Monte Carlo Methods in finance and insurance
Dr. Christoph Wagner
Date/Time: Mon 8-10
The main idea of the Monte Carlo (MC) method is to approximate an expected value E(X) by an arithmetic average of a very large number of independent
random experiments with distribution of X in a stochastic simulation. As the expected value operator plays a pivotal role in the pricing equation of
financial instruments the MC method has a widespread use in financial engineering. We start with the problem of generating suitable random numbers and
move then forward to different schemes of the MC method and the respective algorithms and apply them to selected financial and actuarial models.
Korn, R. et al: Monte Carlo Methods and Models in Finance and Insurance, Chapman & Hall/CRC (2010)
Glasserman, P.: Monte Carlo Methods in Financial Engineering, Springer (2004)
Asmussen, S., Glynn, P.: Stochastic Simulation, Springer (2007)
Jaekel, P.: Monte Carlo Methods in Finance, Wiley Finance (2002)
Interested participants are asked to apply by email as there are only a limited number of seats available.
Zielgruppe: fortgeschrittene Bachelor- Masterstudenten Finanz und Versicherungsmathematik und mathematik
Vorkenntnisse: Wahrscheinlichkeitstheorie, Finanzmathematik I+II