Volatility & bandsHistorical Volatility · HV
The realized volatility of returns over a past window, usually annualized as a percent.
Works in most conditionsEngine-computed on a fixed sample series
What it is
Historical volatility, often abbreviated HV and also called realised volatility, measures how much an asset has actually moved over a past window, expressed as a percentage. It is a backward-looking statistic that answers a concrete question: over the last stretch of time, how large were this asset's day-to-day price swings? Unlike implied volatility, which is derived from option prices and reflects the market's expectation of future movement, historical volatility is computed directly from the price history that has already happened. It is usually annualised so that a 20-day window and a 60-day window can be compared on the same scale, and quoted as a yearly percentage such as 20 percent. Traders use it to set expectations for how far price is likely to range, to size positions relative to how turbulent the market has been, and to judge whether options look expensive or cheap against the movement the asset has genuinely delivered. It is a measure of magnitude only, saying nothing about direction.
How it is calculated
Historical volatility is the standard deviation of the asset's returns over a lookback window, scaled to an annual figure. The standard approach uses logarithmic daily returns — the natural log of each day's close divided by the previous close — because log returns are additive over time and behave well statistically. You take those daily log returns over the chosen window, commonly 20 trading days, and compute their standard deviation, which measures how much they scatter around their average. That gives a daily volatility figure, which is then annualised by multiplying by the square root of the number of trading periods in a year, typically the square root of 252 for daily data. The square-root scaling reflects the statistical fact that volatility grows with the square root of time under the usual assumptions. The result is the annualised percentage traders quote; different lookback windows or return frequencies will yield different numbers from the same price series, so the window is always part of the definition.
Reading it, step by step
Read the level of historical volatility relative to the asset's own history rather than as an absolute — a 30 percent reading is calm for one instrument and wild for another. A rising HV means the market has been getting choppier, with larger daily swings, while a falling HV means it is calming down and ranges are contracting. Comparing HV across windows tells a story: if short-window HV is well above long-window HV, volatility has spiked recently, and if it is well below, the market has quieted lately. The most valuable comparison is often against implied volatility priced into options — when HV sits far below IV, options look rich relative to recent realised movement, and when HV sits above IV, options may be cheap. Because volatility tends to cluster and mean-revert, an unusually low HV frequently precedes an expansion, and an extreme high tends to subside, so the extremes are more informative than the middle.
Best timeframes and settings
Historical volatility is most commonly computed on daily data with a 20-day window, which roughly corresponds to a trading month and gives a responsive but reasonably stable read. Shorter windows such as 10 days react quickly to a change in conditions but are noisier and can whipsaw, while longer windows such as 60 or 90 days give a smoother, more stable estimate that lags real shifts. The choice of window is the key setting and directly controls the responsiveness-versus-stability trade-off, so many traders watch several windows at once to see whether recent volatility is above or below the longer-term norm. The annualisation factor depends on the data frequency — the square root of 252 for daily bars, or the appropriate root for weekly or intraday data — and must match the return interval. Because the annualised figure depends heavily on the lookback, a short and a long window can tell genuinely different stories at the same moment, which is a feature to exploit rather than a flaw to ignore.
When and where to use it
Use historical volatility to set realistic expectations for range, to size positions inversely to turbulence, and to compare realised movement against the implied volatility in options. It applies to any asset with a price history — stocks, indices, FX, commodities, crypto — and is a core input to volatility-scaled risk management, where you allot less capital when realised volatility is high. It is especially useful for spotting volatility regimes: unusually compressed HV often flags a market coiling before an expansion, while extreme HV flags stress that tends to revert. It is not a directional tool and should never be used to predict which way price will go. Avoid over-relying on a single window, since the figure is sensitive to the lookback, and remember it is purely backward-looking, so it cannot anticipate a shock. It is best used as a gauge of the volatility environment that shapes position size and expectations rather than as a trade trigger.
Strategies that use it
Volatility-scaled sizing: compute annualised HV and set position size inversely to it, taking larger positions when realised volatility is low and trimming exposure when it is high, so each trade risks a roughly constant amount regardless of conditions. Compression-expansion strategy: watch for HV to fall to an unusually low level relative to its own history, mark the market as coiled, and prepare to trade the direction of the eventual expansion with a stop sized off the widening range. Volatility mean-reversion in options: compare HV against implied volatility, and when IV sits far above recent HV, favour option-selling structures that profit if realised movement stays subdued, or the reverse when IV is unusually low relative to HV. In each case HV informs risk sizing, regime read, or relative value rather than pointing a direction, so it is paired with a separate directional trigger or an options structure that profits from the volatility view itself.
Combining it with other indicators
Historical volatility pairs naturally with other volatility measures and with directional tools. Standard deviation is its building block, and Bollinger Bands — built from standard deviation — visualise the same information as expanding and contracting bands around price. Average True Range gives a complementary, price-based read on range that folds in gaps, so comparing ATR and HV can flag when overnight jumps are driving movement. The most important companion for many traders is implied volatility from the options market, since the HV-versus-IV relationship drives volatility trading and reveals whether options are rich or cheap. Because HV is directionless, a trend tool such as a moving average or ADX supplies the direction once HV has characterised the environment. Chaikin Volatility, which measures the rate of change of a smoothed range, can corroborate whether volatility is expanding or contracting alongside HV.
Where it fails
Historical volatility is entirely backward-looking, so it says nothing about direction and nothing about a coming shock — it can read reassuringly low right before a violent move, which is the classic trap for anyone who mistakes calm history for future safety. The annualised figure depends heavily on the lookback, so short and long windows can disagree sharply at the same moment, and reporting a single number without stating the window is misleading. Extreme past events remain in the window until they roll off, so a single wild day can keep the reading elevated long after conditions have normalised, and its departure can drop the figure abruptly. Traders also misuse it as a directional or predictive signal when it is neither. The defences are to watch multiple windows, to treat low HV as a warning of possible expansion rather than a guarantee of calm, to compare against implied volatility for a forward-looking cross-check, and to pair it with a directional tool for any actual trade.
A worked example
Suppose you compute 20-day historical volatility on a stock and find that the standard deviation of its daily log returns over that window is 0.012, meaning a typical day moved about 1.2 percent. To annualise, multiply by the square root of 252, which is about 15.87, giving 0.012 times 15.87 equals roughly 0.19, or 19 percent annualised volatility. If that same stock's 60-day HV is 28 percent, the shorter window sitting well below the longer one tells you the market has quieted recently relative to its own norm — a compression that often precedes an expansion. If at-the-money options on the stock are implying 35 percent volatility, the gap between 19 percent realised and 35 percent implied suggests options are pricing in far more movement than the stock has lately delivered, which an options trader might read as options looking rich. A position trader, meanwhile, seeing the low realised volatility, might size a directional trade a little larger while keeping a stop wide enough to survive the expansion the compressed HV is warning about.