Ehlers Autocorrelation
Computes Pearson correlation of smoothed price with its lags to identify market structure.
Usage
Use to generate an autocorrelation periodogram showing which cycle periods are currently dominant. Visualise as a heatmap to track cycle period shifts over time.
Background
Ehlers introduces autocorrelation-based cycle measurement in Cycle Analytics for Traders (2013) as a more robust alternative to DFT. By computing autocorrelation of Roofing-filtered price at each lag, then applying a spectral DFT to the lag series, he obtains a periodogram insensitive to amplitude variations.
Parameters
length(default: 20): Correlation window lengthnum_lags(default: 100): Number of lags to compute
Formula
\[
\rho(lag) = \frac{N \sum X Y - \sum X \sum Y}{\sqrt{(N \sum X^2 - (\sum X)^2)(N \sum Y^2 - (\sum Y)^2)}}
\]