New Second-order Convergent Schemes for Solving decoupled FBSDEs

Fuente: arXiv
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Main Authors: Wang, Wenbo, Jia, Guangyan
Format: Preprint
Published: 2026
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author Wang, Wenbo
Jia, Guangyan
author_facet Wang, Wenbo
Jia, Guangyan
contents This paper proposes a new second-order symmetric algorithm for solving decoupled forward-backward stochastic differential equations. Inspired by the alternating direction implicit splitting method for partial differential equations, we split the generator into the sum of two functions. In the computation of the value process Y, explicit and implicit schemes are alternately applied to these two generators, while the algorithms from \citep{ZhaoLi2014} are used for the control process Z. We rigorously prove that the two new schemes have second-order convergence rate. The proposed splitting methods show clear advantages for equations whose generator consists of a linear part plus a nonlinear part, as they reduce the number of iterations required for solving implicit schemes, thereby decreasing computational cost while maintaining second-order convergence. Two numerical examples are provided, including the backward stochastic Riccati equation arising in mean-variance hedging. The numerical results verify the theoretical error analysis and demonstrate the advantage of reduced computational cost compared to the algorithm in \citep{ZhaoLi2014}.
format Preprint
id arxiv_https___arxiv_org_abs_2601_10149
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle New Second-order Convergent Schemes for Solving decoupled FBSDEs
Wang, Wenbo
Jia, Guangyan
Numerical Analysis
Probability
This paper proposes a new second-order symmetric algorithm for solving decoupled forward-backward stochastic differential equations. Inspired by the alternating direction implicit splitting method for partial differential equations, we split the generator into the sum of two functions. In the computation of the value process Y, explicit and implicit schemes are alternately applied to these two generators, while the algorithms from \citep{ZhaoLi2014} are used for the control process Z. We rigorously prove that the two new schemes have second-order convergence rate. The proposed splitting methods show clear advantages for equations whose generator consists of a linear part plus a nonlinear part, as they reduce the number of iterations required for solving implicit schemes, thereby decreasing computational cost while maintaining second-order convergence. Two numerical examples are provided, including the backward stochastic Riccati equation arising in mean-variance hedging. The numerical results verify the theoretical error analysis and demonstrate the advantage of reduced computational cost compared to the algorithm in \citep{ZhaoLi2014}.
title New Second-order Convergent Schemes for Solving decoupled FBSDEs
topic Numerical Analysis
Probability
url https://arxiv.org/abs/2601.10149