Markov Chains and Monte Carlo Simulation


Dr. Pavel Grabarnik, Russian Academy of Sciences

Time and place

Tuesday, 12–14 h, He 22, Room 202/ 203

Homework session
Thursday, 12-13 h, He 22, Room 202/ 203


4 weeks, beginning Tuesday, November 20

Lecture: 2 h/week

Homework session: 1 h/week


Probability Calculus (required), Statistics (recommended)

Intended audience

Students and Ph.D. students with interest in stochastics


Markov chains represent one of the basic statistical models for sequences of random variables, which exhibit a certain dependence structure. There exist various applications, amongst others, in finance and insurance, but also, for example, in life and biosciences. Besides, one often faces with a problem that the mathematical model becomes so complex that explicit analytic formulae do not exist. In this case, Markov chain Monte Carlo simulation is used as an auxiliary tool to obtain approximate solutions.

Further information

This lecture is held within the framework of the activities of the DFG Research Training Group "Modelling, analysis and simulation in economy mathematics" at the Ulm University.



  • Dr. Pavel Grabanik
  • Office hours on appointment
  • Phone: +49 (0)731/50-23528


  • First class: November 20.