Hurst Exponent
Measures the persistence or anti-persistence of a time series using R/S analysis.
Usage
Use to classify the current market regime. H > 0.5 suggests a trending market (persistent); H < 0.5 suggests a mean-reverting market (anti-persistent). Useful as a filter for trend-following or mean-reversion strategies.
Background
The Hurst Exponent, pioneered by Harold Edwin Hurst in 1951, quantifies the 'memory' of a time series. In technical analysis, it distinguishes between trending, mean-reverting, and random walk price action. It is a critical feature for machine learning models to adapt their logic to the underlying market structure.
Parameters
period(default: 100): Lookback period for R/S analysis
Formula
\[
H = \frac{\ln(R/S)}{\ln(N)}
\]