does the trial work? The trial starts by itself the first time your account opens the app, once its email is confirmed: there is no "start the trial" step and no checkout to go through, and nothing asks for a card. It lasts 30 days in total, from that day. It applies once per account — an account that has already held a subscription does not get a second trial. A checkout that never went through is not "having held a subscription": see [my first checkout didn't go through — do I still get the trial?](#my-first-checkout-didnt-go-through-do-i-still-get-the-trial) below. Checkout is where you **buy** a plan, not where a trial begins. ## Which plan does the trial start on? The trial starts on **Advanced** by default. If you chose Starter, Advanced or Ultimate on the website's pricing page before signing up, it starts on that plan instead. Either way it is only the starting point: you can [move the trial to another plan](#how-do-i-change-the-plan-of-my-trial) at any time during the 30 days. ## What does the trial include? The plan the trial is on, at that plan's own limits, from day 1 — there is no separate trial-only level. A trial on Starter runs at Starter's limits, a trial on Advanced at Advanced's, a trial on Ultimate at Ultimate's; the figures for each are in [what each plan includes](/docs/account-security/what-each-plan-includes). The [plan level](/docs/account-security/plan-level) named on the billing card is that same plan, and it is the one being enforced. Move the trial to another plan and that plan's limits apply from the moment you move it. ## How do I change the plan of my trial? Open **Settings → Billing** and select **Change plan**: during a trial, that dialog moves the trial itself. You can move it to Starter, Advanced or Ultimate, on any billing interval, as often as you like. Each move takes effect immediately, charges nothing, and does not change the trial's end date — the trial is 30 days in total, whichever plans it spends them on. **With no card on file**, the dialog is titled `Which plan do you want to try?` and reads `Change whenever you like, no card needed. The trial still ends on {date}: after that you stay on Free, unless you add a card.` The plan you are trying now is marked `On trial now`, and every other plan carries `Try {plan}`. At the foot it asks `Want to stay on {plan} after {date}?`, with the button `Add a card`. **With a card on file**, the dialog is titled `Change plan` and reads `It's free until {date}. From that day we charge the plan you choose here.` Every other plan carries `Switch to {plan}`, with the line `Starts now. Still free until {date}.` **Upgrade now** and **Switch at renewal** are what a paying subscriber sees in that dialog — see [how to read your plan](/docs/account-security/how-to-read-your-plan#whats-the-difference-between-upgrade-now-and-switch-at-renewal). Inside a trial, the dialog moves the trial instead. ## What do I see when the trial starts? **A new account** is greeted on Home by a panel that shows once: `Welcome: you have 30 days of {plan}, free`, then `Your trial runs until {date}.` and `No card: at the end you pay nothing and go back to Free, unless you choose a plan.` Its button is `Create your first strategy`, and the link `Rather try another plan?` opens the dialog that [moves the trial](#how-do-i-change-the-plan-of-my-trial). **An account that existed before and never had a subscription** gets the same 30-day trial, once, the next time it opens the app, announced by a one-time dialog: `We've turned on 30 days of {plan} for you`, then `Free until {date}, no card needed. At the end you go back to Free, unless you choose a plan.`, followed by what that plan gives you. Its buttons are `Start` and `Choose another plan`. ## Where do I see how many days of the trial are left? In the plan tile in the sidebar. During the trial it names the plan as `{plan} · trial`, in lime — the mark every plan your account holds wears, trial or paid — and on the right it shows the days left: `{n} days left`, and `1 day left` on the last day. More on the tile itself is in [plan compliance](/docs/backtesting/plan-compliance#where-do-you-see-how-much-of-your-plan-you-are-using). ## Will I be reminded before the trial ends? Yes, when no card is on file: Fincanva reminds you 7 days and 1 day before the trial ends. In the app, a one-time dialog reads `Your {plan} trial ends in 7 days` (or `Your {plan} trial ends tomorrow`), then `On {date} you go back to Free. Nothing is charged: there is no card on file.` It lists the strategies that will be locked on that day — kept, not deleted, and reopened as soon as you choose a plan. Its buttons are `Stay on {plan}`, which adds a card, and `See the other plans`. An email with the same content is sent at the same two moments, with the subject `Your {plan} trial ends in 7 days` or `Your {plan} trial ends tomorrow`. With a card on file there is no reminder, because nothing is lost on day 31: billing simply starts. ## When am I charged? On day 31, on the plan and billing interval the trial is on that day — **only if you have added a card.** Without one, nothing is ever charged. The trial row of the plan card on **Settings → Billing** states in advance what day 31 will do. With a payment method on file — the default one, which is where the charge goes — it reads `You’ll be billed for {plan} on {date}`, and below it `When your trial ends, the payment method on file is charged. Cancel before then and nothing is charged.` With none on file, it reads `Your trial ends on {date}`, and below it `No payment method is set to be charged, so nothing is charged and your subscription ends with the trial.` When Fincanva cannot load your payment details, or when you have already cancelled the trial, the row shows only `Your trial ends on {date}`, with no sentence about a charge. Before Fincanva has a date to show, it reads `Your trial is running`. Either way, you are never charged without a card already on file to charge. ## What happens when the trial ends? **With a card on file:** billing starts on the plan the trial is on, and nothing else changes — your account was already running at that plan, so day 31 adds a charge rather than a change of limits. If something you hold exceeds what the plan allows, that was already true during the trial, and the rule that governs any downgrade applies: nothing is deleted, and what exceeds the plan stops running until it fits again — see [plan compliance](/docs/backtesting/plan-compliance). **With no card:** nothing is charged. The subscription ends, your account is on Free, and the strategies beyond what Free allows are locked — kept, not deleted — under the same [plan compliance](/docs/backtesting/plan-compliance) rule a downgrade uses. A one-time notice says so: `Your trial has ended: you're on Free`, with how many strategies are locked, and the button `Choose a plan`. ## What happens after a trial that ended without a card? You are on Free, and choosing a plan reopens what was locked — but it is a purchase, not a second trial: the trial does not repeat, and a plan bought after it is charged from today, with a card. **Settings → Billing → Change plan** then reads `Choose a plan`, with `Your trial ended on {date}. {n} strategies are locked: they reopen as soon as you choose a plan. You pay from today; the trial doesn't repeat.` Each plan card says how many locked strategies it reopens — `Reopens {n} strategies` — and the plan you tried is marked `Tried`. That is different from an account whose **paid** plan ended: its dialog reads `Welcome back: choose a plan`, and marks the previous plan `Your previous plan`. ## Can I cancel during the trial? Yes, and nothing is charged if you do. Cancelling before the trial's end date stops the subscription before the first payment is ever attempted. With a card on file, the billing page's trial notice says so itself: "Cancel before then and nothing is charged." With none on file it says nothing about cancelling, because without a card nothing is charged on day 31 either way. See [how to read your plan](/docs/account-security/how-to-read-your-plan) for the Cancel action itself. ## Limits and edge cases ### I subscribed again and didn't get a new trial The trial applies once per account. An account that already held a subscription — even one that ended, including a trial that ended without a card — does not get another, and choosing a plan starts billing from today. That is different from a checkout that never ran a subscription at all — see [my first checkout didn't go through](#my-first-checkout-didnt-go-through-do-i-still-get-the-trial) below. ### My first checkout didn't go through — do I still get the trial? Yes. Only a subscription that actually ran counts — one that ran, even for a day, uses up the trial (see [I subscribed again and didn't get a new trial](#i-subscribed-again-and-didnt-get-a-new-trial)), but a checkout that never went through never ran one. That covers an earlier attempt that never completed, such as a declined card or a bank verification (3-D Secure) you didn't finish: nothing was charged and nothing was served, so the account still counts as never having had a subscription, and the 30-day trial starts by itself the next time you open the app, with the [one-time dialog](#what-do-i-see-when-the-trial-starts) that announces it. A trial today cannot leave you in that state, because [it starts with no checkout and no card](#how-does-the-trial-work) — there is no payment to fail. Fincanva does not tell you which plan to be on, and this page is not a recommendation to subscribe — see [Is this financial advice?](/docs/investing-theory/is-this-financial-advice#is-this-financial-advice). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/account-security/what-each-plan-includes # What each plan includes Fincanva has five plans — Free, Starter, Advanced, Ultimate and Professional — and this page lists what each includes. Every figure, tick and price below is read at build time from the same source the app enforces and the website's pricing page prints, so the three can never disagree. ## How do Fincanva's plans work? Each plan grants a fixed set of strategy, screener, Live and backtest-realism limits. The narrower scale your billing card counts — [plan level](/docs/account-security/plan-level), the three plans a subscription can actually be — is a different reading of the same order; how a strategy's own setup is checked against your plan is a separate question again, covered in [plan compliance](/docs/backtesting/plan-compliance). The tables on this page have one column per plan you can subscribe to. **Professional has no column and no published price**: it is a contact path rather than a plan on this list — reach it by writing to [hello@fincanva.com](mailto:hello@fincanva.com). ## What does the Free plan include? Free needs no card and has no time limit. What it includes is the **Free** column of every table below; a cell marked not included there is something a paid plan adds. The [30-day trial](/docs/account-security/the-30-day-trial) is the way to try a paid plan at that plan's own limits before paying for it: it starts by itself, with no card, on Advanced — or on the plan you chose on the website's pricing page before signing up — and you can move it to another plan as often as you like during the 30 days. **On every plan, Free included:** - The screener, over the whole universe — unlimited saved screeners, 10 filters each. - Backtesting on real market data, with the equity curve, portfolio metrics and monthly returns. - Profit reinvestment in every simulation. ## What do the paid plans cost? Prices are in EUR, from Fincanva's live price list. Each figure is the total charged for that period — a quarterly or yearly price is one charge for the whole period, not a monthly rate: | Plan | Monthly | Quarterly | Yearly | | --- | --- | --- | --- | | Starter | EUR 29 | EUR 78 | EUR 276 | | Advanced | EUR 79 | EUR 213 | EUR 756 | | Ultimate | EUR 149 | EUR 402 | EUR 1,428 | ## Do backtests differ by plan? Yes, in two ways: how much a strategy can hold, and how realistic its results are. **What a strategy can hold** — how many allocation methods, covariance estimators and saved strategies, how many instruments and screeners one strategy takes, and how many strategies a [Combined](/docs/getting-started/combined) may hold: | Build | Free | Starter | Advanced | Ultimate | | --- | :---: | :---: | :---: | :---: | | Allocation methods — Of the 23 methods available today | 2 | 7 | 15 | 23 | | Allocation methods for a Combined — 15 methods of the 23 available also work at the portfolio tier | Not included | Not included | 7 | 15 | | MPT (Markowitz) options — Of 2, inside MPT | Not included | Not included | Not included | 2 | | Covariance estimators — Of 8 — how a method estimates the covariance matrix | Not included | Not included | 5 | 8 | | Correlation estimators — Of 6 — how Min Correlation estimates the correlation matrix | Not included | 5 | 5 | 6 | | Saved strategies | 2 | No limit | No limit | No limit | | Instruments per strategy — Rises with every plan | 5 | 10 | 25 | 50 | | Screeners per strategy — Attach a screener to a strategy | Not included | 1 | 2 | 8 | | Combined strategies — Components inside one Combined | Not included | Not included | 5 | 10 | **Strategies inside one Combined counts the ones in use.