STA 447/2006: Stochastic Processes

Description

Time: Wednesdays 6pm – 9pm

Office hours: Wed 4:30pm – 5:30pm (Instructor), Tue 9am – 10am (TA)

Teaching assistants: Yan Zhang and Marco Antonio GH

This is an introductory course for stochastic processes. In this semester, we will discuss stochastic processes with various structures, including (discrete-time) Markov chains, martingales, Brownian motion and Poisson processes. Topics include, but are not limited to, recurrence and convergence of Markov chains, optional stopping and martingale convergence, and basics of stochastic calculus. If time permits, we will also cover applications including Monte Carlo algorithms, random walks on graphs, branching processes, option pricing, queueing theory, and more.

Announcement

• First lecture starts on January 8th.

Textbooks

Default textbook

• A first look at stochastic processes by Jeff Rosenthal

Reference books

• Introduction to stochastic processes, by Greg Lawler

• Essentials of stochastic processes, by Rick Durrett, 2nd Edition

Grading

2 mid-term exams during classes and a final exam.

Raw final grade = max (25% * midterm1 + 25% * midterm2 + 50% * final, 33.3% * midterm1 + 66.7% * final, 33.3% * midterm2 + 66.7% * final, 100% * final)

There are no graded homework assignments. However, you are strongly encouraged to attempt the textbook's practice problems to learn the material well.