基于MCMC方法的连续时间SV模型建模研究

Modeling of Continuous-time Stochastic Volatility Using MCMC Method

连续时间模型已被广泛地应用于资产定价中,但是它的参数估计仍存在许多困难。针对这一问题,利用基于Markov链的Monte Carlo模拟积分方法对连续时间的SV模型进行估计,选取上海股市的日综合指数进行实证研究,结果证明了所提模型和方法的有效性。

The continuous-time models have been used in the pricing of various stocks. But there are still many difficulties in the estimate. For this problem, the parameters of the model are estimated by using Markov chain Monte Carlo method and an example is taken based on Shanghai Stock Exchange index. The results show that the modle and the method are both valid.