6.265J Advanced Stochastic Processes
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; functional limit theorems. Applications to finance theory, insurance, queueing and inventory models.
This class counts for a total of 12 credits. This is a graduate-level class.
You can find more information on MIT OpenCourseWare at the Advanced Stochastic Processes site.
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