** A strategy switched off inside a Combined does not count toward it, and whatever is switched on or off, a Combined holds at most 20 [strategies in total](/docs/getting-started/strategy-in-a-combined), on every plan. **No limit means your plan does not cap it.** Behind **No limit** on saved strategies and saved screeners there is still a technical safety maximum, which exists to stop runaway creation, and no plan level raises it because it is not a plan lever. The app is where you will meet that number: your usage panel counts against it, so the figure you see there is the safety maximum, not an allowance you bought. **How realistic the results are** — which risk rules a strategy can switch on, how far it may be leveraged, and whether trading costs and taxes are counted: | Protect | Free | Starter | Advanced | Ultimate | | --- | :---: | :---: | :---: | :---: | | Risk-on/off rules — Of 5 kinds — when a strategy switches to Risk-Off | Not included | Not included | 4 | 5 | | Leverage — Free is unlevered; every paid plan reaches the same ceiling | 1× | 3× | 3× | 3× | | Simulation realism | Not included | costs | costs + taxes | costs + taxes | Inside a strategy you can choose from 23 [allocation methods](/docs/strategies/allocation-and-allocation-method) today, and across the strategies inside a [Combined](/docs/getting-started/combined) from 15. Which of them your plan includes: | Allocation methods | Free | Starter | Advanced | Ultimate | | --- | :---: | :---: | :---: | :---: | | Equal Weights | Included | Included | Included | Included | | Fixed Allocation | Included | Included | Included | Included | | Market Cap | Not included | Included | Included | Included | | Min Correlation | Not included | Included | Included | Included | | Inverse Volatility | Not included | Included | Included | Included | | Ranking-Based | Not included | Included | Included | Included | | Floating | Not included | Included | Included | Included | | Risk Parity | Not included | Not included | Included | Included | | MPT (Markowitz) | Not included | Not included | Included | Included | | Black-Litterman | Not included | Not included | Included | Included | | Mimicking | Not included | Not included | Included | Included | | Beta Neutral | Not included | Not included | Included | Included | | HRP · Hierarchical Risk Parity | Not included | Not included | Included | Included | | HERC · Equal Risk per Group | Not included | Not included | Included | Included | | NCO · Nested Clustered Optimization | Not included | Not included | Included | Included | | Maximum Diversification | Not included | Not included | Not included | Included | | Minimum MAD | Not included | Not included | Not included | Included | | Minimum CVaR | Not included | Not included | Not included | Included | | CDaR · Conditional drawdown | Not included | Not included | Not included | Included | | EVaR · Entropic VaR | Not included | Not included | Not included | Included | | Scenario CVaR | Not included | Not included | Not included | Included | | Robust worst case | Not included | Not included | Not included | Included | | Stochastic programming | Not included | Not included | Not included | Included | Across the strategies inside a Combined the choice is narrower, and a Combined itself needs the first plan that includes one, so that is where this choice starts: | Allocation methods for a Combined | Free | Starter | Advanced | Ultimate | | --- | :---: | :---: | :---: | :---: | | Equal Weights | Not included | Not included | Included | Included | | Risk Parity | Not included | Not included | Included | Included | | Inverse Volatility | Not included | Not included | Included | Included | | Ranking-Based | Not included | Not included | Included | Included | | MPT (Markowitz) | Not included | Not included | Included | Included | | Black-Litterman | Not included | Not included | Included | Included | | Fixed Allocation | Not included | Not included | Included | Included | | Maximum Diversification | Not included | Not included | Not included | Included | | Minimum MAD | Not included | Not included | Not included | Included | | Minimum CVaR | Not included | Not included | Not included | Included | | CDaR · Conditional drawdown | Not included | Not included | Not included | Included | | EVaR · Entropic VaR | Not included | Not included | Not included | Included | | Scenario CVaR | Not included | Not included | Not included | Included | | Robust worst case | Not included | Not included | Not included | Included | | Stochastic programming | Not included | Not included | Not included | Included | A method's own theory is covered on its own page; this page states only which plan unlocks it. MPT's options follow MPT: an option is included only on a plan that includes MPT itself. | MPT (Markowitz) options | Free | Starter | Advanced | Ultimate | | --- | :---: | :---: | :---: | :---: | | Resampled | Not included | Not included | Not included | Included | | Constraints | Not included | Not included | Not included | Included | The [covariance matrix](/docs/strategies/covariance-matrix) setting — how a method that reads one estimates it — follows the method for its basic estimators: wherever a method that reads one is included, so are they. The advanced estimators have a plan of their own: | Covariance estimators | Free | Starter | Advanced | Ultimate | | --- | :---: | :---: | :---: | :---: | | Sample | Not included | Not included | Included | Included | | Ledoit-Wolf · identity | Not included | Not included | Included | Included | | Ledoit-Wolf · constant correlation | Not included | Not included | Included | Included | | Exponentially weighted moving average (EWMA) | Not included | Not included | Included | Included | | Manual shrinkage | Not included | Not included | Included | Included | | Marchenko-Pastur | Not included | Not included | Not included | Included | | Nonlinear Ledoit-Wolf | Not included | Not included | Not included | Included | | Regime-conditional (HMM) | Not included | Not included | Not included | Included | ## Which risk rules and analysis tools does each plan include? Risk rules, the settings that size a Combined's exposure, and the analysis pages each start at a plan of their own: | Risk-on/off rules | Free | Starter | Advanced | Ultimate | | --- | :---: | :---: | :---: | :---: | | Single series | Not included | Not included | Included | Included | | Double series | Not included | Not included | Included | Included | | Hidden regimes (Markov) | Not included | Not included | Included | Included | | Clustering | Not included | Not included | Included | Included | | Strategy's own performance | Not included | Not included | Not included | Included | | Leverage | Free | Starter | Advanced | Ultimate | | --- | :---: | :---: | :---: | :---: | | Leverage | 1× | 3× | 3× | 3× | | Volatility target | Not included | Not included | Included | Included | A setting that lives on a Combined is included only where a Combined is. That is why the [volatility target](/docs/backtesting/volatility-target) and an [invested portion](/docs/backtesting/invested-portion#how-does-fincanva-handle-it) above 100% — borrowed money on top of the Combined's own capital, bounded by the leverage ceiling — start at the first plan that includes a Combined, even where a cheaper plan's leverage ceiling is already above 1×. The same holds for [contribution analytics](/docs/analysis/contribution-analytics), which sits on a Combined's **Components** page. | Analyse | Free | Starter | Advanced | Ultimate | | --- | :---: | :---: | :---: | :---: | | Analysis tabs — Of the 10 tabs in Analysis | 4 | 6 | 10 | 10 | | Advanced analyses — Of 3, inside the Analysis tabs | Not included | Not included | 3 | 3 | | Screener backtest — Re-screen the market month by month over history | Included | Included | Included | Included | | Backtest history from — The earliest year a backtest may start | 2020 | 2010 | 2000 | All history | | Analysis tabs | Free | Starter | Advanced | Ultimate | | --- | :---: | :---: | :---: | :---: | | Capital Growth | Included | Included | Included | Included | | Position History | Not included | Included | Included | Included | | Performance Metrics | Included | Included | Included | Included | | Monthly Returns | Included | Included | Included | Included | | Allocation History | Not included | Not included | Included | Included | | Components | Not included | Not included | Included | Included | | Correlations | Not included | Not included | Included | Included | | Start-Date Sensitivity | Not included | Included | Included | Included | | Projection | Included | Included | Included | Included | | Robustness | Not included | Not included | Included | Included | | Advanced analyses | Free | Starter | Advanced | Ultimate | | --- | :---: | :---: | :---: | :---: | | Strategies: where the result comes from | Not included | Not included | Included | Included | | Regime timeline | Not included | Not included | Included | Included | | Backtest reliability | Not included | Not included | 100 | 1,000 | | Project | Free | Starter | Advanced | Ultimate | | --- | :---: | :---: | :---: | :---: | | Monte Carlo projection cone — On every plan; the ceilings change | Included | Included | Included | Included | What each of these is, on its own page: [Risk-Off](/docs/strategies/risk-on-and-risk-off), [Hidden regimes (Markov)](/docs/strategies/hidden-regimes-markov), [Clustering](/docs/strategies/clustering), [Strategy's own performance](/docs/strategies/strategy-s-own-performance), the [regime timeline](/docs/analysis/regime-timeline) (drawn wherever a quantitative risk rule is active), the [Projection tab](/docs/analysis/see-where-a-strategy-could-go-with-the-projection-tab) (whose guide states [how far ahead each plan projects](/docs/analysis/see-where-a-strategy-could-go-with-the-projection-tab#how-far-ahead-does-my-plan-let-me-project)), and the [Robustness tab](/docs/analysis/test-how-much-to-trust-a-backtest-with-the-robustness-tab) — [backtest reliability](/docs/analysis/backtest-reliability) and the [stress test](/docs/analysis/stress-test). The worst-days rows of [Performance Metrics](/docs/analysis/what-every-number-in-performance-metrics-means#what-do-the-worst-days-rows-show) — historical and Gaussian value at risk, and conditional value at risk — are on every plan. ## How much