两因子期权定价模型的条件蒙特卡罗加速方法

Efficient Accelerating Method of Conditional Monte Carlo Simulation for Two factor Option Pricing Model

摘要:

对一类随机波动率模型下的欧式期权定价问题，首先推导出条件蒙特卡罗方法的计算框架，然后基于鞅表示定理构造了一类有效的控制变量．数值实验结果表明：结合鞅控制变量的条件蒙特卡罗方法有效地减小蒙特卡罗模拟误差,对模型参数的依赖性小．

Abstract:

The conditional Monte Carlo method was constructed for pricing European options under stochastic volatility model, and then an efficient control variate was presented based on the Martingale representation theorem. Numerical tests show that conditional Monte Carlo simulations based on the martingale control variate method can reduce simulation error. Moreover the dependence of the efficiency of simulation on model parameters is not sensitive.