An Intuitive Guide to MCMC (Part I): The Metropolis-Hastings Algorithm

Probabilistic algorithms such as Markov Chain Monte Carlo (MCMC), particularly the Metropolis-Hastings algorithm, are fundamental to advanced quantitative finance, providing robust methods for sampling complex probability distributions. These algorithms enable precise risk modeling and asset valuation by efficiently approximating integrals and distributions that are otherwise computationally intractable, highlighting their critical role beyond the current AI hype.