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Adaptive moving average (AMA) considered as one of the newer moving average tool for finding trend changes. AMA was developed to overcome the disadvantages of other moving averages (simple, exponential and weighted moving averages); especially their time lag in predicting the trends and the generation of false trading signals. Although there is not much evidence that adaptive moving average offer better results than others, it is a very good indicator when used in conjunction with other tools.


Adaptive moving average is a moving average changing its sensitivity with price fluctuations. Like exponential and weighted moving average it gives more weight to new price changes. AMA becomes more sensitive when price is moving in a direction – stays farther to current price; and becomes less sensitive when price is in volatility – stays close to current price. Just like other moving averages, buy signals are generated when prices goes above AMA and sell signals are generated when prices moves below AMA.

There are different weight factors available for calculating adaptive moving average. The most used one is the Efficiency Ratio (ER) by Perry Kaufman. ER of Kaufman Adaptive Moving Average measures the strength of the trend by giving more weight to recent day; the values range from -1.0 to +1.0. The formula for calculating ER is calculated as total price change for a period (usually 10 days) divided by sum to absolute price change for each bar.

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