Definition

Hidden Markov Model

Meaning ⎊ A statistical framework for predicting unobserved market states based on visible output data like price movements.
Greeks.liveJune 5, 2026

Hidden Markov Model

A hidden Markov model is a statistical model where the system being modeled is assumed to be a Markov process with unobserved states. The observer only sees the output, which is influenced by the hidden state, such as price returns reflecting an underlying volatility regime.

In quantitative finance, this is used to infer the current market state ⎊ such as accumulation or distribution ⎊ without direct observation. It is a powerful tool for decoding the signals within order flow and market microstructure.

By identifying these hidden patterns, traders can anticipate regime shifts before they become obvious in the price data. This methodology is essential for developing algorithmic strategies that adapt to changing market psychology and behavioral game theory.

It provides a structured way to map complex, noisy data to a limited set of interpretable market states.

Goodness of Fit
Model Checking Logic
Autoregressive Process
Predictive Accuracy
Constant Product Formula Risk
Optimistic Execution Model
Default Validity Assumptions
WebSocket Vs REST

Glossary

Hidden State Transitions

Mechanism ⎊ These transitions represent latent shifts in market regimes where underlying probabilistic models change without an explicit external signal.