Three Algorithms for Solving High-Dimensional Fully Coupled FBSDEs Through Deep Learning

Shaolin Ji, Shige Peng, Ying Peng, Xichuan Zhang

Abstract: Recently, the deep learning method has been used for solving forward–backward stochastic differential equations (FBSDEs) and parabolic partial differential equations, as it has good accuracy and performance for high-dimensional problems. In this article, we mainly solve fully coupled FBSDEs through deep learning and provide three algorithms, and the numerical results show remarkable performance, especially for high-dimensional cases.

External IDs:dblp:journals/expert/JiPPZ20