Parallel computing for option pricing based on the backward stochastic differential equation

The Backward Stochastic Differential Equation (BSDE) is a robust tool for financial derivatives pricing and risk management. In this paper, we explore the opportunity for parallel computing with BSDEs in financial engineering. A binomial tree based numerical method for BSDEs is investigated and applied to option pricing. According to the special structure of the numerical model, we develop a block allocation algorithm in parallelization, where large communication overhead is avoided. Runtime experiments manifest optimistic speedups for the parallel implementation.