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 editorsBriand, Philippe; Geiss, Christel; Geiss, Stefan; Labart, Céline

Journal or seriesBernoulli

ISSN1350-7265

eISSN1573-9759

Publication year2021

Publication date01/03/2021

Volume27

Issue number2

Pages range899-929

PublisherInternational Statistical Institute

Publication countryNetherlands

Publication languageEnglish

DOIhttps://doi.org/10.3150/20-BEJ1259

Publication open accessNot open

Publication channel open accessChannel 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.


Keywordsdifferential equationsstochastic processesconvergenceapproximation

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


Contributing organizations


Ministry reportingYes

Reporting Year2021

JUFO rating2


Last updated on 2024-03-04 at 20:16