The dependence of decision-making with respect to modelling assumptions has received considerable attention in the financial mathematics community over the last years. However, further progress in this research direction was hindered by the lack of a fitting notion of closeness between stochastic processes. In this talk, I will provide strong evidence supporting the suitability of 'adapted Wasserstein distances' for this task, in the form of stability and sharp quantitative error bounds for some of the most classical problems arising in financial mathematics. Unlike their more familiar counterparts, these transport-based distances take the role of information explicitly into account.
Adapted Wasserstein distance and stability in mathematical finance
17.06.2020 10:20 - 11:05
Organiser:
Fakultät für Mathematik
Location:
Zoom Meeting