Hurst Exponent Pass Node
Hurst Exponent — Series Input
Overview
The Hurst Exponent Pass Node applies Rescaled Range (R/S) analysis to any upstream numeric series, computing the Hurst exponent H over a rolling window. H measures the long-range dependence or memory of the series.
The Hurst exponent was originally used in hydrology to characterise river flood cycles and has become a key tool in quantitative finance for distinguishing trending from mean-reverting markets.
Formula
Parameters
| Parameter | Default | Description |
|---|---|---|
| period | 100 | Rolling window in bars. Values ≥ 100 recommended for reliable estimates. |
Inputs & Outputs
| Slot | Direction | Type | Description |
|---|---|---|---|
| input | Input | { values, timestamps } | Any upstream numeric series |
| values | Output | (number | null)[] | Hurst exponent H per bar; nulls during warm-up |
| timestamps | Output | number[] | Unix timestamps aligned to input |
Use Cases
Strategy Selection
H > 0.55 → trend-following; H < 0.45 → mean-reversion; 0.45–0.55 → neutral / wait for clarity.
Market Regime Classification
Track H over time to classify bull trends, consolidations, and mean-reverting corrective phases.
Asset Screening
Screen assets for persistent (H > 0.6) behaviour to find the best candidates for momentum strategies.
Tips & Best Practices
Use Large Windows
R/S analysis is noisy with small samples. Use period ≥ 100 for daily data; ≥ 200 for even more reliable estimates.
Log Returns Input
Feed log returns to the Hurst node for a more stationary input that produces cleaner estimates than raw prices.
Confirm with DFA
DFA is more robust to non-stationarity. Use both Hurst and DFA to confirm the regime before trading.