Three-State Markov Chain Strategy for Long, Short, and Flat Signals

Summary

This strategy describes a three-state market model with bullish, bearish, and stagnant states. It labels the state by comparing each closing price with the previous close, then uses nine configurable transition probabilities to select a subsequent state. The trading rules enter long in a bullish state, enter short in a bearish state, and close positions in a stagnant state.

The document outlines the model and its parameter inputs but provides no backtest period, performance metrics, or evidence that the transition mechanism predicts market behavior. Its stated risks include sensitivity to manually chosen probabilities, lag from close-based classification, oversimplification, and potentially frequent trading costs. The source implements transitions with a deterministic counter rather than estimating or sampling probabilities from historical observations, so the probability framing does not itself demonstrate a statistically validated Markov forecast.

Key ideas

• The method classifies price action as bullish, bearish, or stagnant based on consecutive closes.
• Nine transition parameters govern movement among the three states.
• Bullish and bearish states trigger directional positions, while stagnant state closes positions.
• The transition mechanism uses a counter, and the document provides no empirical validation of predictive performance.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.