Understanding Markov Chains: From Basics to Convergence and Sampling

This article explains the fundamentals of Markov chains, illustrates their transition matrix with a market example, demonstrates convergence through Python code, and outlines how to use the stationary distribution for sampling in Monte Carlo simulations.

Markov chainMonte CarloSampling

0 likes · 9 min read

Understanding Markov Chains: From Basics to Convergence and Sampling

Model Perspective

Oct 2, 2022 · Fundamentals

Why Do Markov Chains Always Converge? A Hands‑On Exploration

This article explains the basic definition of Markov chains, illustrates a stock‑market example with transition matrices, demonstrates convergence through Python simulations, and shows how the steady‑state distribution enables sampling for Monte Carlo methods.

Monte CarloPythonconvergence

0 likes · 10 min read

Why Do Markov Chains Always Converge? A Hands‑On Exploration