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In order to combine the advantages of both the slower and faster moving averages, Perry Kaufman, market technician, money manager and author, developed the adaptive moving average (AMA). Faster moving averages, using fewer days in their calculations, are more sensitive to market fluctuations and will alert a trader to changes in trend sooner than a slower moving average. But the faster moving average becomes overly sensitive during a sideways-moving market and often has the trader buying in and out of market fluctuations or noise when there is little profit to be made. The slower moving average filters out that noise, but has a lag that often keeps the trader out of a significant amount of profit when the market begins to trend. |
The AMA adjusts the length of its moving average so that it's faster, using fewer days, to calculate its moving average when the market moves swiftly, changes directions, or breaks out of a trading range. Yet it slows down, using more days, when the market is volatile and moving sideways. Therefore, it should generate fewer and more profitable buy/sell signals. |
In calculating the AMA, Kaufman first used price direction and volatility to come up with an efficiency ratio (ER). The ER approaches 1 when the market is moving up or down, and approaches zero when it's in a sideways pattern. Kaufman then calculated two of what he called, smoothing constants, using a fast and slow exponential moving average. He combined the two smoothing constants with the ER to arrive at an AMA that adjusts to the market's trend, then generates buy and sell signals. |
Adapted from "Adaptive Moving Averages" by Bruce Faber, Technical Analysis of STOCKS & COMMODITIES, Volume 13, Number 6. The complete mathematical formulas used, and excel spreadsheet data, are available at Adaptive Moving Average by Bruce Faber |
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