基于蒙特卡洛方法的金融市场风险VaR的算法分析

Algorithm Analysis of VaR in Financial Market Based on Monte Carlo Method

为解决蒙特卡洛(Monte Carlo)方法在计算风险价值(Value at Risk,VaR)方面的缺陷,文章首先引入GARCH模型来刻画金融数据的波动聚集性,再引入马尔科夫链蒙特卡洛(Markov Chain Monte Carlo,MCMC)方法,来克服GARCH模型参数估计约束条件带来的估计误差。通过对上证50指数的实证分析表明,引入MCMC方法可以提高模型的估计精确度。

In order to solve the defects of Monte Carlo method in the calculation of Value at Risk （VaR）, this paper introduces the GARCH model to describe the volatility and aggregation of financial data. And then the paper introduces Markov Chain Monte Carlo （MCMC） to overcome the errors resulted from the restrictions of parameter estimation of GARCH model. The empirical analysis on the SSE50 index shows that the introduction of MCMC estimation method improves the estimation accuracy of the model.