M.Sc. Christian Pötz

Technical University Munich
Chair of Mathematical Finance (Prof. Zagst)

Postal address
Parkring 11-13
85748 Garching b. Munich


Phone: +49 (89) 289 - 18790
Room: 8101.03.402

  

Short CV

After his undergraduate studies in mathematics (minor economics) at the Technische Universität Darmstadt, Christian joined the graduate program "Mathematical Finance and Actuarial Science" at the Technische Universität München. His master thesis deals with the topic "Chebyshev Interpolation for parametric option pricing – empirical and theoretical investigations“. During his master studies, he spent a semseter abroad at the University of Copenhagen and he did internships at UniCredit Bank AG and Ernst & Young. Since then Christian is doing his PhD at the Chair for Mathematical Finance in cooperation with KPMG Center of Excellence in Risk Management

 

 

PhD Project

Complexity reduction techniques for accurate real-time evaluations in pricing and risk management

In his PhD Project, Christian investigates computational methods in finance and analyses the potential efficiency gain.

Real-time evaluation and risk management of large portfolios is one of the hardest and most urgent task of financial institutions. Fast and accurate computational methods are indispensable. In this project, we face the growing demands on computational methods in finance by exploring complexity reduction techniques for option pricing and risk management.

Starting point of the PdD project are recurrent pricing problems, in which the same calculations have to be repeatedly performed for a large set of parameters. Standard pricing methods, such as Monte Carlo simulation, Fourier methods or PDE techniques can be very time consuming and thus complexity reduction techniques become important. The two main pillars of the project are the polynomial interpolation method in the Chebyshev points and an empirical interpolation method, using the so-called Magic Points. Both methods feature a fast error decay and explicit error bounds are known.

We can build on the initial works that have been produced by Kathrin Glau and her doctoral students. The aim of the project is an extensive analysis of the efficiency gain obtained by applying the two interpolation methods to parametric problems in option pricing, hedging and more general risk assessment tasks. Important steps are the handling of sensitivities and the extension of the methods to higher dimensional problems.

Supervisor: Prof. Dr. Kathrin Glau