compute power does each plan include? Compute power is how much of one simulation Fincanva computes at the same time, and it is the one plan difference that is about waiting rather than about what a strategy may do. It does not rise at every plan level. Set by your plan: 4 on Free and Starter, 8 on Advanced and 16 on Ultimate and Professional. See [what each plan includes](/docs/account-security/what-each-plan-includes). A higher figure runs more of the same work at once: it buys no extra data, no further allocation method and no longer history, so nothing about the strategy or the period behind the result changes with the plan. What it does and does not say about the wait is on [compute time](/docs/backtesting/compute-time), the page that owns how long a run takes. The table below prints the same figures under the label **Compute power**. ## What about Live strategies, leverage, and benchmarks? Following a strategy Live, the Holdings page, compute power and support are the limits that are not about what a strategy can hold. Leverage is in the realism table above. | Follow & help | Free | Starter | Advanced | Ultimate | | --- | :---: | :---: | :---: | :---: | | Strategies followed Live | Not included | 1 | 5 | No limit | | Holdings page — What to buy today, ticker by ticker | Not included | Included | Included | Included | | Compute power — How much of one simulation computes at the same time — Starter matches Free | 4 | 4 | 8 | 16 | | Support | Standard | Standard | Standard | Priority | Every plan benchmarks against the market benchmarks; from Advanced your own live portfolios can serve as benchmarks too. A strategy already pointed at one of yours keeps it and keeps running on a plan that does not include them — see [benchmark](/docs/getting-started/benchmark). ## Limits and edge cases ### What sets the backtest's starting year? Your plan sets the earliest year a backtest may start from — the **Backtest history from** row above — and **Fincanva applies it**. A plan whose cell reads **All history** has no floor and reaches every year there is data for; how far that is depends on the series, see [data coverage](/docs/data-methodology/what-fincanva-s-data-coverage-figures-count). The floor is applied in three places: - **The starting-year picker** lists no year before your plan's floor. Where a higher plan reaches further back, the plan's mark sits beside the picker and names it; opening it says from which year your plan starts and from which year that plan does. - **Saving** a start year before the floor is refused, and the message names the year you chose, the year your plan starts from and the plan that reaches it. When you duplicate, copy, combine or extract a strategy that starts earlier, the copy is still created, but it starts at your plan's floor — a message tells you at once which year it moved from and which plan keeps the full history. The original is not changed. - **A strategy that already starts earlier** — because you moved to a plan with a later floor — is not moved and not deleted. It is set aside like any strategy your plan does not cover: its settings stay editable, and moving its start to your plan's floor or later, or moving to a plan that reaches its year, makes it runnable again. See [plan compliance](/docs/backtesting/plan-compliance). A new strategy starts at 2000 by default, or at your plan's floor where that is later. See [what Settings → Usage tells you](/docs/account-security/what-settings-usage-tells-you#backtests-start-from) for how your own floor is shown. ### How do these limits show up while I work? A strategy that exceeds one of these limits does not lose what it holds — it stops running until it fits the plan again, or the plan changes to cover it. That check, and everything it does and does not do, is [plan compliance](/docs/backtesting/plan-compliance). To see where you personally stand against these numbers right now, see [what Settings → Usage tells you](/docs/account-security/what-settings-usage-tells-you); to see how your plan itself is displayed and changed, see [how to read your plan](/docs/account-security/how-to-read-your-plan). Fincanva does not tell you which plan to be on, and this page is not a recommendation to subscribe — see [Is this financial advice?](/docs/investing-theory/is-this-financial-advice#is-this-financial-advice). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/account-security/what-happens-if-a-payment-fails # What happens if a payment fails Your access does not stop: Fincanva keeps everything your plan covers available while the payment is retried, and shows a notice on every page until it clears. You resolve it by updating your payment method. ↗ See this in Fincanva — Settings, on the Billing page, under Payment method ## Before you start No prerequisites. The notice appears on its own when a payment Fincanva expected has not been collected, and it disappears on its own once the payment clears or the subscription ends — there is nothing to switch on, and no way to dismiss it. ## What does the notice on every page mean? It means a payment Fincanva expected has not been collected — and its wording tells you which of two different situations you are in. It appears as a warning strip above whatever page you are on, everywhere in the app. - **A renewal was refused.** "A payment for your subscription didn't go through. Update your payment method to keep your access." The payment method on file was declined — commonly an expired card, a block by the bank, or insufficient funds. - **A first payment has not arrived yet.** "We haven't received your first subscription payment yet. Check your payment method if nothing arrives." Nothing has necessarily gone wrong here: a payment method that settles over several days can leave a brand-new subscription uncollected while it completes. Neither case changes the plan you are on. On the billing page the card's headline still names that plan — **Advanced plan**, or whichever one you hold — and the payment is described beside it: a refused renewal under **Payment failed**, a first payment that has not arrived yet under **Payment pending**. ## What can I still use while this is happening? Everything your plan covers, exactly as before. A failed payment changes what Fincanva *says*, not what you can do: your strategies still run, your screeners still return matches, your live portfolios still update. The billing page states the same thing under **Payment failed** — "You keep Advanced while we retry." This is deliberate. The first refused charge is not a decision to stop serving you, and treating it as one would cut off someone whose card simply expired. ## Steps 1. Select **Update payment method**. The button sits on the notice strip itself, and again on **Settings** → **Billing**, under **Payment method**. 2. Wait while the button reads "Opening payment settings…". Fincanva does not handle card details itself — it hands you to Stripe, the payment provider that holds them. 3. Add or replace the payment method in the Stripe page that opens, and confirm it there. If your bank asks for an extra confirmation, complete it in the same place. 4. Return to Fincanva. ## What you should see The notice strip is gone from every page, and the billing page no longer shows **Payment failed** beside your plan. Nothing else has to be re-done: the state is read live from Stripe on each page you open, so it reflects the payment as soon as the payment provider accepts it. ## How long do I have before this becomes a problem? Fincanva does not set that deadline, and deliberately does not publish one. The retry schedule belongs to Stripe: it decides how many times to re-attempt the charge, how far apart, and when to give up. Any countdown shown here would be a number Fincanva does not control and could not keep true. What you can rely on is the notice itself. It stays for exactly as long as the payment is uncollected, and it disappears by itself the moment that changes — in either direction. ## What happens if the payment never goes through? Your subscription ends, and paid access ends with it. The billing page states the consequence in advance, under **Payment failed**: "Update your payment method — if the retries don't go through, the plan ends." **Nothing you have built is deleted.** Strategies, screeners, portfolios and their results all remain. What changes is what a plan covers: work beyond the reach of your current plan stops running rather than disappearing, and trying to run it is refused in words that name the plan — `This strategy is outside your {currentPlan} plan, so it cannot run.` Subscribing again restores the access; it does not have to restore the work, because the work was never removed. Removing an account and its contents is a separate, deliberate action you take yourself — see [account deletion](/docs/account-security/account-deletion). A failed payment never triggers it. Fincanva does not tell you which plan to be on, and this page is not a recommendation to subscribe — see [Is this financial advice?](/docs/investing-theory/is-this-financial-advice#is-this-financial-advice). ## What does the plan card show once the subscription has ended? It stops naming the plan you held. Once access actually stops, the plan card on **Settings** → **Billing** reads the headline **Free** — the same headline shown to an account that never subscribed — and the line under the plan name reads **"No active subscription."** instead of a price. The level indicator above it reads **Level 0 of 3**: Free is not missing from Fincanva's plan scale, it sits on it unheld — see [plan level](/docs/account-security/plan-level) for what the scale counts. A dated row still names what happened, so the change is not silent. It reads `Your {plan} plan ended on {date}`, naming the plan you held and the day it ended, or, when the subscription closed because the retries described above ran out rather than because you cancelled it, `Your {plan} plan ended — the payment was never collected`. Either sentence is followed by the same line: "Everything you built is still here. Subscribing again restores access to it." The action beneath depends on which of the two endings you are in: after a cancellation it reads **Choose a plan** and opens the same plan picker as a first subscription, while a subscription that ended because the retries ran out reads **Update payment method** instead — that ending is a payment that never arrived, so the card offers the payment page rather than the plan picker. ## Common problems ### The strip is still there after I updated my card Open a page again. The billing state is read fresh each time a page loads, so the strip clears on the next load rather than the instant the Stripe page closes. If it persists, the new method has not been accepted yet — the Stripe page shows the payment's own status. ### "Couldn't open the payment portal. Try again." The handover to Stripe did not complete. Select **Update payment method** again; the same button on **Settings** → **Billing** opens the same place if the notice strip's one keeps failing. ### I never subscribed, and I'm seeing a payment notice The notice only appears for an account with a subscription whose payment is uncollected. If you are on the free plan you will not see it — check which account you are signed in with on **Settings**. