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
VIRTA submission year: 2021
JUFO rating: 2