---
title: "Alpha"
description: "Alpha is the return a strategy earns beyond what its market exposure explains; Fincanva does not currently display an alpha metric anywhere."
canonical_url: "https://fincanva.com/docs/analysis/alpha"
last_updated: "2026-07-25"
md_url: "https://fincanva.com/docs/analysis/alpha.md"
---

# 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.

*Backtests show what would have happened — not what will. Fincanva provides no financial advice — see [Is this financial advice?](/docs/investing-theory/is-this-financial-advice).*