AMCS 336 Numerical Methods for Stochastic Differential Equations

Prerequisites: knowledge of basic probability, numerical analysis, and programming. Brownian motion, stochastic integrals and diffusions as solutions of stochastic differential equations. Functionals of diffusions and their connection with partial differential equations. Weak and strong approximation, efficient numerical methods and error estimates. Jump diffusions.