15.070J | Fall 2013 | Graduate

Advanced Stochastic Processes

Course Description

This 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 …
This 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.
Learning Resource Types
Problem Sets with Solutions
Exams with Solutions
Lecture Notes
Instructor Insights
A graph depicting three examples in blue, yellow, and green of stopped Brownian motion.
Hitting and stopping times of three samples of Brownian motion. (Image courtesy of Thomas Steiner on Wikimedia Commons. License: CC-BY-SA.)