Adaptive Composite Moving Average with Trend and Range Weighting Modes
Summary
This indicator description introduces the Adaptive Composite Moving Average (ACMA), which combines distance-based weighting, recency weighting, and an efficiency-ratio measure of trend strength. It offers four modes: favor prices near the mean, favor recent prices, combine both approaches, or adapt their blend to an estimated trending or ranging regime. A configurable stability filter proportionally blends the current value with the previous output when price and average move in opposite directions under a specified threshold. The note also gives parameter ranges and example settings for different trading styles.
The design draws on ideas associated with KAMA, ALMA, weighted and exponential averages, and VIDYA. These foundations are established concepts, while the claimed benefits of the combined architecture are not supported here by comparative tests or performance results. The author labels the release an early version and invites feedback. Its recommended settings are suggestions, not evidence of suitability across markets, instruments, or timeframes.
Key ideas
- ACMA offers four weighting modes based on distance from the mean, recency, or a combination of both.
- Its adaptive mode uses an efficiency ratio to favor recency in trends and mean proximity in ranges.
- An optional stability filter blends output changes when price and the average diverge under a threshold.
- The indicator exposes lookback, weighting mode, sensitivity, and stability settings.
- The document describes a version-one design but provides no comparative backtest or performance evidence.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.