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15.070J Advanced Stochastic Processes (MIT)

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.... Show More

Keywords:: theoretic probability, modeling, insurance, functional limit theorems, queueing, large deviations theory, Probability and Statistics, reflected Brownian motion, analysis, ocwc, oec, Ito calculus, filtration, Brownian motion, stochastic integration, martingales, finance theory, inventory models, stopping theorems, applications, stochastic processes

Disciplines:

Mathematics and Statistics / Statistics and Probability

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Material Type:: Online Course
Date Added to MERLOT:: August 6, 2014
Date Modified in MERLOT:: January 8, 2021
Author:: Prof. David Gamarnik
Submitter:: The Open Education Consortium
Primary Audience:: College General Ed
Technical Format:: Website

Mobile Compatibility:: Not specified at this time
Language:: English
Cost Involved:: No
Source Code Available:: No
Accessibility Information Available:: No
Creative Commons:: This work is licensed under a Attribution-NonCommercial-ShareAlike 3.0 United States