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/account-security/what-settings-usage-tells-you # What Settings → Usage tells you Settings → Usage answers two separate questions on one page: how much you hold against the ceilings your plan really sets, and what your plan gives you next to what each plan above it adds. ## How does Settings → Usage work? The page has two sections. **What you hold** counts, across your whole account, each list your plan puts a ceiling on. **Your plan** lists what your plan includes in the column **What you have**, and what every plan above yours adds in the column **Still to unlock**. ## What does "What you hold" show? "What you hold" shows a row only for a count your plan really caps, with the same counter the list itself shows beside its header, and next to it a row of seats — one cell per unit of the ceiling, filled for each one you hold. In practice: - On **Free**, the row is saved strategies, capped at two. - On **Starter** and **Advanced**, the row is strategies followed Live, capped at one and five. - On **Ultimate** there is no capped count, so no row appears. - On **Professional** there is no capped count either, and the section reads "Your plan puts no ceiling on anything you hold." On every plan on sale — Free, Starter, Advanced and Ultimate — the section opens with your plan's plate: a ribbon with the plan's name and four of its figures (strategies in Live, allocation methods, how far back backtests start, compute power), the same values as the lines of "What you have" below. On Ultimate the plate adds "The highest plan: you have everything Fincanva does." Professional has no plate, because it is not a plan on sale. **Why saved strategies and saved screeners usually have no row:** on the plans where they read "no limit", the figure behind them is a technical safety maximum of 999 that stops runaway creation. No plan raises it, because it is not a plan lever, so the page reads it as no limit and shows no row. **A zero ceiling is not shown here either:** following strategies Live on Free is not a count Free caps but a feature Free does not include, so it appears under "Your plan", in the plan that opens it. The ceilings for every plan are on [what each plan includes](/docs/account-security/what-each-plan-includes). Each row's counter reads one of a few ways, depending on where you stand: - `{held} of {allowed}` — within the ceiling, for example "4 of 5" for strategies followed Live on Advanced. - `{held} of {allowed} · {beyond} set aside` — over the ceiling; the surplus is what reads **Set aside**, per [plan compliance](/docs/backtesting/plan-compliance). - `{held} of {allowed} · {beyond} not followed` — specific to Live: strategies past the Live ceiling stay open and readable, they simply stop being followed. ## What does "Your plan" show? "Your plan" shows what your plan gives you, and what each plan above yours adds, in two columns built from the same lines as the plan comparison on the public pricing page — one shared derivation, so the figures always match what each plan includes. - **What you have** lists every line of the comparison that your plan includes, grouped under Build, Protect, Analyse, Project and Follow & support. Each line carries your plan's value: a number, "No limit", a year or "All history", or a tick where the line is simply included. This is where the limits inside a single strategy show — for example "Instruments per strategy", "Screeners per strategy", "Strategies in a Combined", "Leverage" and "Backtests start from". "Strategies in a Combined" counts the strategies a [Combined](/docs/getting-started/combined) holds in use; a switched-off one does not count. - **Still to unlock** has one group for every plan above yours, cheapest first. Each group is headed by a button that names the plan — for example "Switch to Advanced" — that leads to Settings → Billing, with a count of what it adds ("N more things"), and lists the lines that plan adds, each with the value it brings. On Ultimate there is nothing above to unlock, so this column does not appear and "What you have" stands alone, centred. On **Professional** the section shows no columns — see the question on the billing card below. ## Does this page show my trial's limits? Yes, the same way it shows any plan's: this page reads your account's live enforced capability level, and during a 30-day trial that level is the plan the trial is on — a trial has no limits of its own, so both sections show your plan's figures, from day 1. What this page does not do is call the trial out by name — the trial row of the plan card at **Settings → Billing** does that, with the trial's end date, not here. See [the 30-day trial](/docs/account-security/the-30-day-trial) for what the trial actually grants and what that row says. ## Why does this page ever disagree with the billing card? In one case, and a trial is not it — during a trial the two agree, because the trial runs at the plan the billing card names (the section above). The case that remains is **a paying customer on Professional**: the billing card names your plan from Fincanva's own price catalogue, which has no entry for Professional, so a Professional subscriber sees a generic **Custom** label there instead of a name. This page reads your account's actual enforced capability level instead, so "What you hold" still counts against Professional's own ceilings. "Your plan" draws no comparison for it: Professional is not one of the plans on sale, so the section shows only "Your plan is not one of the plans on sale, so there is no comparison with the others here. The ceilings above are its own." See [how to read your plan](/docs/account-security/how-to-read-your-plan) for what the billing card shows and why. ## Limits and edge cases ### Backtests start from Your plan's earliest backtest start year shows as the "Backtests start from" line in **What you have** — a year, or "All history" where the plan has no floor — and where a plan above yours reaches further back, its year shows under **Still to unlock**. Fincanva applies that floor: the starting-year picker lists no earlier year, a save that asks for one is refused with a message naming the plan that reaches it, and a strategy that already starts earlier — after a move to a plan with a later floor — is set aside rather than moved, with its settings still editable. The floor for each plan, and the three places it is applied, are on [what each plan includes](/docs/account-security/what-each-plan-includes#what-sets-the-backtests-starting-year). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/account-security/why-fincanva-asks-you-to-accept-the-terms # Why Fincanva asks you to accept the Terms Fincanva asks you to accept its Terms and Privacy Policy because it does not create an account, or let an account into the app, without a recorded acceptance of the current version of the Terms. You give that acceptance once, by ticking one box when you sign up, and you are asked again only when Fincanva publishes a new version — that second request is the screen headed **One more step**. ## Before you start No prerequisites. The acceptance step appears on its own: on the sign-up screen when you create an account, on the sign-in screen under **One step to finish** when you sign in with an address or a Google account that has no Fincanva account yet, and on the **One more step** screen when an existing account's recorded acceptance is out of date. ## Steps 1. On the sign-up screen, tick "I accept the Terms and Privacy Policy." — the box always starts unticked. 2. Sign up the way you prefer: the emailed link or code, a password, or **Continue with Google**. If you press one before ticking the box, nothing is sent: the box is marked, the cursor moves to it, and it reads "Please accept the Terms and Privacy Policy to continue." 3. If the **One more step** screen appears later, tick the same box and select **Agree and continue**. ## What you should see Fincanva creates your account and records the date and the version of the Terms you accepted. After **One more step**, you go on into the app, and the screen does not come back until Fincanva publishes a new version of the Terms. ## Why do I have to accept the Terms to sign up? Because Fincanva does not create an account without that acceptance. The sign-up screen carries one required checkbox — "I accept the Terms and Privacy Policy." — and every way of signing up checks for it before doing anything: the emailed link or code, a password, and **Continue with Google**. Press one without the tick and nothing is sent — the box is marked, the cursor moves to it, and it reads "Please accept the Terms and Privacy Policy to continue." The box always starts unticked. The rule is not only on the screen: the server itself refuses to create an account whose request does not carry the acceptance. When you accept, Fincanva records the date and the version of the Terms you accepted. Both come from Fincanva's own clock and its own current version, never from your browser. Starting from the sign-in screen instead adds one step. If you sign in with **Continue with Google**, or with the link or code Fincanva emails you, and there is no Fincanva account for you yet, the sign-in screen asks for the same acceptance under the heading **One step to finish** before it creates one — see [passwordless sign-in](/docs/account-security/passwordless-sign-in). Starting from the sign-up screen, where you have already ticked the box, you never see it, and neither does anyone who already has an account. ## Is there a minimum age to use Fincanva? Yes: the Terms restrict Fincanva to adults. In the Terms' own words: "Usage of Fincanva and the Service is age restricted: to access and use Fincanva and its Service the User must be an adult under applicable law." There is no separate age checkbox. The requirement lives inside the Terms, so ticking the box that accepts the Terms accepts it too. ## What does the "One more step" screen mean? The **One more step** screen means your account has no recorded acceptance of the current Terms — either because you accepted an earlier version, or because no acceptance was ever recorded for it — and Fincanva needs you to accept the current version before you carry on. It reads "Please review and accept to keep using Fincanva.", shows the same checkbox as sign-up, and a button, **Agree and continue**. Pressing it before ticking the box saves nothing: the box is marked and reads "Please accept the Terms and Privacy Policy to continue." Accepting records the new version and takes you on into the app. There is no way past the screen without accepting: until you accept the current version, every page of the app you open sends you back to it. Signing out and in again does not skip it either, because the check reads the version recorded on your account, not anything stored in your browser. ## Why am I being asked to accept the Terms again? Because Fincanva has published a new version of its Terms since you last accepted. Every acceptance is stored with the version it was given for; once the current version moves on, an acceptance recorded against an earlier one no longer counts, and the next page you open in the app shows **One more step**. It happens once per new version. After you accept, the screen does not come back until the Terms change again. An account with no recorded acceptance at all meets the same screen once, for the same reason. ## Where do I read the Terms and the Privacy Policy? On Fincanva's website: [the Terms](/terms), [the Privacy Policy](/privacy), and [the addendum to the Terms](/terms/addendum). The two links inside the checkbox's sentence open the Terms and the Privacy Policy in a new tab, so reading them does not lose your place on the sign-up screen. Cookies are a separate consent, with its own banner and its own way to change your mind later — see [how cookie consent works](/docs/account-security/how-cookie-consent-works-on-fincanva). A visitor covered by US state privacy law also sees a "Notice at Collection" link beside the checkbox, explained under [Your Privacy Choices and Notice at Collection](/docs/account-security/your-privacy-choices-and-notice-at-collection). What happens to your record of accepting the Terms if you later delete your account is covered under [account deletion](/docs/account-security/account-deletion). ## Common problems ### "Please accept the Terms and Privacy Policy to continue." You pressed a button — **Continue with email →**, a password sign-up, **Continue with Google**, or **Agree and continue** — before ticking the box. Nothing was sent and nothing was saved. Tick "I accept the Terms and Privacy Policy." and press the same button again. The buttons are never greyed out by the box: the line under it is how the screen tells you what is missing. ### "One step to finish" after signing in with an emailed link or code You chose **Sign in**, but there is no Fincanva account for that address yet, so after you opened the link or typed the code, the sign-in screen asks to create one: "This email doesn't have an account yet. Accept the Terms and Privacy Policy to create it." Your address is already filled in when you opened the link in the same browser; otherwise type it. Tick the box, press **Continue with email →**, and open the new email Fincanva sends — its link or code creates your account and signs you in. The link or code from the first email cannot be used again. Until you open that first email, the sign-in screen looks the same whether or not an account exists, so nobody who types your address can learn whether you have one. ### "Something went wrong. Try again." Your acceptance on the **One more step** screen was not saved. Press **Agree and continue** again. If your session expired while the screen was open, Fincanva sends you to the sign-in screen instead; sign in and the **One more step** screen comes back, because the acceptance was never recorded. