HMM Basics: Understanding Regime Detection From Log Returns to Market Regimes Using Hidden Markov Models In the previous notebook, we proved that log returns are the correct transformation for financial time series. Now we’ll use those log returns to detect market regimes using Hidden Markov Models (HMMs) . What …

HMM 101 An example of how we’ll be using our Hidden Markov Models in this project. HMM Workflow: Initialization (k-means): Cluster observations to get initial emission parameters Training (Baum-Welch ): Refine transition matrix & emission distributions Prediction (Viterbi ): Decode the most likely state sequence This …

Stochastic Modeling of Market Dynamics and the Efficient Market Hypothesis If the Efficient Market Hypothesis holds, then what hope do we have for using technical analysis? I. Introduction: The Dialectic of Efficiency and Predictability I.A. Contextualizing the Conflict Modern financial economics operates under a …

HMM Algorithms: Viterbi and Baum-Welch In our article on HMMs we discussed what Hidden Markov Models are. In this article, we’ll discuss how you train them based on observations. The key concepts are the Viterbi algorithm and the Baum-Welch algorithm . This article will assume some familiarity with statistics, so …

A Comprehensive Guide to Hidden Markov Models: Uncovering the Unseen Have you ever tried to guess what’s happening behind the scenes by just looking at the clues? Imagine you have a friend whose mood seems to change randomly. One day they are happy, the next they are sad, and the day after that they are just neutral. …