An algorithmic introduction to numerical simulation of stochastic differential equations

A practical and accessible introduction to numerical methods for stochastic differential equations is given. The reader is assumed to be familiar with Euler's method for deterministic differential equations and to have at lea st an intuitive feel for the concept of a random variable; however, no know ledge of advanced probability theory or stochastic processes is assumed. Th e article is built around 10 MATLAB programs, and the topics covered includ e stochastic integration, the Euler-Maruyama method, Milstein's method, str ong and weak convergence, linear stability, and the stochastic chain rule.