An Efficient Numerical Method for Forward-Backward Stochastic Differential Equations Driven by G-Brownian motion
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In this paper, we study the numerical method for solving forward-backward stochastic differential equations driven by G-Brownian motion (G-FBSDEs) which correspond to fully nonlinear partial differential equation (PDEs). First, we give an approximate conditional G-expectation and obtain feasible methods to calculate the distribution of G-Brownian motion. On this basis, some efficient numerical schemes for G-FBSDEs are then proposed. We rigorously analyze errors of the proposed schemes and prove the convergence results. Finally, several numerical experiments are given to demonstrate the accuracy of our method.
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