Introduction to Stochastic Processes

Catalog description

This is an introductory course in stochastic processes. Stochastic processes are widely used as modeling tools in many fields of application, including finance, physics, biology and engineering. The course will include an introduction to measure theory, the basic theory of discrete and continuous time Markov chains, branching processes, Poisson point processes Brownian motion and martingales. In the final part of the course, more advanced topics such as stochastic integrals, free fields, Markov loops and Ising model may be included as time permits and according to the background of the students. Pre-requisites: Grade B or better in either MATH-SHU 140 (Linear algebra) or MATH-SHU 141 (Honors Linear Algebra I), and grade B or better in either MATH-SHU 235 (Probability and Statistics) or MATH-SHU 238 (Honors Theory of Probability) Fulfillment: Honors Math Electives, Math Additional electives; DS Concentration in Math.