Level:
Graduate
Instructors:
Prof. David Gamarnik
Premal Shah
Some stopping times (even hitting times) of Brownian motion. (Image courtesy of Thomas Steiner.)
Course Features
Course Highlights
Course Description
The class covers the analysis and modeling of stochastic processes.
Topics include measure theoretic probability, martingales, filtration,
and stopping theorems, elements of large deviations theory, Brownian
motion and reflected Brownian motion, stochastic integration and Ito
calculus and functional limit theorems. In addition, the class will go
over some applications to finance theory, insurance, queueing and
inventory models.