KAMA: An Adaptive Moving Average for Trend Signals

Summary

The article explains Kaufman’s Adaptive Moving Average (KAMA), which adjusts its responsiveness according to an efficiency ratio derived from net price direction relative to total price movement. The ratio is intended to be low in choppy markets and high in directional markets, allowing the average to smooth more during noise and respond faster as a trend develops. The tutorial outlines the calculation, identifies the standard parameters it uses, and gives rules for opening and closing long and short positions based on price relative to KAMA and the average’s slope.

It also describes implementing the indicator in a trading platform, applying signal filtering, and testing a simple strategy with slippage. The article reports favorable backtest behavior across a cryptocurrency bear market and a later bull market, but supplies no detailed performance figures in the text. It cautions that the rules need further refinement, including filters and stop controls, and that fixed parameters may not suit future conditions. A backtest alone does not establish live performance.

Key ideas

• KAMA adjusts its smoothing based on the ratio of net price movement to total movement over a period.
• A low efficiency ratio corresponds to choppy conditions, while a high ratio signals more directional movement.
• The example strategy opens positions when price and KAMA slope agree and closes when either condition reverses.
• The article reports a backtest using slippage but does not provide numerical performance details in the text.
• Additional filters and risk controls may be needed, and historical parameters may not generalize.

Tags

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