What it means
Average true range answers a simple question: how much does this market actually move? Unlike a plain high-minus-low range, the true range also captures overnight gaps by comparing today's range with the distance from yesterday's close to today's extremes, and averaging that over a period, conventionally 14 days, produces the ATR.
The indicator comes from J. Welles Wilder, who introduced it in his 1978 book on technical trading systems.
It belongs to the family of tools that measure volatility rather than direction, so ATR says nothing about whether prices will rise or fall, only how energetically they are moving. Reference material in university trading courses defines it exactly this way.
Traders put the number to three main uses. Position sizing scales trade size inversely to ATR, so volatile markets get smaller positions for the same money risk, and stop placement sets protective stops at a multiple of ATR beyond entry, wide enough to survive normal noise.
Breakout confirmation treats moves larger than the recent ATR as meaningful rather than random drift. Interpretation is relative, not absolute.
An ATR of $2 on a $20 stock is a wild market, while the same $2 on a $200 stock is calm, so comparisons only make sense within one instrument over time and traders watch ATR rising or falling rather than reading any level as inherently high or low. Rising ATR typically accompanies stress or excitement and falling ATR accompanies quiet consolidation, and because volatility clusters, many systems treat a jump in ATR as a regime change and reduce exposure automatically.
ATR also underlies several derived tools traders meet later. Chandelier exits hang stops from peak prices by an ATR multiple, volatility breakout systems trigger entries at ATR-scaled distances, and risk-parity position sizing divides target risk by ATR, so learning the base measure once opens the door to a whole family of techniques built on it.
For managers outside trading, ATR is a useful mental model even without charts: any forecast that ignores how much a quantity normally swings will be surprised constantly, so sizing commitments, buffers and deadlines to the observed range of the underlying variable is the ATR habit applied to ordinary planning. The indicator ages gracefully because it asks so little, needing no forecast, no fundamental input and no market regime assumption, only honest measurement of recent movement.
In a field crowded with elaborate signals, that humility is exactly why risk systems still reach for it decades after its invention.
In practice
Real-world examples.
Example
A currency trader sets a stop three times the 14-day ATR below entry to avoid being shaken out by noise. With an ATR of 60 pips, the stop sits 180 pips away. She sizes the position so that a stop-out costs her a fixed fraction of her account.
Example
A systematic fund cuts position size in half when ATR doubles, keeping risk per trade constant. Its managers do not forecast the volatility jump, they simply respond to it. The approach keeps losses on volatile days in line with those on quiet days.
Example
An analyst notes ATR climbing for weeks as evidence that a quiet market is entering a volatile regime. She tells the risk committee to expect larger daily swings and to widen buffers on planned hedges. The warning arrives before the headline moves do.
Formula
Calculation
True range = max(high - low, |high - prior close|, |low - prior close|). ATR = average of the true range over N periods, conventionally 14, and Wilder's smoothing updates it as new ATR = ((prior ATR x 13) + current true range) / 14.
Worked example. A stock closed yesterday at $100 and today trades between a low of $101 and a high of $104. The plain range is $104 - $101 = $3, but the true range is max($3, |$104 - $100| = $4, |$101 - $100| = $1) = $4, because the overnight gap counts. Daily true ranges of $1.20, $1.50 and $1.80 give a 3-period ATR of ($1.20 + $1.50 + $1.80) / 3 = $1.50.
To use it, a trader buys at $50 with a 14-day ATR of $1.50 and sets a stop 3 ATR below entry: 3 x $1.50 = $4.50, so the stop is at $45.50. Risking $1,000 on the trade means buying $1,000 / $4.50 = about 222 shares. If ATR doubled to $3.00, the same rule would give a stop distance of $9.00 and a position of about 111 shares, half the size.Case study
Seen in the real world.
This is a fictional example. Callisto Trading, an invented firm, sizes every position at 1% of capital risked over a 2-ATR stop. With $1,000,000 of capital that is $10,000 of risk, and a currency pair with an ATR of 0.50 gives a stop distance of 1.00 and a position of 10,000 units.
When the pair's ATR doubles to 1.00 during a central bank crisis, the stop distance becomes 2.00 and the system automatically halves the position to 5,000 units. The firm's loss on the eventual stop-out is again about $10,000, matching its ordinary losing trades instead of dwarfing them. A rival desk using fixed-size positions takes twice the loss on the same move.
Watch out
Common mistakes.
- Reading ATR as a direction signal, when it measures only volatility and says nothing about which way prices will go. It pairs with trend tools, not instead of them.
- Comparing ATR levels across different instruments, when the number only has meaning relative to that market's own price and history. Normalise by price before comparing.
- Setting fixed-price stops regardless of ATR, so normal volatility triggers stops that were never given room to work. Multiples scale the stop to the market.
Questions
People also ask.
What period is standard for ATR?
Fourteen periods is the convention from Wilder's original work, though traders adjust it for faster or slower responsiveness. Shorter periods react faster to regime changes.
Does a high ATR mean prices will fall?
No. High ATR means wide movement in either direction; it often accompanies declines but predicts no direction by itself. Direction comes from other tools.
How does ATR differ from standard deviation?
ATR measures the average bar-to-bar range including gaps, while standard deviation measures dispersion of returns around their mean. Both describe volatility from different angles.
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