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/account-security/account-deletion # Account deletion Account deletion in Fincanva is a scheduled request rather than an immediate erase: you confirm it, and the account is set to be deleted **14 days later**. Those 14 days are a grace period you control — sign in at any point during them and **Keep my account** cancels the request outright. When the date arrives, your private content is deleted and your account identity is anonymized. The dialog states it plainly: "Deletion is scheduled for 14 days from now, not immediate. You can sign back in any time during that window and cancel." **Also seen as:** delete account, close account, right to erasure ## What happens the moment I request deletion? Fincanva schedules the deletion, signs out the browser you did it in, and emails you the date. Nothing is deleted yet. Three things stand between a stray click and a scheduled deletion: 1. **A recent sign-in.** If your session is more than 15 minutes old, Fincanva refuses and says "For your security, please sign in again, then return here to delete your account." with a **Sign in again** button. This action cannot run off a session left open on someone else's machine. 2. **Typing your own address.** The dialog asks you to type your email in full — `Type {email} to confirm` — and the confirm button stays disabled until it matches. 3. **A written summary first.** Under "What happens after the grace period", the dialog lists exactly what goes and what stays before you can act. Once confirmed, you land back on the sign-in screen, and an email arrives titled "Your Fincanva account is scheduled for deletion" carrying the exact date. ## How do I cancel a scheduled deletion? Sign back in. While a deletion is scheduled, a banner sits at the top of every page — `Your account is scheduled for deletion on {date}.` — with a **Keep my account** button beside it, and pressing it cancels the request. Your security settings show the same thing as `Your account will be deleted on {date}. You can still keep it until then.` Nothing is degraded while you wait: during the grace period the account works exactly as before, your strategies and screeners run, and the scheduled date is the only difference. The scheduled-deletion email spells the route out: "You have until then to change your mind: just sign in to Fincanva and click *Keep my account* on the banner at the top of any page." The window closes when the date arrives. Once Fincanva has begun finalizing the deletion it cannot be called back, because the removals it performs are irreversible. ## What is deleted, and what is anonymized? Two different fates, and the distinction is the point: your content is deleted, while the account record itself survives in a stripped form that identifies nobody. | What | Fate | |---|---| | Strategies and strategy folders you own, including their saved run history | deleted | | Screeners and screener folders you own | deleted | | Your personal preferences | deleted | | Your sign-in methods, connected accounts, and active sessions | deleted | | Your two-factor secret and backup codes | deleted | | Your account identity — email address, name, profile picture | **anonymized**: the address is replaced with a non-deliverable placeholder and the name becomes "Deleted user" | | Your record of accepting the Terms | **kept**, with the IP address it was recorded from removed | | Public and shared data | not deleted | Anonymization rather than row-removal is deliberate: keeping a nameless account record keeps historical references intact while stripping everything that points at a person. In the app's own words: "Your account identity is anonymized." and "Public and shared data are not deleted." Read that second sentence precisely: **Public** means the catalogue Fincanva publishes, not something you made visible — see [Mine / Public](/docs/getting-started/mine-public). Public items were never yours, so deleting your account leaves them untouched; every item that *is* yours is deleted no matter who else could see it. The record of your acceptance of the Terms is kept for the same reason the account row is: it is what keeps "did this account accept version N, and when" answerable once the account itself is gone, and the IP address stored beside it is removed because that part points at a person. Any active subscription is cancelled as part of finalizing the deletion. ## Does deletion sign my other devices out? No — not on the day you ask. Scheduling the deletion signs out only the browser you requested it from; every other signed-in browser stays signed in, because the account keeps working normally throughout the grace period. Your sign-in methods and every remaining session are removed when the deletion actually runs on day 14. If you want the other browsers out now, that is a separate action: press **Sign out** on each row, or **Sign out all other sessions**, under [active sessions](/docs/account-security/active-sessions). And if you cancel with **Keep my account**, you simply sign in again as normal. ## How does Fincanva handle it? - The grace period is 14 days, counted from the moment you confirm. - Confirmation requires typing your own email address, and a sign-in newer than 15 minutes. - Requesting deletion signs out the browser you did it in — other sessions are untouched until day 14 — and the account still works normally if you sign back in. - **Keep my account** cancels the request at any time before the date, from the banner or your security settings. - Two emails are sent: one confirming the schedule and its date, one confirming completion. - After the date: private strategies, screeners, folders, preferences, sign-in methods, sessions, and two-factor data are deleted; the account identity is anonymized; public and shared data are untouched. - There is no "delete right now" option — the 14-day path is the only one. ## What is the difference between day 1 and day 15? **Day 1.** You type your email into the confirmation field and press **Delete my account**. Fincanva signs you out and emails you the date — say 8 August. Nothing has been deleted. That evening you sign in to check something: everything is there, every strategy runs, and a banner at the top reads "Your account is scheduled for deletion on 8 August." next to **Keep my account**. Had you pressed it, the schedule would have been cancelled on the spot and the account would carry on as if you had never asked. **Day 15.** You didn't press it. On 8 August the deletion runs. Your strategies, strategy folders, screeners, screener folders and their saved run history are gone; so are your preferences, your sign-in methods, your sessions, and your two-factor secret and backup codes. Your account row survives with its email replaced by an undeliverable placeholder and its name set to "Deleted user" — nothing in it points to you. A final email arrives: "Your Fincanva account has been deleted as scheduled. We've removed your sign-in methods, your private strategies and screeners, and your preferences." Signing in on day 15 is not possible, and there is no undo. Coming back means creating a new account, which starts empty — the old one is not recoverable, by you or by anyone at Fincanva. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/account-security/active-sessions # Active sessions Active sessions is the list of browsers that are currently signed in to your Fincanva account, one row per browser, with the ability to end any of them remotely. Ending a session signs that browser out and forces a fresh sign-in there; it changes nothing else about your account and does not touch your password. The list is the answer to "am I still signed in somewhere I shouldn't be?" — and the fix for it. **Also seen as:** signed-in devices, logged-in devices ## What does the Active sessions list show? Each row is one signed-in browser, labelled in the form "Chrome on macOS" — browser and operating system, read from the browser's own identification — falling back to "Unknown device" when that identification is missing or unreadable. Under the label sits a freshness line: | Row state | What you see | What it means | |---|---|---| | The browser you are reading this in | "Active now" plus a **This device** badge | the current session; it has no Sign out button | | Any other signed-in browser | `Last active {relative}` — for example "Last active 2 hours ago" | when that session last made a request | The rows are sessions, not machines: two browsers on one laptop are two rows, and tabs inside one browser share a single row. ## How do I sign out a device I'm not using? Press **Sign out** on that row. The session ends immediately, the row disappears from the list, and the next time anyone opens Fincanva in that browser they meet the sign-in screen. Your own session is untouched — the row you are sitting in offers no **Sign out**, only the **This device** badge. To clear everything else at once, **Sign out all other sessions** sits below the list and asks for confirmation first: "Sign out from all other devices?" — "You'll need to sign in again from those devices. This session stays signed in." Confirm with **Sign out others**. The button only appears when there is in fact another session to end. ## How long does a session last if I do nothing? A session ends on its own in two ways, whichever comes first: **2 hours of inactivity**, or **30 days** from when it was created. Activity refreshes the idle clock but not the 30-day one, so even a browser you use daily eventually asks you to sign in again. When either limit fires, the session is gone rather than merely idle, and Fincanva says so: "Session expired" — "Your session expired — please sign in again." Nothing in your account changes; you simply sign in and carry on. When you hit that expiry from inside the app, signing back in returns you to the page you were on rather than to a generic starting page — the exact view you were looking at, not just the section it lived in. ## Why did an old device disappear from the list on its own? Fincanva keeps at most **10 active sessions per account**. When a new sign-in would push you past that, the least recently active session is dropped to make room. Signing in again on the same browser also replaces