How to Use ATR: Volatility, Stop Distance and Position Size

What ATR measures

ATR (Average True Range) is an indicator that measures, in price units, how far one bar usually moves. It was introduced by Wilder, who also created RSI, and it looks only at the size of moves, not whether price will rise or fall. If Bitcoin's daily ATR is $2,000, it means the daily range has averaged around $2,000 over the last two weeks or so. The value is widely used as a basis for deciding how far away to place a stop and how large a position to take to carry the same risk. ATR is useful because the same price move means very different things depending on the market and the period. A 3% drop is a big event in a market that usually moves 1% a day, but an ordinary day in one that usually moves 5%. The threshold at which participants feel 'that was a big move' is itself tuned to the usual swings, and ATR puts that threshold into a number. The order to look at it is: first whether the current ATR is high or low compared with the last few months for that market, then what percentage of price it is. Calling an ATR big or small from the raw number alone means nothing across markets at different price levels.

True range (TR): why the previous close is included

The raw material for ATR is the true range (TR) calculated for each bar. TR is the largest of the three values below. The previous close is included because of gaps. If the previous bar closed at 100 and the next bar opened at 106 and traded between 105 and 110, high − low is only 5, but price actually moved from 100 to 110, so TR is 10. Crypto trades around the clock, so the next bar usually opens near the previous close, and in most cases TR equals high − low. Measuring without gaps understates risk. Someone holding a position from the previous close has already seen their profit or loss change by the size of an overnight gap, but if you look only at high − low, that move disappears from the record. The commodity futures markets for which Wilder originally built the indicator also closed and reopened, so gaps were common. As in the chart, the second value is the largest when there is a gap up and the third when there is a gap down, and if the previous close lies within the bar's range, high − low is the largest of the three.

• High − low: how far price moved within the bar
• |High − previous close|: grows when there is a gap up
• |Low − previous close|: grows when there is a gap down
• The first bar has no previous close, so only high − low is used

ATR: Wilder's average of TR

ATR is the TR averaged using Wilder's method, and TradingView's default is 14 bars. The first ATR is the simple average of the first 14 TR values; after that it continues as ATR = (previous ATR × 13 + current TR) ÷ 14. It is an exponential average (RMA) that gives each new TR only 1/14 of the weight, so old values do not drop out all at once as in a simple 14-bar average but fade gradually. It takes a little over 9 bars for the effect of one large bar to fall by half. This is why averaging TR with a simple mean in a spreadsheet gives a slightly different value from TradingView. The method has trade-offs. A simple average drops sharply in a step on the day a large bar from 14 bars ago leaves the window, while Wilder's average comes down smoothly without such steps. In return, an ATR that has grown shrinks slowly and shows a larger-than-usual value for a while after a sudden move has passed. And because the calculation carries forward from the first bar, the early values can differ slightly depending on how many bars the chart has loaded; with long enough data that difference disappears.

It is in price units, so convert it to a percentage

ATR is in the same units as price, so it cannot be compared directly between coins. That is why it is converted to ATR ÷ close × 100, a percentage of price. At a price of $60,000 with an ATR of $1,800 it is 3%; at a price of $0.50 with an ATR of $0.03 it is 6%, so although the number is small, the second one swings twice as much. Even for the same coin, ATR grows as price rises several times over, so a percentage is also the right way to compare across years. Changing the timeframe changes ATR too. Daily ATR is larger than 1-hour ATR, but not 24 times larger, because the ups and downs within a day partly cancel out. This easily leads to mistakes when you mix timeframes. If you set a stop distance from 1-hour ATR and then hold the position for several days, the stop ends up too close compared with a day's worth of swings. Conversely, using daily ATR to set a stop for a trade lasting a few hours puts it too far away. The basic rule is to use ATR from the timeframe that matches how long you will hold, and the percentage version is useful for lining up markets side by side to see how much each one usually swings.

Volatility comes in clusters

Price volatility tends to come in stretches: large moves follow large moves, and quiet periods follow quiet periods. This property is called volatility clustering, and it is widely observed not only in crypto but in stocks and currencies as well. It is the reason recent ATR is used as a gauge of how much price may swing in the near future. But as the chart shows, ATR grows over several bars after a sudden move begins and stays high for a while even after price returns to where it was. As an average it always lags, and a low ATR is only a record that things have been quiet so far, not a sign they will stay quiet. Clustering happens because participants' reactions chain together. A large move triggers stops and forced liquidations, and those orders push price further, enlarging the next bar's move. The days after news breaks, when interpretations split and big orders flow both ways, create the same pattern. So right after ATR jumps to several times its usual level, swings often do not shrink straight away even if price returns to where it was. Conversely, many people read a long stretch of ATR at the bottom, much like a Bollinger squeeze, as a state in which movement can suddenly grow once the balance breaks.

