Monte Carlo Acceleration Method for Pricing Asian Options in High Performance Computing

Abstract:

An investigation was made into the control variate method of Monte Carlo simulation to price Asian options by stochastic volatility model with central processing unit(CPU) cluster and graphic processing unit(GPU) devices. By taking arithmetic average Asian options with stochastic volatility under discrete monitoring time as example, an efficient control variate was chosen, and the computing efficiencies between algorithm accelerating method and devices accelerating method in CPU cluster and GPU were studied respectively. The relationship between the computation results and the parameters of the model was explored. Numerical results show that an investigation of the two accelerating methods can shorten the computation time a lot.