Ehlers Adaptive CCI with a Homodyne Cycle-Period Estimate

Summary

This document presents an implementation of John Ehlers’ Adaptive Commodity Channel Index. It estimates a dominant cycle period from price data by smoothing prices, deriving in-phase and quadrature components, and applying a homodyne discriminator. The estimated period is bounded and smoothed, then used to set the lookback length for the CCI calculation. The index compares the latest typical price with its rolling mean and mean deviation, scaled by the conventional constant shown in the implementation.

The document names Ehlers’ book as the method’s source and mentions a screenshot comparing the adaptive indicator with Donald Lambert’s CCI, but supplies no performance study or trading rules. It therefore explains indicator construction rather than establishing predictive value. The code also depends on historical bars and platform-specific syntax; initialization, edge cases, and implementation details such as phase calculation may affect results. Traders would need to validate the implementation and test any signals across markets and regimes before relying on them.

Key ideas

• The method estimates a changing cycle period from smoothed price data using in-phase and quadrature components.
• It constrains and smooths the period estimate before using it as the CCI lookback length.
• The adaptive index normalizes the latest typical price’s deviation from its rolling average by mean absolute deviation.
• The document provides an implementation and a visual comparison, but no evidence of trading performance.

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