Course: STAT 31120
Title: Numerical Methods for Stochastic Differential Equations
Instructor(s): Zhongjian Wang
Teaching Assistant(s): TBD
Class Schedule: Section 1: MW 4:10 PM-5:30 PM (Remote)
Textbook(s): Milstein, Numerical Integration of Stochastic Differential Equations
Description: The numerical analysis of SDE differs significantly from that of ODE due to the peculiarities of stochastic calculus. This course starts with a brief review of stochastic calculus and stochastic differential equations, then emphasizing the numerical methods needed to solve such equations. The stochastic Taylor expansion provides the basis for the discrete-time numerical methods for differential equations. The course presents many results on high-order methods for strong sample path approximations and for weak functional approximations. To help with developing an intuitive understanding of the underlying mathematics and hand-on numerical skills, examples and exercises on PC are included.
Prerequisite(s): Knowledge of ODE and SDE is essential. STAT 39000 or STAT 39010 or STAT 38510 are strongly recommended.
