Adaptive Moving Averages Using Efficiency Ratio to Adjust Trend Speed

Summary

The document explains Kaufman’s adaptive moving average (AMA) as an adjustment to conventional moving averages, whose fixed speeds can lag sharp trends or turn repeatedly in noisy markets. It introduces an efficiency ratio that compares net price change with the total path traveled over a lookback period. A high ratio indicates directional movement, while a low ratio indicates choppier price action.

The ratio scales a smoothing constant between fast and slow settings; squaring that constant further reduces movement in sideways markets. AMA then updates from its prior value toward the current price using this adaptive weight, following the basic recursive form of an exponential average. The author describes the intended benefits—faster tracking in clear trends and slower movement amid noise—but provides no empirical test results. The text explicitly leaves A-share strategy testing for future work, and a commenter challenges whether smoothed, data-driven timing methods adapt meaningfully to markets. Thus, the method is presented conceptually, not validated as a profitable strategy.

Key ideas

• A conventional moving average uses fixed weights or speed, which can be poorly suited to changing market conditions.
• The efficiency ratio compares net price displacement with the total distance traveled by prices.
• The ratio adjusts a smoothing constant between fast and slow settings according to trend clarity.
• Squaring the adjusted constant is intended to make the average move very slowly when the market lacks direction.
• The document describes the indicator but does not provide a strategy backtest or evidence of profitability.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.