Math 866 – Stochastic Process II (Fall 2020)

Prerequisite: Math 865 or permission of the instructor.

Text: Continuous Time Markov Processes (Graduate Studies in Mathematics), by Thomas M. Liggett. Publisher: American Mathematical Society, 2010.

References

• Markov Processes, Characterization and Convergence. By Stewart N. Ethier and Thomas G. Kurtz. Publisher: Wiley. 1986.
• Stochastic Processes. By Richard F. Bass. Publisher: Cambridge University Press. 2011.
• Brownian Motion and Stochastic Calculus. (Graduate Text in Mathematics) By Ioannis Karatzas and Steven E. Shreve. Publisher: Springer. 1998.

Jin Feng's Office

Room: 510 Snow Hall, Thursday 2:00-3:30 pm or by appointment (through zoom)

Lecture time: Tuesday and Thursday. 11:00am-12:15 pm through zoom

Homework and Exams

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.

Course Coverage

Brownian Motion, Markov Chains, Stochastic Integrations, Feller Process, Interacting particle systems, Martingale theory and Martingale Problems, linear parabolic and elliptic PDEs, Applications, etc…