Advanced Stochastic Processes
15.070J · Electrical Engineering and Computer Science, Sloan School of Management · Graduate · Fall 2013
Prof. David Gamarnik
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.
The syllabus, on MIT OpenCourseWare
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Syllabus ↗
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Attribution
Prof. David Gamarnik. 15.070J Advanced Stochastic Processes. Fall 2013. Massachusetts Institute of Technology: MIT OpenCourseWare, https://ocw.mit.edu. License: CC BY-NC-SA 4.0.
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