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Overview — An oscillator based on information theory (Shannon entropy) that quantifies how "ordered" versus "random" recent price movements are, on a 0–1 scale.
Main Features
- ATR-adaptive discretization of price changes into directional symbols (no fixed pip thresholds)
- Normalized entropy (0 = perfectly ordered/trending, 1 = maximum disorder/choppy)
- Smoothed signal line (SMA of raw entropy) to reduce noise
- Configurable symbol resolution (finer or coarser classification)
How It Works — Each bar's price change is classified into one of InpSymbolCount symbols based on its size relative to ATR. Over a rolling window ( InpWindowSize ), the frequency distribution of symbols is used to compute Shannon entropy, normalized by the maximum possible entropy for that symbol count.
Input Parameters
- InpWindowSize (50) — rolling window length
- InpSymbolCount (5) — number of discretization symbols
- InpAtrMultiplier (0.35) — ATR fraction defining the "flat" band
- InpAtrPeriod (14) — ATR period for the threshold
- InpSignalSmoothing (5) — SMA period for the signal line
How to Use — Attach in a separate window below the price chart. Use low entropy readings as confirmation for trend-following signals, and high readings as a warning to avoid trend-following entries.
Use Cases — Filter to avoid trading trend-following strategies during choppy conditions; combine with the Invictus Trading Adaptive Kalman Trend for a two-part trend confirmation system.
Important Notes — This is a statistical characterization tool, not a buy/sell signal. It does not predict future entropy, only measures recent price behavior.
Version Information — v1.00, initial release.
- caption: "Entropy falls in trending phases, rises in choppy ones."
- caption: "Adaptive, ATR-based symbol discretization — no fixed pip thresholds."
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