Direct Answer
Average Daily Range is a volatility measure used to measure dispersion, range, implied uncertainty, or expansion/contraction in price movement. The production page must define the exact calculation convention before interpreting higher or lower readings, because platform and provider implementations can differ.
Average Daily Range: Formula, Meaning, Signals, Examples and How to Use It
How Is Average Daily Range Calculated?
Average Daily Range is the mean of the daily high-low range over a chosen number of days. It captures the typical intraday distance the instrument travels, ignoring gaps between sessions.
Formula: ADR = (1 / n) x sum of (High_i - Low_i) over the last n days
Inputs:
- Daily high and low prices
- Number of days n (commonly 14 or 20)
Worked example. Daily ranges of 2.1, 1.8, 2.4, 2.0 and 1.7 average 2.00 over five days. The inputs are illustrative numbers, not market data.
Reading it. It is a simple yardstick for how far price usually moves in a day, used for sizing stops or judging whether today's range is large relative to normal. Some sources express it as a percentage of price instead of in price units.
Limits. It ignores overnight gaps, which the true range includes, and it is unbounded by outliers: one very wide day lifts the average for the whole window. Price-unit values are not comparable across instruments.
Indicator overview
| Attribute | Value |
|---|---|
| Category | Volatility |
| Asset classes | Stocks, ETFs, Indexes, Options, Futures, Forex, Crypto, Commodities |
| Output type | Line/scalar |
| Parameters | Varies by implementation; document exact settings on use |
What is Average Daily Range?
Average Daily Range is a volatility measure used to measure dispersion, range, implied uncertainty, or expansion/contraction in price movement. The production page must define the exact calculation convention before interpreting higher or lower readings, because platform and provider implementations can differ.
For Swoopr, the canonical profile separates definition, calculation, interpretation and decision use. That keeps readers from collapsing a descriptive metric into a trading strategy. An indicator can describe trend, momentum, volatility, participation, positioning or risk without providing a complete entry, exit, sizing or portfolio decision.
What does it measure?
Average Daily Range measures specific market properties in the Volatility domain. The practical value is repeatability: the same inputs and formula can be applied across a defined dataset, allowing users to compare readings through time or across instruments when the calculation convention is held constant.
How to read Average Daily Range
Interpretation depends on the market property being measured. A descriptive reading is not automatically predictive. The same numerical state can lead to different outcomes in a strong trend, quiet range, event-driven gap or illiquid market. Always combine with context from price structure, volume, and broader market regime before drawing conclusions.
Strengths
- A plain mean of high-minus-low gives an intuitive typical day's travel in the instrument's own price units.
- Only the high and low of each day are needed, so the figure can be computed from any daily bar series without a prior close.
- Reproducible when the formula and data convention are fixed.
Weaknesses and limitations
- Each day carries equal weight, so a change in regime shows up slowly while old wide days remain in the average.
- Sessions with abnormal hours, such as half-days, have narrower ranges and pull the mean down without any change in volatility.
- 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. Where multiple valid definitions exist, Swoopr states the alternatives and the reason for selecting its primary convention.
Frequently Asked Questions
Is Average Daily Range a buy or sell signal?
No. It is a simple yardstick for how far price usually moves in a day, used for sizing stops or judging whether today's range is large relative to normal. It ignores overnight gaps, which the true range includes, and it is unbounded by outliers: one very wide day lifts the average for the whole window. 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 Average Daily Range?
Average Daily Range takes these inputs: daily high and low prices; number of days n (commonly 14 or 20). 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 Average Daily Range be used by itself?
It ignores overnight gaps, which the true range includes, and it is unbounded by outliers: one very wide day lifts the average for the whole window. Price-unit values are not comparable across instruments. For that reason it is read next to measures of direction, participation, valuation, liquidity and risk, not alone.
Does Average Daily Range work on every timeframe?
The calculation (ADR = (1 / n) x sum of (High_i - Low_i) over the last n days) 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 Average Daily Range give false signals?
Each day carries equal weight, so a change in regime shows up slowly while old wide days remain in the average. Sessions with abnormal hours, such as half-days, have narrower ranges and pull the mean down without any change in volatility. Lag, noise and regime changes add to this, because market participants react to new information after the reading is calculated.
How should Average Daily Range be backtested?
Rebuild Average Daily Range from daily high and low prices 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.