Wednesday, November 3, 2021 - 17:00 in V10-122
Calculating robust price bounds using generative adversarial nets
A talk in the Bielefeld Stochastic Afternoon series by
Stephan Eckstein
| Abstract: |
$$\textbf{Bielefeld Stochastic Afternoon - Math Finance Session}$$
To calculate robust price bounds, one has to identify risk-neutral distributions that correspond to extreme cases given the constraints on the market, leading for instance to the martingale optimal transport problem. This talk presents a method to solve such optimization problems using neural networks and a MinMax approach, which is in close relation to generative adversarial networks. We showcase how regularization methods can justify the utilization of neural networks in this framework, and further show how numerical tools from the area of generative adversarial networks can be adapted to obtain stable numerical solutions to robust pricing problems. This talk is mainly based on joint work together with Luca De Gennaro Aquino.
Within the CRC this talk is associated to the project(s): C3, C4, C5 |
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