--- title: "Range-Based Volatility: Formula, Meaning" description: "Range-based volatility estimates volatility from the high-low range of each bar rather than from closing prices alone. The simplest form scales the average..." canonical: https://www.getswoopr.com/indicators/volatility/range-based-volatility/ source: "Swoopr Investment: https://www.getswoopr.com" --- ## Direct Answer > Range-based volatility estimates volatility from the high-low range of each bar rather than from closing prices alone. The simplest form scales the average log range by a constant tied to the expected range of a Brownian motion. It uses the fact that a wide range implies large movement, even when the close ends near the open. # Range-Based Volatility: Formula, Meaning, Signals, Examples and How to Use It ## How Is Range-Based Volatility Calculated? Range-based volatility estimates volatility from the high-low range of each bar rather than from closing prices alone. The simplest form scales the average log range by a constant tied to the expected range of a Brownian motion. **Formula:** `sigma_bar ~ mean(ln(High / Low)) x sqrt(pi / 8), about 0.627 x mean log range; annualize with sqrt(252)` **Inputs:** - High and low for each bar - Window length n - Scaling constant (sqrt(pi / 8) for the mean-range form) **Worked example.** An average log high-low range of 0.022 corresponds to a per-bar volatility of about 1.38%. The inputs are illustrative numbers, not market data. **Reading it.** It uses the fact that a wide range implies large movement, even when the close ends near the open. More refined estimators (Parkinson, Garman-Klass) use squared ranges and extra price points for better efficiency. **Limits.** The scaling assumes zero drift, continuous trading and no gaps; discrete sampling makes observed ranges too small, so results lean low. The mean-range form is also less efficient than the squared-range estimators. ## What is Range-Based Volatility? Range-based volatility estimates volatility from the high-low range of each bar rather than from closing prices alone. The simplest form scales the average log range by a constant tied to the expected range of a Brownian motion. ## How to use Range-Based Volatility It uses the fact that a wide range implies large movement, even when the close ends near the open. More refined estimators (Parkinson, Garman-Klass) use squared ranges and extra price points for better efficiency. A reading alone is never a buy or sell signal; it needs context from price structure, volume, volatility and the broader market regime. ## Strengths - Scaling the mean log range by a constant converts a simple range average into a volatility figure under a stated Brownian assumption. - Because it averages ranges rather than squaring them, a single wide bar affects the estimate less than under squared-range estimators. - Reproducible when the formula and data convention are fixed. ## Weaknesses and limitations - The per-bar figure must be scaled by the square root of bars per year, so intraday and daily bars need different annualization factors. - Bias from discrete sampling changes with bar size, so results from a few wide bars and many narrow bars are not equally biased. - Correlated indicators can create false confidence by repeating the same underlying information. ## Editorial and risk note This page is educational content, not individualized investment advice. It should not imply guaranteed prediction, accuracy or outperformance. ## Frequently Asked Questions Is Range-Based Volatility a buy or sell signal? No. It uses the fact that a wide range implies large movement, even when the close ends near the open. The scaling assumes zero drift, continuous trading and no gaps; discrete sampling makes observed ranges too small, so results lean low. A trade built on it still needs a trigger, an invalidation rule, a position size and realistic execution assumptions. What is the best setting for Range-Based Volatility? Range-Based Volatility takes these inputs: high and low for each bar; window length n; scaling constant (sqrt(pi / 8) for the mean-range form). There is no universal best setting for the tunable ones, so test them across instruments, regimes and out-of-sample periods and favor stable parameter regions over one historical winner. Can Range-Based Volatility be used by itself? The scaling assumes zero drift, continuous trading and no gaps; discrete sampling makes observed ranges too small, so results lean low. The mean-range form is also less efficient than the squared-range estimators. For that reason it is read next to measures of direction, participation, valuation, liquidity and risk, not alone. Does Range-Based Volatility work on every timeframe? The calculation (sigma_bar ~ mean(ln(High / Low)) x sqrt(pi / 8), about 0.627 x mean log range; annualize with sqrt(252)) can be run on any bar size, but behavior is not portable: a reading on a five-minute chart describes a very different market window from the same reading on a daily chart. Validate the exact timeframe before relying on it. Why does Range-Based Volatility give false signals? The per-bar figure must be scaled by the square root of bars per year, so intraday and daily bars need different annualization factors. Bias from discrete sampling changes with bar size, so results from a few wide bars and many narrow bars are not equally biased. Lag, noise and regime changes add to this, because market participants react to new information after the reading is calculated. How should Range-Based Volatility be backtested? Rebuild Range-Based Volatility from high and low for each bar using point-in-time data, write the rules before testing, include delisted securities where relevant, model realistic fills and costs, reserve a validation sample and compare with a simpler baseline. ## References - [The Journal of Business: On the Estimation of Security Price Volatilities from Historical Data (1980)](https://doi.org/10.1086/296072) S Swoopr Editorial Team The Swoopr Editorial Team produces independent investment education, research, and tools for understanding markets, evaluating opportunities, and managing risk. All content is educational only and does not constitute personalized investment advice. 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