基于非参数分布的沪深股市VaR测度

沪深大盘指数的收益率分布函数并不服从通常人们所认为的正态分布.因此,采用一种新的方法—非参数核密度估计,对沪深股指收益率分布进行拟合.该方法不仅很好地刻画了收益率分布的尖峰和肥尾特征,而且由此建立的VaR模型比一般的基于参数分布的VaR模型更能捕捉市场的风险特征,结论也更加准确.

The Application of VaR Model of Nonparametric Distribution on Financial risk Management

As we known,the distribution function of return is not complying with the normal distribution in Shanghai and Shenzhen Stock Markets.Therefore,the paper uses a new method-nonparametric kernel density estimation to research the distribution function of return on Shanghai and Shenzhen Stock Indices.The method is better to depict the characters of multi-peaks and fat tail on return distribution,and based on the method we construct the VaR model to capture the more risks on markets than those of based on the general parametric distribution,so the results are much more accurate.