Markov Chains and Monte Carlo Simulation

Lecturer
Jun.-Prof. Dr. Zakhar Kabluchko

Exercises
Dipl.-Math. Christian Hirsch


Time and place

Lectures

Tuesday, 16-18  (HeHo 18, Room 120)

Exercise session
Tuesday, 12 - 13 (HeHo 18, Room 120)

Written exam

Monday, July 18, 9:00 AM, Room H20

 

Exercise sessions start at April 19, 2011.


Type

2 hours lecture + 1 hour exercises

Starting from the 2nd homework sheet we will no longer accept joint homework solutions. Sheets containing more than one student name will not be graded.

For the assessment of your homework solutions a registration at SLC is required

 


Problem sets

problem set 1

problem set 2

problem set 3

problem set 4, appendix to solution of 4.2

problem set 5

problem set 6, sketch of solution for 6.4

problem set 7

problem set 8, sketch of solution to 8.2-8.4

problem set 9

problem set 10

problem set 11, sketch of solution for 11.3d

problem set 12 (corrected version of exercise 2)

mock exam , sketch of solution for problems 3 and 5b


Prerequisites

Probability Calculus


Intended Audience

Bachelor students in Mathematics, Business Mathematics and Mathematical Biometrics; Master students in Finance
Credit points: 4


Exam

The second exam takes plays on 29th of September, between 12:00 and 17:00 in the office of the lecturer (E00, Helmholtzstr. 18). The participants will receive an e-mail with the exact time of their exam. You may use the following text by Nicolas Privault to prepare for the exam: PDF


Literature

  • O. Häggström: Finite Markov Chains and Algorithmic Applications. Cambridge University Press, 2002
  • S. I. Resnick: Adventures in Stochastic Processes. Birkhäuser, 1992
  • Y. Suhov, M. Kelbert: Probability and Statistics by Example. Volume 2. Markov Chains: A Primer in Random Processes and their Applications. Cambridge University Press, 2008
  • T. Rolski, H. Schmidli, V. Schmidt, J. Teugels: Stochastic Processes for Insurance and Finance. Wiley, 1999
  • E. Behrends: Introduction to Markov Chains. Vieweg, 2000
  • P. Bremaud: Markov Chains, Gibbs Fields, Monte Carlo Simulation, and Queues. Springer, 2008

 

 

Contact

Lecturer

 

  • Office hours on appointment
  • Phone: +49 (0)731/50-23527
  • Homepage

Teaching Assistant

  • Office hours on appointment
  • Phone: +49 (0)731/50-31083
  • Homepage


News


Anonymous Feedback

On this  page  you can send us anonymous comments on the lecture and exercise sessions.