Stochastic Processes
(graduate course in mathematics)
Space-time coordinates of teaching
Roster
Course code
Email alias (send me email once to ensure your email
is included in this alias)
Prerequisites:
- Undergraduate probability, including basic elements of stochastic processes
- A graduate course in probability, e.g., see here for notes and bibliography (send me email for lecture notes)
- Analysis
- Measure theory and integration
Contents: Brownian motion; Poisson and point processes; Stochastic analysis; Markov processes; Gaussian processes; Partial differential equations and probability; Diffusions; Lévy processes; Special topics
Attendees' obligations:
- Attend lectures
- Participate (e.g., ask questions during lectures)
- Solve exercises
- Do Assignment 1; Assignment 2; Assignment 3; Assignment 4; Assignment 5; Assignment 6
Bibliography:
- Richard Bass. Stochastic Processes. Cambridge University Press, 2011
- Daniel Revuz and Marc Yor. Continuous Martingales and Brownian Motion. Springer-Verlag, 2004
- Chris Rogers and David Williams. Diffusions, Markov Processes and Martingales, Vol. I and Vol. II. Cambridge University Press, 2000
- Olav Kallenberg. Foundations of Modern Probability. Springer-Verlag, latest edition: 2010