2020-21 Fall - MSDM5003 - Stochastic Processes and Applications

Course

Description

Probability theory; maximum likelihood; Bayesian techniques; principal component analysis, data transformation and filtering; Brownian motion and stochastic processes; cross-correlations; power laws; log-normal distribution and extreme value distributions; Maxwell-Boltzmann distribution; Monte Carlo methods; agent-based models; evolutionary games; Black-Scholes equation.
Course period1/09/2031/12/20
Course levelPG
Course formatLecture