MATH 866 – Stochastic Process II (Fall 2021)

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  1. Text: Continuous Time Markov Processes (Graduate Studies in Mathematics), by Thomas M. Liggett. Publisher: American Mathematical Society, 2010.
  1. References: Lecture notes on SDEs; Markov Processes, Characterization and Convergence. By Stewart N. Ethier and Thomas G. Kurtz. Publisher: Wiley. 1986.
  1. Prerequisite: Math 865 or permission of the instructor.
  1. Office: 510 Snow Hall; Office hour: Tuesday, Thursday 2:00-3:00 pm.
  1. Lecture time: Tuesday and Thursday. 11:00am-12:15 pm.
  1. Exams:  Midterm exams will be given in the form of exercises. Final exams will be given in the form of mini-research/reading/presentation project.
  1. Course coverage:  Brownian Motion, Martingales, Stochastic Integrations, Stochastic Differential Equations,  Martingale Problems, linear parabolic and elliptic PDEs, Optimal Control Theory, etc…