基于Copula-GARCH模型的原油市场和股票市场相关性研究

由于原油市场和股票市场之间的联动性日益增强,因此研究两个市场之间的关联特征,分析原油价格波动对股市的影响,有助于规避风险,保证经济持续平稳地增长.采用Copula-GARCH模型对WTI原油价格的收益率序列和NASDAQ股指的收益率序列进行实证分析.结果表明,GARCH(1,1)-t模型拟合两个序列的条件边缘分布效果最好,时变SJC Copula模型比常相关Copula模型能更好地刻画两个市场之间的相关关系.两个收益率序列之间存在正的相关关系,且相关关系具有时变性,相关结构具有一定的不对称性,上尾相关系数小于下尾相关系数,即两个市场同时出现价格极端下跌的可能性更大.这为中国金融市场风险管理,规避油价波动对股市的冲击提供一定的参考依据.

Research on the Correlation between Crude Oil Market and Stock Market Based on Copula-GARCH Model

As the linkage between the crude oil market and the stock market is increasing, studying the correlation characteristics between the two markets and analyzing the impact of crude oil price fluctuations on the stock market will help avoid risks and ensure sustained and stable economic growth. The Copula-GARCH model is used to empirically analyze the return sequence of WTI crude oil price and the return sequence of NASDAQ stock index. The results show that the GARCH(1,1)-t model fits the conditional marginal distribution of the two sequences best and the time-varying SJC Copula model can better describe the correlation between the two markets than the often correlated Copula model. There is a positive correlation between the two return rate series, the correlation is time-varying, and the correlation structure has a certain asymmetry. The upper-tail correlation coefficient is smaller than the lower-tail correlation coefficient, that is, the possibility of extreme price drops in the two markets at the same time Bigger. This provides a certain reference basis for risk management in China''s financial market and avoiding the impact of oil price fluctuations on the stock market.