An efficient numerical method for forward-backward stochastic differential equations driven by G-Brownian motion

Existence and Measurability of the Solution of the Stochastic Differential Equations Driven by Fractional Brownian Motion

Numerical Method for Backward Stochastic Differential Equations

We propose a method for numerical approximation of Backward Stochastic Differential Equations. Our method allows the final condition of the equation to be quite general and simple to implement. It relies on an approximation of Brownian Motion by simple random walk.

Reflected Backward Stochastic Differential Equations Driven by Countable Brownian Motions

In this note, we study one-dimensional reflected backward stochastic differential equations (RBSDEs) driven by Countable Brownian Motions with one continuous barrier and continuous generators. Via a comparison theorem, we provide the existence of minimal and maximal solutions to this kind of equations.

Numerical Algorithms for Forward-Backward Stochastic Differential Equations

Efficient numerical algorithms are proposed for a class of forward-backward stochastic differential equations (FBSDEs) connected with semilinear parabolic partial differential equations. As in [J. Douglas, Jr., J. Ma, and P. Protter, Ann. Appl. Probab., 6 (1996), pp. 940–968], the algorithms are based on the known four-step scheme for solving FBSDEs. The corresponding semilinear parabolic equat...

existence and measurability of the solution of the stochastic differential equations driven by fractional brownian motion