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Markov Model
Hidden
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Python
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Chain Model
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Tutorial
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11:30
YouTube
Nathan Kutz
Chapter 19.2 - Markov Decision Process for RL
The following are video lectures associated with the textbook "Data-Driven Modeling and Scientific Computation" by J. Nathan Kutz (Oxford 2025, 2nd Ed). WEBPAGE: faculty.washington.edu/kutz CODE & DATA: github.com/nathankutz/ScientificComputing
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Navigating Podcast
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A HIDDEN MARKOV MODEL JUST MAPPED EVERY MAJOR MARKET REGIME SINCE THE 2007 CRASHan enhanced hmm reads market data and outputs a probability distribution over hidden states basically is this a bull regime or a bear regime right nowred zone is high confidence bear blue is bull the x marks are where the model flags elevated riskrun it into the 2026 tariff shock and it reads the same pattern it caught back in 2007 and 2022worth being clear this isn't a claim that trading on the signal beats buy and
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Markov Decision Processes: Every RL Problem Is the Same Game #reinforcementlearning #MDP #ai
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Stop building spread models on assumptions you can't actually name.This MIT’s lecture on Stochastic Processes lays out random walks and Markov chains, the exact assumptions sitting underneath every stationary-spread claim in pairs trading.This is the part of the pipeline that should not be skipped.
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MIT published the complete graduate course on discrete stochastic processes for free.Taught by Robert Gallager one of the most respected names in information theory.It covers finite-state Markov chains, eigenvalues and eigenvectors of stochastic matrices, renewal theory, and martingales.The mathematical foundation behind regime switching models used across quantitative finance.Watch It Now & get ready for the article on Kalman Filter Tomorrow!
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So, Where Is Michael from Univer?
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