that browser's own earlier row rather than stacking a second one, which is why a much-used device shows one entry and not a history. So a row vanishing without you pressing anything means one of three ordinary things: the session hit its 2-hour idle limit, it hit its 30-day limit, or it was the oldest of eleven. ## Does changing my password sign my other devices out? Yes. Changing your password from your account settings ends every other session on your account, leaving only the browser you changed it in signed in. That makes a password change the blunt instrument for "get everyone else out", and it is worth knowing that the reverse is not true: signing a session out does not change your password, so anyone who knows the password can sign back in. If you suspect the password itself is known, change it — see [passwordless sign-in](/docs/account-security/passwordless-sign-in) — and consider turning on [two-factor authentication](/docs/account-security/two-factor-authentication). ## How does Fincanva handle it? - One row per signed-in browser; the current one carries the **This device** badge and cannot sign itself out from the list. - Other rows show `Last active {relative}`; the current row shows "Active now". - A session expires after 2 hours of inactivity, and in all cases 30 days after it was created. - Signing back in after an expiry from inside the app returns you to the page you were on, not to a generic starting page. - At most 10 sessions are kept per account; beyond that the least recently active one is dropped. - **Sign out all other sessions** appears only when another session exists, and always asks for confirmation. - Changing your password signs all other sessions out. Scheduling [account deletion](/docs/account-security/account-deletion) signs out only the browser you requested it from; the rest are removed when the deletion runs. ## What does it look like in practice? You finished a session on a hotel computer last night and cannot remember whether you signed out. This morning, from your own laptop, you open your security settings. Two rows are listed. The top one reads **This device** with "Active now" — that is the laptop you are on. The second reads "Chrome on Windows" with "Last active 14 hours ago" and a **Sign out** button, which matches the hotel machine. You press **Sign out** on the second row. It disappears, and the hotel browser now holds a dead cookie: whoever opens Fincanva there gets the sign-in screen, with no access to your strategies. Your laptop session is unaffected — you never had to reset your password to close that door. Had there been four unfamiliar rows instead of one, **Sign out all other sessions** would have cleared them in a single confirmed action, leaving only the laptop signed in. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/account-security/passkeys # Passkeys A passkey is a sign-in credential that lives on one device — a phone, a laptop, or a hardware security key — and is unlocked by that device's own screen lock, so you prove who you are with a fingerprint, a face scan, or a device PIN instead of typing a secret. **Fincanva does not support passkeys yet.** This page explains the concept so it is already clear when the feature arrives; it describes no Fincanva flow, because none exists. **Also seen as:** passkey, WebAuthn credential, FIDO2 credential ## Can I use a passkey with Fincanva today? No. In your security settings the **Passkeys** row exists but is inert: its value reads "None" and its button is disabled and labelled "Coming soon". There is nothing to enrol, nothing to name, and nothing to remove. Until it ships, the ways into a Fincanva account are the three described under [passwordless sign-in](/docs/account-security/passwordless-sign-in) — an emailed link, an emailed 6-digit code, or a password — plus **Continue with Google**, each of which can be protected with [two-factor authentication](/docs/account-security/two-factor-authentication). ## What is a passkey? A passkey is a pair of cryptographic keys created for one website and stored on one device. The device keeps the private half and never releases it; the website keeps only the public half, which is useless to anyone who steals it. Signing in means the site sends a challenge, your device unlocks the private key with your fingerprint, face, or PIN, and returns a signature the site can verify. Two consequences follow from that shape, and they are the whole point of the design: - **Nothing reusable is transmitted.** A signature answers one challenge and cannot be replayed elsewhere, so there is no shared secret in flight to intercept. - **The credential is bound to the site that issued it.** A passkey created for one site will not sign a challenge from a lookalike domain, which is why passkeys resist phishing in a way a typed secret cannot. Passkeys are the consumer-facing name for credentials built on the WebAuthn and FIDO2 standards, which is why the same passkey works across browsers and platforms that implement them. ## How is a passkey different from a password? In one line: a password is something you know and can therefore be tricked into typing somewhere else, while a passkey is something your device holds and will only ever present to the one site it was made for. | | Password | Passkey | |---|---|---| | Where it lives | in your head or a manager | on a device, in its secure store | | What travels to the site | the secret itself | a one-off signature | | Phishable | yes — you can type it into a fake page | no — it will not sign for the wrong domain | | Reusable across sites | yes, and that is the risk | no, one per site by construction | | Breach exposure | the site holds something worth stealing | the site holds only a public key | | How you unlock it | by recalling it | with the device's fingerprint, face, or PIN | The practical trade is convenience against portability: a passkey removes the recall step entirely, but it is tied to the device or the platform keychain that holds it, so losing every synced device is a different kind of problem than forgetting a password. ## What the Fincanva setting shows today The security settings page lists **Passkeys** alongside **Password** and **Two-factor authentication** so the eventual home for the feature is visible. The row's state is "None", and its only control is the disabled **Coming soon** button. No passkey can be created, and none affects how you sign in today. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/account-security/passwordless-sign-in # Passwordless sign-in Passwordless sign-in is signing in to Fincanva with a single-use link or 6-digit code emailed to your address, instead of typing a password. It is the route the sign-in screen offers first: you enter your email, press **Continue with email →**, and Fincanva sends one email that carries both a clickable link and a typeable code. Signing in with a password remains available as a second route, and **Continue with Google** as a third. **Also seen as:** magic link, email link, email code, one-time code, OTP ## How does passwordless sign-in work? You give Fincanva your email address and it emails you two interchangeable ways to finish the sign-in — click the link, or type the code into the screen you are already looking at. Both are single-use and both stop working 10 minutes after the email is sent; the screen says so verbatim: "Enter the 6-digit code below, or click the link in the email. Both expire in 10 minutes." If the email hasn't arrived, **Resend code** becomes available again 30 seconds after each send, and the button counts down in the meantime. On the sign-up screen the same email doubles as account creation: `We sent a code to {email} — your first sign-in will create your account.` ## How is signing in without a password different from signing in with one? The difference is what proves it's you — control of your inbox, or knowledge of a secret you stored yourself. | | Passwordless (link or code) | Password | |---|---|---| | What you supply | your email address | your email address and your password | | What proves it's you | you can open the email | you know the password | | What you have to remember | nothing | the password | | How long the proof lasts | 10 minutes, single use | until you change it | | Where it can leak | your inbox | anywhere you reused it | | How you start it | **Continue with email →** | **Sign in with password instead** | Neither route is a lesser account: the same account can use whichever is at hand on the day, and [two-factor authentication](/docs/account-security/two-factor-authentication) applies to both. A third route, **Continue with Google**, hands the check to your Google account instead — and it can also create the account, not only sign in to one you already have. If Google confirms your identity but you don't have a Fincanva account yet, the sign-in screen shows a consent step, headed **One step to finish**, asking you to accept the Terms and Privacy Policy before it creates one. The checkbox starts unticked; press the button without ticking it and nothing happens except that the box is marked with "Please accept the Terms and Privacy Policy to continue." Tick it, press **Continue with Google** again, and you're in — Google doesn't ask again, and there's no separate signup page and no email to open. The emailed link and code lead to the same step. If you enter an address on the sign-in screen that has no Fincanva account yet, the email arrives exactly as it would for an existing account; only when you open its link or type its code does the sign-in screen show **One step to finish**, reading "This email doesn't have an account yet. Accept the Terms and Privacy Policy to create it." Tick the box and press **Continue with email →**: a new email arrives, and its link or code creates the account and signs you in. The first email's link and code are spent by then. A returning user who already has an account never sees this step, by any route. ## Why does Fincanva ask me to verify my email address? Fincanva requires a verified email address before you can sign in with a password, because an unverified address may not belong to the person who typed it. A verification link goes out when you sign up, and until it is opened, a password sign-in stops with "Verify your email before signing in." and the screen switches to "Please verify your email" with a **Resend verification email** button. Opening the link verifies the address and signs you in. The address matters beyond sign-in: it is the channel every passwordless link, code, reset link, and security notice travels through. ## What if I forget my password, or never set one? Use **Forgot password?