This document discusses using a Hidden Markov Model for algorithmic trading by modeling transition probabilities between market states. Changes in transition probabilities imply structural breaks that can be traded, going long when probabilities increase and short when they decrease. Further improvements include hyperparameter tuning, accounting for feature dependence, stress testing, and ensuring the approach does not disorderly impact markets.