基于Copula方法的股票风险的相依性分析

相依性分析在多变量随机分析研究中一直属于前沿问题,研究金融市场各股票之间的相依性,对于分析股票市场的相依性结构以及投资市场的投资组合风险有着重要的意义.选用Copula函数理论对雅虎财经数据中心的上海电力和中国石油股票日收益率数据进行数据拟合,利用核密度估计方法对股票市场估计边缘分布,结合平方欧式距离选取最优Copula函数.运用了Copula函数理论建立股票市场的相关性结构模型,更好地模拟上海电力和中国石油两股市的日收益率的观测数据.

Dependency analysis of stock risks based on the Copula method

Dependency analysis plays an important role in multivariate stochastic analysis. Research on the stock dependency of all financial markets has great significance to the dependency structure of the stock markets and the portfolio risks of investment markets. This paper analyzes the stock return data of Shanghai Electric Power and Petrochina by using the Copula function,and establishes the correlation between the structural models of the stock market. It uses the nonparametric kernel density estimation method to estimate the marginal distribution of the stock market,selects the optimal Copula function based on the square euclidean distance in order to obtain possibly better data for the stock returns of Shanghai Electric Power and Petrochina.