Markov Transition Probabilities for Candle Direction
Summary
The document describes an indicator that classifies price action into bullish and bearish states, then estimates the chance of moving from the current state to either state next. It uses a rolling transition matrix: historical transitions in a localized window determine the percentages displayed for the next candle. The underlying idea is a Markov model, where the forecast depends on the present state and estimated transition probabilities rather than the full path that led there.
The text offers no sample results, validation, or details about how states are defined, how much data the rolling window uses, or how estimates behave across market regimes. Its claims of exact odds, zero latency, and removal of bias are not substantiated. Transition frequencies are estimates from past observations, and the Markov assumption may not capture relevant history or changing conditions. The execution protocol section is empty, so the document does not explain how to turn the indicator into a tested trading strategy.
Key ideas
- A Markov chain estimates the next state from the current state and transition probabilities.
- The indicator labels price action as bullish or bearish and counts transitions in a rolling historical window.
- It displays estimated probabilities for the next candle to be bullish or bearish.
- The document provides no empirical validation or operational details for its forecasting claims.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.