A gradient method for high-dimensional BSDEs

Kossi Gnameho, Stadje Mitja () and Antoon Pelsser
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Stadje Mitja: Faculty of Mathematics and Economics, University of Ulm, Ulm, Germany

Monte Carlo Methods and Applications, 2024, vol. 30, issue 2, 183-203

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.

Keywords: Regression; BSDE; Monte Carlo; Hermite polynomials (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1515/mcma-2024-2002

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