Indicators: Institutional Shannon Entropy (Predictability Index)
i would like to apply this to the other indicators -- to atr for example
Applying Information Theory directly to a volatility derivative like the Average True Range instead of raw price distribution is an excellent quantitative concept that would allow you to measure the predictability of market expansion phases
However, the theoretical model published here is hardcoded to parse standard price arrays. Routing external indicator buffers like the ATR into the Entropy engine requires re-engineering the core mathematical loops to handle dynamic data streams without causing memory leaks in the terminal. I do not provide custom modifications on these open-source structural blueprints, but if you want to deploy that specific ATR-Entropy hybrid model for your live trading, I can build the custom institutional architecture for you, submit a formal request through the Freelance section and we can discuss the engineering requirements to bring your idea into a stable execution environment
this users profile information and all codebase documents that have been submitted have been written in ai. it should be reviewd.
@moderator @admin
this users profile information and all codebase documents that have been submitted have been written in ai. it should be reviewd.
kishan can tag the admins all day but the shannon math is wide open in the codebase
if you think a standard counting loop with log calculations is ai slop you just can't read raw mql5, stop calling the moderators and go learn how to plugar an indicator array safely, real quants are downloading the source while you complain
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Institutional Shannon Entropy (Predictability Index):
A quantitative Information Theory engine that calculates the Shannon Entropy of price distribution to mathematically measure market randomness and algorithmic predictability.
Author: Amanda Vitoria De Paula Pereira