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Entropy Momentum Filter [EMF] -FibonacciFlux

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Entropy Momentum Filter [EMF]

What it does
Measures directional conviction in price action using Shannon entropy of log returns. Low entropy means strong directional conviction — the market is trending. High entropy means indecision — the market is ranging or chaotic.

How it works
  • Entropy Calculation: Builds a histogram of log returns over a rolling lookback window, then computes Shannon entropy H = -sum(p * ln(p))
  • Normalization: Divides by ln(N) to produce a 0-1 scale where 0 = perfect order and 1 = maximum randomness
  • Color Gradient: Green (low entropy, conviction) → Gray (neutral) → Red (high entropy, indecision)
  • Reference Lines: 0.3 low entropy threshold, 0.5 midpoint, 0.7 high entropy threshold


Key Features
  • Single clean concept — Shannon entropy applied to price changes
  • Normalized 0-1 output — no parameter-dependent interpretation needed
  • Built-in alert for conviction spikes (entropy drops below 0.3)
  • Only 2 inputs: lookback period and histogram bin count
  • Lightweight — minimal computational overhead


How to use
  • Conviction filter: Only take trend-following trades when entropy is below 0.5
  • Range detection: High entropy (>0.7) suggests avoid trend strategies or switch to mean-reversion
  • Conviction spike alert: Built-in alert fires when entropy drops below 0.3 — strong move likely starting
  • Combine with directional indicators: Use EMF as a filter on top of your existing signals


Inputs
  • Lookback period (default 20) — rolling window for entropy calculation
  • Histogram bins (default 10) — granularity of the return distribution


Works on all timeframes and instruments. Particularly effective as a regime filter combined with trend-following or mean-reversion strategies.

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