分别使用包含"天数变量"的Log-ACD和Copula模型对股票的连涨和连跌收益率的边缘分布以及二者的联合分布进行了拟合,检验结果表明该模型拟合的效果要优于传统方法.对上证180指数数据做了实证研究,并使用条件VaR对股票连涨连跌收益率进行风险分析,实证结果证明该模型的拟合结果与股市的实际情况是相吻合的.投资者可以依照模型得出的"涨跌风险对比图"分析当前股票市场的涨跌风险对比,从而指导投资行为.
The Log-ACD model which includes the"number of days"variable and Copula model are used respectively to fit the marginal and joint distribution of continuously rising and falling stock yield. The result of test shows that this model is comparatively better than traditional methods.In this paper, Shanghai stock 180 index is used for empirical analysis and conditional VaR is computed for risk analysis. The empirical result proves that this model is consistent to actual market,and investor can use"figure of ris...