The classical assumption in the literature on numerical approximation of stochastic differential equations (SDEs) is global Lipschitz continuity of the coefficients of the equation. However, many SDEs arising in applications fail to have globally Lipschitz continuous coefficients.
In the last decade an intensive study of numerical approximation of SDEs with non-globally Lipschitz continuous coefficients has begun. In particular, strong approximation of SDEs with a drift coefficient that is discontinuous in space has recently gained a lot of interest. Such SDEs arise e.g. in mathematical finance, insurance and stochastic control problems. Classical techniques of error analysis are not applicable to such SDEs and well known convergence results for standard methods do not carry over in general.
In this talk I will present recent results on strong approximation of such SDEs.
Larisa Yaroslavtseva's (University of Graz) talk is based on joint work with Arnulf Jentzen (University of Münster) and Thomas Müller-Gronbach (University of Passau).
on Tuesday 06.06.2023 at 10:00 am at the seminar room SR 11.34
or, online, using the Unimeet link: https://unimeet.uni-graz.at/b/tan-b5q-noz-k0a