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
assignment_turned_in Problem Sets with Solutions
grading Exams with Solutions
notes Lecture Notes
co_present 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.)