** on the sign-in screen and Fincanva emails you a reset link, which is valid for one hour. Past that, the screen tells you plainly: "For security, password reset links expire after 1 hour." — request a fresh one and the old link stays dead. If you created your account with Google and never had a password, the same machinery sets your first one. Fincanva shows "You signed in with Google. We'll email you a link to set a password." with a **Send reset link** button; open the emailed link and choose a password. ## How strong does my password have to be? A Fincanva password must be at least 8 characters long — that is the only rule the app enforces. There is no requirement for capitals, digits, or symbols. Above that minimum the sign-up and reset-password screens show an advisory strength bar labelled `Strength: {level}`, where the level reads **Weak**, **Fair**, **Good**, or **Strong**. It reacts to length and to the mix of character types, and it never blocks you: a password rated **Weak** is accepted as long as it reaches 8 characters. Treat it as feedback, not a gate. ## How does Fincanva handle it? - Passwordless is the route offered first; password sign-in and **Continue with Google** sit beside it. - **Continue with Google**, the emailed link and the emailed code all create an account for a first-time visitor who started from the sign-in screen, after a one-tick consent step for the Terms and Privacy Policy (**One step to finish**). - One email carries both the link and the code, and both expire 10 minutes after it is sent. Each can be used once. - **Resend code** unlocks 30 seconds after each send. - Password reset links expire after 1 hour. - A verified email address is required before a password sign-in succeeds. - Passwords must be at least 8 characters; the strength bar is advisory only. - Changing your password from your account settings signs your other sessions out — see [active sessions](/docs/account-security/active-sessions). ## What does it look like in practice? At 09:00 you enter your email and press **Continue with email →**. One email lands with a **Sign in** button and the code `418 205`. At 09:04 you are on your laptop, where you opened the request, so you type `418205` into the code field and you are in. Had you instead opened the email on your phone, tapping the button would have signed you in there — either one works, whichever device is in your hand. At 09:11 both are dead. Typing the code returns "That code didn't work. Try again or request a new one.", and the link lands on "This link is invalid or has expired." Pressing **Resend code** issues a fresh pair with its own 10-minute window; the first pair never comes back. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/account-security/plan-level # Plan level A plan level is your account's position on the ordered scale of Fincanva's paid plans, and it is what the plan card in **Settings → Billing** reports next to your plan name: `Level {rank} of {total}`. The scale runs Starter, Advanced, Ultimate — three levels, so `{total}` reads 3 — and `{rank}` is where your held plan sits on it: Starter is level 1, Advanced level 2, Ultimate level 3. **Free is not on this scale at all** — it sits at level 0, and the app treats that as *unheld*, not as a missing or broken value. **Also seen as:** plan rank ## Which plans are on the scale, and which are not? Only the three plans you can hold through checkout are on it: **Starter** (level 1), **Advanced** (level 2), and **Ultimate** (level 3), so `{total}` is 3. Two plans sit outside it, for different reasons: - **Free is level 0.** It is the account you have before subscribing to anything, so the scale still applies to it — it is simply unheld. The plan card still shows the indicator for a Free account, at level 0 of 3. - **Professional does not appear on the scale at all.** It is not sold through checkout — [what each plan includes](/docs/account-security/what-each-plan-includes) covers how it is reached — so the plan card shows no level indicator for it: not level 4 of 3, no indicator. A Professional subscriber's card reads **Custom** instead of a level. ## Is this the same as the five plans listed on "what each plan includes"? It is the same ordering, seen from two different widths. [What each plan includes](/docs/account-security/what-each-plan-includes) describes Fincanva's full plan ordering — Free, Starter, Advanced, Ultimate, Professional, five in ascending order of what each unlocks. The plan card's level scale is the narrower view drawn from the same order: it counts only the plans a held subscription can actually be, which is why its own total reads 3 rather than 5. Free is the floor of the wider order and Professional is its top, and neither is ever assigned as a *held* level on the card — which is exactly why the card's own scale starts at Starter and stops at Ultimate. ## Is this the same "level" as the one on Settings → Usage? No — they answer different questions with the same word. This page's level is about your **subscription**: which of the three sellable plans it names, shown on the plan card. [What Settings → Usage tells you](/docs/account-security/what-settings-usage-tells-you) reads a different figure — the *capability* actually enforced on your account right now. The two agree for every account holding one of the three sellable plans, including throughout a [30-day trial](/docs/account-security/the-30-day-trial), which runs at the plan the trial is on rather than at a level of its own. They part company on **Professional**, which is a real enforced capability but not one of the three plans this scale counts: the plan card shows no level there at all, while Settings → Usage still counts what you hold against Professional's own ceilings, and only its plan comparison stays empty, because Professional is not a plan on sale. Neither page is wrong; they are naming two different things that happen to use the same word. ## How does Fincanva handle it? - The plan card in **Settings → Billing** shows the level indicator next to your plan name whenever your account holds one of the three paid, checkout-sold plans, or is on Free (level 0). During a trial it shows the level of the plan the trial is on, which is also the plan being enforced. - A Professional (custom) account shows no level indicator at all — the figure the scale would answer does not apply to a plan with no published price. - `{rank}` and `{total}` are read live from the plans Fincanva actually sells today; this page states the current scale rather than a number to remember, since a plan Fincanva adds or retires from checkout changes `{total}` without needing a new word for the concept. ## What does it look like in practice? An account on **Advanced** opens **Settings → Billing** and sees its plan card read **Level 2 of 3** in English or **Livello 2 di 3** in Italian, beside the plan name: Advanced is the middle of the three sellable plans, one above Starter and one below Ultimate. An account on **Free** sees the same indicator read **Level 0 of 3** — no plan held yet, not an error. An account on **Professional** sees no level indicator at all, because Professional is not one of the three plans the scale counts. A Starter trialer sees **Level 1 of 3** on the plan card from the first day of the trial, and Starter's own limits are what the account runs under while the trial lasts — the same figures [what Settings → Usage tells you](/docs/account-security/what-settings-usage-tells-you) reports. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/account-security/two-factor-authentication # Two-factor authentication Two-factor authentication is a second proof of identity that Fincanva asks for after your first sign-in step succeeds, so that an email address or password on its own is not enough to reach your account. Fincanva accepts three kinds of second proof: a 6-digit code from an authenticator app, one of your saved backup codes, or — on some sign-in routes — a code emailed to you. It is off until you turn it on, and once on it applies to every way into the account. **Also seen as:** 2FA, two-step verification, TOTP ## What does two-factor authentication protect against? It protects against someone who already has your first factor. A password can be guessed, reused, or leaked in another company's breach; an inbox can be left open on a shared machine. With a second factor on, none of that is sufficient on its own, because the attacker also needs the phone in your pocket or the codes you saved. It does not protect against handing the second-factor code to someone who asked you for it. Fincanva never asks for your 6-digit code or a backup code outside the sign-in screen — not by email, not in a chat. ## How do I turn two-factor authentication on? Fincanva walks you through a three-step wizard titled "Set up two-factor authentication". First it shows a QR code: "Scan the QR code with your authenticator app (Google Authenticator, Authy, 1Password…)." — and if the camera route fails, "Can't scan? Enter this code manually" reveals the same secret as text. Second, you prove the pairing worked: "Enter the 6-digit code" and press **Verify**. Third, Fincanva shows your backup codes and makes you tick "I have saved my backup codes" before **Done** unlocks. Before the wizard starts, Fincanva confirms it is really you. If your account has a password, it asks for it ("We ask for your password to confirm it's you."). If it has no password — a Google-only or email-only account — it emails you a confirmation link instead. Turning 2FA off and regenerating codes go through the same confirmation. ## What are backup codes and when do I use them? Backup codes are ten one-time recovery codes, shown once during setup, that stand in for your authenticator app when you can't reach it. The screen states the rule: "Save these one-time recovery codes somewhere safe. Each works once if you lose your authenticator app." You can **Copy all** or **Download .txt** on the spot. At the sign-in screen, **Use a backup code instead** swaps the 6-digit field for a backup-code field, which takes the code in the two five-character groups it was issued in. A wrong or already-spent code returns "That backup code did not work. Try another." You can issue a fresh set at any time with **Generate new backup codes**; doing so kills the old set outright — "Your old backup codes will stop working. Save the new set somewhere safe." ## What does "Trust this browser for 30 days" do? Ticking **Trust this browser for 30 days** at the code screen tells Fincanva to skip the second-factor prompt for the next 30 days on that browser, for **email + password** sign-ins. The scope is narrower than the label suggests, and it matters: an emailed link, an emailed code, or **Continue with Google** asks for the second factor every time, even on a browser you trusted. Trust is stored per browser, so a different browser, a different device, or a private window starts untrusted. ## What if I lose my phone? Use a backup code. At the code screen, **Use a backup code instead** takes one of the ten codes you saved during setup, and one code is all it takes to get in — then you can pair a new authenticator app and generate a new code set from your account settings. If your first step was **Continue with Google**, one more door is open: "Can't access your authenticator app?" offers **Email me a code**, which sends a 6-digit code valid for 5 minutes. That offer is deliberately absent when you signed in by emailed link or emailed code, because a code sent to the same inbox would not be a second factor at all. ## How does Fincanva handle it? - Two-factor authentication is off until you turn it on. There is no plan requirement and no forced enrolment. - Once on, it applies to every sign-in route — password, emailed link, emailed code, and **Continue with Google**. - An authenticator-app code is 6 digits and rotates on your device's clock; an emailed second-factor code is valid for 5 minutes. - Setup issues ten one-time backup codes. Generating a new set invalidates the previous set. - **Trust this browser for 30 days** suppresses the prompt only on email + password sign-ins from that browser. - Turning 2FA on or off, and regenerating codes, always requires a confirmation — your password, or an emailed link if your account has none. - Disabling it is reversible: "Your account will only require a password to sign in. You can re-enable 2FA later." ## What does it look like in practice? Your phone goes into a river on Tuesday. Your authenticator app went with it, and its codes are not recoverable from the app store — they lived on the device. You sign in from your laptop with email and password, reach "Two-factor verification", and instead of typing a code you press **Use a backup code instead**. You paste the first unused code from the ten you filed away at setup. You are in, and that code is now spent: nine remain. Still signed in, you go to your security settings, turn 2FA off with your password, then turn it straight back on to pair the authenticator app on your replacement phone. The wizard's third step hands you a fresh set of ten codes, and the nine leftovers from the old set stop working the moment the new set is issued. Had you had no backup codes and no password — a Google-only account — the recovery path would have been **Email me a code** at the challenge screen, which is offered on that route precisely because your inbox was not your first factor. