Advanced Simulation Methodology

Advanced Simulation Methodology

2 hours of lectures per week, 3 hours computer labs. There will be no teaching 2-3 weeks.

Lecturer:
Søren Asmussen

Contents
The course aims at giving theoretical insight and practical familiarity with a broad spectrum of topics in stochastic simulation (except for Markov chain Monte Carlo which has been covered in other courses). Some key topics are random number generation, output analysis, steady state simulation, gradient estimations (Greeks!), rare events, Lèvy processes, SDE's and Gaussian processes. The applications, examples and exercises will to a large extent be taken from the area of mathematical finance.

Prerequisites
A working knowledge of probability and statistics as well as programming experience.
The necessary background from mathematical finance can easily be picked up along the way, as well as what is needed on Markov chains, Ito calculus etc. to do the labs.

Assessment
Active participation in discussions and presentations.

Textbooks
S. Asmussen, Stochastic Simulation. With a View Towards Stochastic Processes, Maphysto, Aarhus, 1999.
The notes are being reworked and extended to book form (jointly with Peter Glynn, Stanford), and the course will use the new version, not the original one.

ECTS-credits
10.

Semester
Autumn 2003.