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.

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, the Sortino ratio and tracking error, so those ratios are all built on the same annualization. See annualization for how returns, as opposed to dispersion, are put on a yearly scale.

Defaults in Fincanva

• The metrics table shows volatility in the Volatility and risk group as the row Volatility, as a percentage; the group heading, the KPI strip, and the Strategy analytics table all use the same name for the same quantity.
• 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.

Worked example

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 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 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, a separate reading.

These figures describe what a strategy would have done on historical data, not what it will do, and past volatility is not a limit on future variability. Fincanva provides no financial advice — see Is this financial advice?.