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.