Average TRue Range (ATR)
Analysis:
The Average True Range (ATR) was created by J. Welles Wilder. The same J. Welles Wilder who created the Relative Strength Index (RSI). ATR is an indicator of volatility within the market, it does not provide any indication of market direction.
ATR is a measure of the true range values over a specified period of time. J. Welles Wilder recommends using a 14 period ATR thereby calculating the average true range of the previous 14 candles.
The average true range is a measure of the current candle's volatility compared to the close of the previous candle. It takes into consideration:
- Current high - current low
- Current high - previous close
- Current low - previous close
The ATR takes into consideration the highest of all three of these and averages these across the selected period (recommended 14).
The ATR can be described as a moving average of the true ranges of a specified period. As mentioned before, it is not designed to inform or predict market direction. The closest to this use case would be to use the ATR as a trend strength indicator. Generally speaking, the higher the ATR, the greater the strength of the current trend.
ATR is best utilised to determine stop loss and take profit levels once a trading opportunity has already been identified. In its simplest form, ATR could be described as the average price move of a trend throughout a specific period. Therefore, ATR could be used as a tool for placing stop loss and take profit levels based on the volatility of the market at that time. This means that it is a self-adjusting stop loss/take profit tool, adjusting for the market conditions at the time of a trade. This is very powerful compared to using a static stop level for every trade i.e. 20 pips. In a more volatile market, using an ATR based stop loss level will allow for greater room for movement as price swings are more extreme. The opposite is true in a less volatile market whereby, price movements are less extreme, reducing the ATR value which in turn makes stop losses tighter. This can greatly increase the Risk:Reward ratio.
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