15.070 Advanced Stochastic Processes

As taught in: Fall 2005

Level:

Graduate

Instructors:

Prof. David Gamarnik

Premal Shah

A stopped Brownian motion as an example for a martingale.
Some stopping times (even hitting times) of Brownian motion. (Image courtesy of Thomas Steiner.)

Course Features

Course Highlights

This course features a complete set of lecture notes from the instructor, together with the assignments and exams.

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.
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