---
title: "Value at Risk"
description: "Value at Risk (VaR) is the daily loss that a strategy's worst 5% of days reach: on 95% of days it lost less. Fincanva shows it historical and Gaussian."
canonical_url: "https://fincanva.com/docs/analysis/value-at-risk"
last_updated: "2026-09-25"
md_url: "https://fincanva.com/docs/analysis/value-at-risk.md"
---

# 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)