Stochastic Processes

Dr. Alexander Kalinin

Schedule and Venue

EventsDate/TimeRoom
Lectures
Dr. Alexander Kalinin
Monday, 12:15 - 13:45
Thursday, 12:15 - 13:45
B004
Exercise Classes
Alejandro Caicedo
Wednesday, 14:15 - 15:45B004
Additional Exercise Classes
Dr. Alexander Kalinin
Monday, 11:00 - 11:45B251
Final ExamMonday, 12 February, 9:00 - 12:00B005
Retake ExamTuesday, 2 April, 9:00 - 12:00B005

The course is organised via Moodle. If you want to attend the course, please register in Moodle and send an e-mail from your LMU address to kalinin@math.lmu.de.

In this lecture, we will consider various classes of stochastic processes that may differ in their state spaces and underlying index sets with a special focus on Gaussian, Lévy and Markov processes. In summary, the lecture will be divided into three core topics: the construction, the path behaviour and the probabilistic analysis of general stochastic processes.

  • Bauer, H.: Probability theory, De Gruyter, 2011.
  • Dalang R., Khoshnevisan D., Mueller, C., Nualart, D. and Xiao, Y.: A minicourse on stochastic partial differential equations, Springer, 2009.
  • Marcus, M. B. and Rosen, J.: Markov processes, Gaussian processes, and local times, Cambridge University Press, 2006.
  • Applebaum, D.: Lévy processes and stochastic calculus, Cambridge University Press, 2009.
  • Sharpe, M.: General theory of Markov processes, Academic Press, 1988.

All five books are available as PDF files for LMU students at the university library.

Target Participants: Master students in Mathematics and Financial and Insurance Mathematics.

Pre-requisites: Probability theory and measure and integration theory.

Applicable credits: 9 ECTS. Students may apply the credits from this course to the

  • Master in Mathematics, PO 2021 and PO 2011 (WP 4)
  • Master in Financial and Insurance Mathematics, PO 2021 (WP 12), PO 2019 (WP 13), PO 2011 (WP 1)