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/docs/account-security/your-privacy-choices-and-notice-at-collection # Your Privacy Choices and Notice at Collection "Your Privacy Choices" and "Notice at Collection" are the two controls Fincanva shows to meet US state privacy law (California's CCPA/CPRA and the similar statutes modeled on it). "Your Privacy Choices" is a button in **Settings → Security** that lets a US resident opt out of the sale or sharing of their personal information at any time; "Notice at Collection" is a link shown beside the consent checkbox at the exact point Fincanva starts collecting data, on sign-up and on re-consent. Both names are quoted here exactly as the app renders them, and both stay in English in every locale Fincanva ships — including Italian — because a US privacy statute names the control by that literal string, not by a description Fincanva is free to translate. **Also seen as:** CCPA opt-out, "Do Not Sell" link ## Why do Your Privacy Choices and Notice at Collection stay in English? Both names are pinned as literal strings in Fincanva's translation catalogues rather than left to translation. The English and Italian catalogues carry the identical value for each, and an automated test guards exactly that pairing, so a future cleanup pass cannot translate either name by mistake. This is not a blanket rule against translating the surrounding copy. The row label and description around the "Your Privacy Choices" button ("Sale and sharing of personal information" / "Vendita e condivisione dei dati personali") are fully localized, and so is every other sentence on the page — only the two proper names named by the law hold still, because translating them would sever the control from the exact legal term a US resident is entitled to see. ## Who sees these two controls? Only a visitor Iubenda — the consent-management platform Fincanva already loads — has determined is covered by a US state privacy law. Nothing in Fincanva's own code decides this — no check on your address, your language, or your country. Fincanva reads the verdict Iubenda has already reached and shows or hides the controls accordingly. The gate wraps the whole "Privacy" section of Settings → Security, heading included: someone the check does not apply to never sees an empty "Privacy" section, and the settings navigation drops its anchor for the same reason. The same principle governs "Notice at Collection" — the link renders nothing for a visitor the check does not cover, and nothing for a covered visitor until Iubenda has actually supplied the notice URL to link to. When the verdict cannot be read at all (an unexpected response from Iubenda's script), Fincanva treats that as "does not apply" and hides both controls rather than risk showing a US-only control to the wrong visitor. Iubenda answers two related questions: whether a US state privacy law covers the visitor at all, and whether California's own law does. Where those two answers differ, Fincanva follows the broader one — does a US state privacy law apply — because that is the question this pair of controls is about; whether California in particular is involved is a narrower question, and the wrong one to gate them on. Under the Iubenda configuration Fincanva runs, the two answers agree for every visitor, so this changes nothing anyone sees today; it decides which answer wins if they ever differ. ## Does this mean Fincanva applies different privacy rules by location? No. The underlying consent regime — what Fincanva asks a visitor to agree to, and what the default is — is the single strictest standard (EU-style opt-in) for every visitor everywhere, with no geographic branch anywhere in the product. Geography decides only whether these two extra controls are visible, never what the consent rules themselves are. A visitor in Germany and a visitor in California both start from the identical opt-in default; the Californian additionally sees a sale/sharing opt-out button and a notice at the moment of signup, because US state law grants that specific pair of rights on top of a baseline that is already stricter than what US law alone would require. A separate, ungated control exists for the regime everyone already has: "Manage cookie preferences" in the same Security page reopens the general cookie-consent layer for withdrawal, visible to every signed-in user regardless of location — it answers the GDPR-style "make withdrawing consent as easy as giving it" requirement, which is not a US-only right. ## Where do I find Your Privacy Choices? In **Settings → Security**, in its own "Privacy" section — present only for a visitor the check above applies to. The button carries the official CCPA/CPRA opt-out mark next to its label and opens Iubenda's preferences layer, where the opt-out is exercised. If that layer cannot be reached, the button shows an inline error rather than doing nothing silently. ## Where do I find Notice at Collection? Beside the consent checkbox, on the sign-up page and again on the "accept terms" re-consent screen — the two places Fincanva collects data, so the notice appears at the point collection starts, as US law requires. It links out to Iubenda's own Notice-at-Collection page — one address Fincanva configures with Iubenda, not a different page per state. ## How does Fincanva handle it? - Both controls are shown only when Iubenda's jurisdiction check reports that US state privacy law covers the visitor; no verdict, or one that cannot be read, hides both. When Iubenda's own second answer — whether California's law applies — disagrees with it, Fincanva follows the broader US state privacy verdict, the question these two controls actually serve. The two answers agree for every visitor under the configuration Fincanva runs, so no visitor's experience differs because of this today. - "Your Privacy Choices" lives in Settings → Security and is reachable at any time, matching the "exercisable whenever" requirement US state law places on this specific right; "Notice at Collection" appears only at the point of collection (sign-up, re-consent), never elsewhere. - Both strings are identical, character for character, in the English and Italian translation catalogues. - The consent regime that "Your Privacy Choices" and "Notice at Collection" sit beside is the same strict opt-in default for every visitor; nothing in the regime itself varies by geography. - A separate "Manage cookie preferences" control, ungated by geography, is available to every signed-in user for withdrawing general cookie consent. ## What happens to two visitors who sign up on the same day? A visitor in Los Angeles opens the sign-up page. The consent checkbox is there from the start — it never waits on anything — and once Iubenda's script resolves her jurisdiction, "Notice at Collection" appears linked beside it. She creates the account, and later, from Settings → Security, she finds a "Privacy" section with a "Your Privacy Choices" button she can use at any time to opt out of the sale or sharing of her data. A visitor in Milan opens the same sign-up page the same day. His consent checkbox is identical — the same opt-in default, the same required agreement — but no "Notice at Collection" link appears beside it, because Iubenda's verdict for his jurisdiction does not trigger US state privacy law. Later, in his own Settings → Security, the "Privacy" section itself does not render at all: no heading, no button, and no anchor for it in the settings navigation, because that right is not one Italian law grants him. He can still reach "Manage cookie preferences" on the same page, since that control answers a different, geography-independent question. ## Related - [Account deletion](/docs/account-security/account-deletion) — the other Settings → Security control governed by a strict, no-exceptions timeline. - [Two-factor authentication](/docs/account-security/two-factor-authentication) and [Active sessions](/docs/account-security/active-sessions) — the other account-security controls on the same page. Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/changelog # A plan refusal now says what's wrong **2026-09-25** · billing · 2026.09 A refusal that names a plan limit — on Backtest, Copy, Clone, Combine or Save — now names what's wrong: the limit itself, your strategy's value and your plan's, for example "it starts in 1990, Advanced starts from 2000" or "it has 6 strategies, Advanced allows 5", followed by which plan would cover it ("Switch to Ultimate"). The padlock tooltip on a strategy row and the set-aside panel list every breach this way, not only the first. See [plan compliance](/docs/backtesting/plan-compliance). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/changelog # Choose which strategies keep running when your plan shrinks **2026-09-11** · billing · 2026.09 When a plan change means your plan no longer covers every [live](/docs/getting-started/mark-live) strategy you follow, you are asked which ones to keep — at the moment it happens, not after. The dialog states how many live strategies you follow against how many your plan covers, and pre-selects the strategies you used most recently; the rest stop being followed but stay in your library with their history, and go live again once your plan covers them. See [what each plan includes](/docs/account-security/what-each-plan-includes). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/changelog # Old-platform customers sign in with the same account **2026-09-21** · account-auth · 2026.09 If you had an account on Fincanva's earlier platform, you sign in with that same account today — there is nothing new to create. On sign-in you find the subscription you were already paying for, and your strategies, portfolios and screeners are where you left them. See [get started with Fincanva](/docs/getting-started/get-started-with-fincanva-in-five-steps) and [how to read your plan](/docs/account-security/how-to-read-your-plan). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/changelog # The Free plan keeps more saved strategies **2026-09-25** · billing · 2026.09 The Free plan now lets you keep more saved strategies: Set by your plan: 2 on Free and 999 on Starter, Advanced, Ultimate and Professional. See [what each plan includes](/docs/account-security/what-each-plan-includes). See [what each plan includes](/docs/account-security/what-each-plan-includes). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3) --- URL: https://fincanva.com/changelog # Usage and Change plan are redesigned **2026-09-25** · billing · 2026.09 Settings → Usage now leads with what your plan gives you and what each plan above yours adds: **What you have** lists what's already unlocked, **Still to unlock** lists what a higher plan would add, both read from the same ledger the pricing page reads. See [what your Usage page tells you](/docs/account-security/what-settings-usage-tells-you). Billing's **Change plan** dialog is now three plan cards, each with its price and what it includes, instead of one long comparison, with a line under each button saying when you'd be charged. See [what each plan includes](/docs/account-security/what-each-plan-includes). Fincanva is for education and illustration only. It is not personalised financial advice, and past or simulated results do not predict future ones. [Read the Terms Addendum](https://fincanva.com/terms/addendum#section-3)