This seminar aims to look at various computational topics related to mathematical finance. This will range from numerical methods, via simulation especially Monte Carlo techniques and classical statistical approaches to machine learning methods. The implementation of the methods in R will be discussed.

This seminar is primarily intended for master students, but topics suitable for Bachelor students will be on offer.

To register for the seminar,  please write an email to robert.stelzer(at)uni-ulm.de until 15th September 2023.

Please give your name, matriculation number, and your programme of studies as well as a list of previously attended courses in probability and statistics.

The number of participants is limited to 15 students.

The seminar will be mainly based on the book

Rituparna Sen, Sourish Das, Computational Finance with R, 2023, Springer Singapore

Some topics (especially for Master students) may be based on further books/ papers, e.g.:

Soeren Asmussen, Peter W. Glynn, Stochastic Simulation: Algorithms and Analysis, 2007, Springer, New York

Carl Graham, Denis Talay,  Stochastic Simulation and Monte Carlo Methods: Mathematical Foundations of Stochastic Simulation, 2013, Springer, Berlin

Rüdiger Seydel, Tools for Computational Finance, 2017, Springer, London

Norbert Hilber, Oleg Reichmann, Christoph Schwab, Christoph Winter Stochastic Simulation and Monte Carlo Methods: Mathematical Foundations of Stochastic Simulation, 2013, Springer, Berlin