A1 Journal article (refereed)
Donsker-type theorem for BSDEs : Rate of convergence (2021)

Briand, P., Geiss, C., Geiss, S., & Labart, C. (2021). Donsker-type theorem for BSDEs : Rate of convergence. Bernoulli, 27(2), 899-929. https://doi.org/10.3150/20-BEJ1259

JYU authors or editors

Publication details

All authors or editors: Briand, Philippe; Geiss, Christel; Geiss, Stefan; Labart, Céline

Journal or series: Bernoulli

ISSN: 1350-7265

eISSN: 1573-9759

Publication year: 2021

Publication date: 01/03/2021

Volume: 27

Issue number: 2

Pages range: 899-929

Publisher: International Statistical Institute

Publication country: Netherlands

Publication language: English

DOI: https://doi.org/10.3150/20-BEJ1259

Publication open access: Not open

Publication channel open access: Channel is not openly available

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/75131

Web address of parallel published publication (pre-print): https://arxiv.org/abs/1908.01188v1

Abstract

In this paper, we study in the Markovian case the rate of convergence in Wasserstein distance when the solution to a BSDE is approximated by a solution to a BSDE driven by a scaled random walk as introduced in Briand, Delyon and Mémin (Electron. Commun. Probab. 6 (2001) Art. ID 1). This is related to the approximation of solutions to semilinear second order parabolic PDEs by solutions to their associated finite difference schemes and the speed of convergence.

Keywords: differential equations; stochastic processes; convergence; approximation

Free keywords: backward stochastic differential equations; convergence rate; Donsker’s theorem; finite difference scheme; scaled random walk; Wasserstein distance

Contributing organizations

Ministry reporting: Yes

Reporting Year: 2021

JUFO rating: 2