On the homotopy analysis method for backward/forward-backward stochastic differential equations
For researchers in science, engineering, and finance dealing with high-dimensional BSDEs/FBSDEs, the HAM offers a more efficient analytic approximation than existing numerical methods.
The paper applies the homotopy analysis method (HAM) to solve backward and forward-backward stochastic differential equations, achieving high accuracy for a 6-dimensional case in less than 1% CPU time compared to a numerical method, with slower complexity growth as dimensionality increases.
In this paper, an analytic approximation method for highly nonlinear equations, namely the homotopy analysis method (HAM), is employed to solve some backward stochastic differential equations (BSDEs) and forward-backward stochastic differential equations (FBSDEs), including one with high dimensionality (up to 12 dimensions). By means of the HAM, convergent series solutions can be quickly obtained with high accuracy for a FBSDE in a 6 dimensional case, within less than $1\%$ CPU time used by a currently reported numerical method for the same case [34]. Especially, as dimensionality enlarges, the increase of computational complexity for the HAM is not as dramatic as this numerical method. All of these demonstrate the validity and high efficiency of the HAM for the backward/forward-backward stochastic differential equations in science, engineering and finance.