Setting stop distance as a multiple of ATR

ATR is widely used to set stop placement. The idea is to place the stop some multiple of ATR away from the entry price so that ordinary swings alone do not hit it. Two or three times are common examples, but there is no fixed value: a small multiple gets hit by noise often, and a large one makes each loss bigger. Once the stop distance is set, position size is calculated as the loss you can accept ÷ the stop distance. If volatility doubles, the stop distance doubles and the size halves, so the amount you can lose in one trade stays the same. The detailed calculation is covered in the article on stop distance and position size. The core of this idea is that the stop is placed according to 'how much the market usually swings', not according to your own circumstances of 'how much I can afford to lose'. Your circumstances are handled with position size, not stop distance. A common mistake is doing it backwards: deciding the size first and then, out of fear of losses, placing the stop much closer than ATR, where ordinary swings easily hit it. Many people also adjust the stop by looking at nearby support and resistance or the previous low, rather than relying on the ATR multiple alone.

• Example: you have decided you can accept a loss of $1,000 per trade
• Price $100, ATR $4, 2× → stop at $92 (distance $8)
• Size = 1,000 ÷ 8 = 125 units
• If ATR is $8, the distance is $16 → 62.5 units

Indicators built on ATR

ATR is also used as an ingredient in other indicators. Supertrend draws a trailing line a multiple of ATR (TradingView's default is a 10-bar ATR and a multiple of 3) away from (high + low)/2, and treats a close beyond that line as a change in direction. A Keltner Channel is a band set a multiple of ATR above and below an exponential moving average; this site's Bollinger Band Squeeze Scanner flags a squeeze when the Bollinger Bands move inside a Keltner Channel of EMA20 ± 1.5 × ATR(20). The futures liquidation price calculator shows stops placed 1.5, 2 and 3 times ATR(14) away, and whether each stop would be reached before the liquidation price. All of these use the same idea: 'some multiple of the usual swing'. These indicators inherit ATR's characteristics as they are. Because ATR grows late after a sudden move, Supertrend's trailing line also drifts away from price for a while right after a sharp move, and in quiet stretches ATR is small, so the line hugs price and flips often. The difference between Keltner Channels and Bollinger Bands also comes from here. Bollinger Bands use the dispersion of closes and Keltner Channels use bar ranges, so in stretches with many gaps and wicks the two bands move differently.

What ATR does not tell you

ATR does not tell you direction. It grows the same way whether price keeps plunging or keeps surging, so the fact that ATR has risen does not by itself mean a trend has started or ended. And because it is a 14-bar average, extreme moves such as a moment when liquidations cascade get buried in the average. A stop set at a multiple of ATR is also only based on past swings, and in a sudden move the order can be filled at a worse price than the stop. ATR is a ruler for the size of risk, not a value that promises anything about future moves. One common mistake is reading a rising ATR as a sign of falling prices because ATR often rises in down markets. In markets where sharp drops tend to be shorter and more violent than sharp rises, such scenes catch the eye often, but the ATR formula contains no direction. Another is assuming that a low ATR means low risk. A low ATR is a record that things have been quiet lately, so if you greatly increase position size on top of it, losses grow along with it the moment the calm breaks.

How it looks different in crypto and stocks

Because ATR includes gaps in TR, differences in market structure show up directly in the number. In stocks, overnight news is priced into the next day's open all at once after the regular session ends, so on some days a large part of the daily TR comes from the gap rather than from intraday movement. Examples are Samsung Electronics or SK hynix gapping open the day after an earnings report or a big move in the US semiconductor index, or a large US tech stock reporting after the close and opening far away the next day. Intraday stop orders cannot protect against such gaps, so even a stop set at an ATR multiple can be jumped over at the open. Crypto trades around the clock, so gaps are rare, but it moves on weekends too, and long wicks often appear during thin overnight hours. Korean stocks have a daily price limit (±30%), which caps the daily TR in both directions, while US stocks and crypto have no such cap. With 1-hour ATR on stocks, keep in mind that the big bars right after the open and the small bars around midday mix together, so the swings are uneven even within a day. Crypto ATR as a percentage of price tends to be larger than that of large-cap stocks, so even with the same stop multiple, position size can differ a great deal.

A practical checklist

When you look at ATR on a live chart, first remember that the last bar's value is not final. The TR of a forming bar grows as its high and low widen, so ATR looks small right after a bar opens and large during a bar with a sudden move, and only settles when the bar closes. With Wilder's averaging the effect of one bar is cut to 1/14, but using ATR from closed bars to set stop distance and size keeps things steadier. If you change your stop distance every time ATR jumps during the bar, the reference keeps moving and the risk limit you first set loses its meaning. The mistake of seeing the small TR of a bar that has just opened and thinking the market is quiet right now comes from the same cause. Here is an order of checks for the screen.

• Check that the timeframe matches how long you will hold
• Convert ATR to a percentage of price and compare it with recent months
• Calculate stop distance and size from the ATR of closed bars
• Check whether a gap or liquidation-driven spike in the last 14 bars is inflating ATR
• Look for support and resistance near a stop set at an ATR multiple
• For stocks, check gap-risk dates such as earnings; for crypto, weekends and thin hours
• Do not use the size of ATR as a basis for judging direction