Forschungsgruppe "Stochastische Algorithmen und Nichtparametrische Statistik"

Seminar "Modern Methods in Applied Stochastics and Nonparametric Statistics" Sommer Semester 2022

19.04.2022 N.N.

26.04.2022 N.N.

03.05.2022 Jun.-Prof. Dr. Martin Redmann (Martin-Luther-Universität Halle-Wittenberg)
Solving high-dimensional optimal stopping problems using model order reduction (hybrid talk)
Solving optimal stopping problems by backward induction in high dimensions is often very complex since the computation of conditional expectations is required. Typically, such computations are based on regression, a method that suffers from the curse of dimensionality. Therefore, the objective of this presentation is to establish dimension reduction schemes for large-scale asset price models and to solve related optimal stopping problems (e.g. Bermudan option pricing) in the reduced setting, where regression is feasible. We illustrate the benefit of our approach in several numerical experiments, in which Bermudan option prices are determined.
10.05.2022 Prof. Vladimir Spokoiny (WIAS und HU Berlin)
Laplace's approximation in high dimension
17.05.2022

24.05.2022

31.05.2022

07.06.2022

14.06.2022 Priv. - Doz. Dr. John Schoenmakers (WIAS Berlin)
Dual randomization and empirical dual optimization for optimal stopping
21.06.2022 Grigory Malinovsky (KAUST)

28.06.2022

05.07.2022

12.07.2022

19.07.2022

26.07.2022



last reviewed: April 27, 2022 by Christine Schneider