Permutation Entropy Regime

Most complexity measures available to MetaTrader users look at the size of price moves. Permutation entropy looks at their order instead. Every overlapping run of InpOrder consecutive closes is reduced to its rank pattern - which position in the run is highest, which is second highest, and so on - and every run in the rolling window is classified into one of InpOrder-factorial possible patterns. The Shannon entropy of how often each pattern occurs, normalised to 0..1, is the reading. A market cycling through orderings close to uniformly - every pattern about equally likely - reads near 1, close to what a genuinely random sequence would produce. A market that keeps repeating a small subset of orderings reads low: something is structuring the sequence, whether that is a strong trend, a tight range, or some other regularity the entropy measure does not itself distinguish. That is the honest limitation of the method - it detects structure, not what kind. This complements existing choppiness and randomness tools rather than duplicating them: those typically look at magnitude or at pass/fail run-length tests, while this looks purely at the ordinal shape of short sequences. Notes and limitations - Patterns are built directly from close prices with ties broken by bar position, the standard convention - on instruments with very coarse tick sizes, genuine ties become more common and slightly understate the entropy. - Higher InpOrder values need a larger InpLookback to keep the pattern histogram from being dominated by sampling noise; the input validation only enforces a loose four-times-order floor. - This flags a statistical regime property, not a trade signal, and says nothing about direction. - Entropy is recomputed independently every bar from the trailing window; it does not smooth between readings.

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