Numerical approximation of general Lipschitz BSDEs with branching processes

We extend the branching process based numerical algorithm of Bouchard et al. [3], that is dedicated to semilinear PDEs (or BSDEs) with Lipschitz nonlinearity, to the case where the nonlinearity involves the gradient of the solution. As in [3], this requires a localization procedure that uses a prior...

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Bibliographic Details
Main Authors: Bouchard Bruno, Tan Xiaolu, Warin Xavier
Format: Article
Language:English
Published: EDP Sciences 2019-01-01
Series:ESAIM: Proceedings and Surveys
Online Access:https://www.esaim-proc.org/articles/proc/pdf/2019/01/proc196513.pdf
Description
Summary:We extend the branching process based numerical algorithm of Bouchard et al. [3], that is dedicated to semilinear PDEs (or BSDEs) with Lipschitz nonlinearity, to the case where the nonlinearity involves the gradient of the solution. As in [3], this requires a localization procedure that uses a priori estimates on the true solution, so as to ensure the well-posedness of the involved Picard iteration scheme, and the global convergence of the algorithm. When, the nonlinearity depends on the gradient, the later needs to be controlled as well. This is done by using a face-lifting procedure. Convergence of our algorithm is proved without any limitation on the time horizon. We also provide numerical simulations to illustrate the performance of the algorithm.
ISSN:2267-3059