A gradient method for high-dimensional BSDEs-Reference-Cited by-同舟云学术

A gradient method for high-dimensional BSDEs

Published:2024-02-14 Issue:2 Volume:30 Page:183-203
ISSN:0929-9629
Container-title:Monte Carlo Methods and Applications
language:en
Short-container-title:

Author:

Gnameho Kossi¹,Stadje Mitja²,Pelsser Antoon³

Affiliation:

1. Essec, Cergy, France ; and Department of Quantitative Economics , Maastricht University , Maastricht , Netherlands

2. Faculty of Mathematics and Economics , University of Ulm , Ulm , Germany

3. Department of Quantitative Economics , Maastricht University , Maastricht , Netherlands

Abstract

Abstract We develop a Monte Carlo method to solve backward stochastic differential equations (BSDEs) in high dimensions. The proposed algorithm is based on the regression-later approach using multivariate Hermite polynomials and their gradients. We propose numerical experiments to illustrate its performance.

Publisher

Walter de Gruyter GmbH

Link

https://www.degruyter.com/document/doi/10.1515/mcma-2024-2002/pdf

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