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105.745 Theory of stochastic processes
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2023S, UE, 1.0h, 1.5EC


  • Semester hours: 1.0
  • Credits: 1.5
  • Type: UE Exercise
  • Format: Presence

Learning outcomes

After successful completion of the course, students are able to understand the basic concepts underlying the theory of discrete-time and continuous-time Markov chains and discrete-time martingales. They are also able to apply these concepts in a variety of applications.

Subject of course

See lectures

Teaching methods

Discussion of the problem sheets previously provided by the lecturer

Mode of examination


Additional information

Face-to-face classes. Due to the COVID pandemic, there may be changes in the teaching modalities.



Course dates

Wed09:00 - 11:0015.03.2023 - 07.06.2023Seminarraum 127 Theory of stochastic processes
Theory of stochastic processes - Single appointments
Wed15.03.202309:00 - 11:00Seminarraum 127 Theory of stochastic processes
Wed29.03.202309:00 - 11:00Seminarraum 127 Theory of stochastic processes
Wed26.04.202309:00 - 11:00Seminarraum 127 Theory of stochastic processes
Wed10.05.202309:00 - 11:00Seminarraum 127 Theory of stochastic processes
Wed24.05.202309:00 - 11:00Seminarraum 127 Theory of stochastic processes
Wed07.06.202309:00 - 11:00Seminarraum 127 Theory of stochastic processes

Examination modalities

Students will be required to work out problems at home and present them during the class. There will also be a written exam in June or July (date to be agreed). The final grade will take into account these two components.

Course registration

Begin End Deregistration end
01.02.2023 08:00 31.03.2023 20:00 31.07.2023 20:00


Study CodeObligationSemesterPrecon.Info
066 394 Technical Mathematics Mandatory elective
066 395 Statistics and Mathematics in Economics Mandatory elective
860 GW Optional Courses - Technical Mathematics Not specified


  • Norris, J. (1997). Markov Chains. Cambridge University Press. doi:10.1017/CBO9780511810633
  • Williams, D. (1991). Probability with Martingales. Cambridge University Press. doi:10.1017/CBO9780511813658

Previous knowledge

Basic probability theory, calculus and linear algebra