TA for STAT 5264: Stochastic Processes with Applications (Section 002)

I’m currently a TA for STAT 5264: Stochastic Processes with Applications (Section 002), taught by Prof Graeme Baker. This is a graduate-level course that covers the theory and applications of stochastic processes, including Markov chains, Poisson processes, Brownian motion, and stochastic calculus. We are using the book Stochastic Calculus for Finance II: Continuous-Time Models by Steven Shreve as the main textbook, which can be accessed here. I am holding office hours on Tuesdays from 3-4PM and Wednesdays from 9-10AM at Uris Hall 321/322.

Some tips for the course include:

• Not always expanding all of the expectations; a lot of the problems can be worked out by using the properties of conditional expectations and the tower property, as well as other properties of stochastic processes and their expectations covered during the course.
• Remember the density for a standard Brownian motion at time $t$, as well as the key properties of Brownian motion such as independence of increments, stationary increments, and (important) the Markov property.