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本文采用静、动态Copula函数以及基于秩的极大似然估计方法对中美两国基础材料行业股市尾部相关性进行研究;首先对样本数据进行重尾性质的简单描述,后采用静态和动态Copula相结合分析尾部相关性,在研究过程中加入金融危机影响因素;经过分析得出:美国基础材料行业股市收益率重尾特征明显高于我国,且两国样本数据分析结果显示左侧尾部相关性高于右侧;美国基础材料行业对我国基础材料行业股市左侧尾部具有明显映射效应,而我国能源行业对美国能源行业不具有映射效应;金融危机的发生使得两国该行业股市相关性显著增加,但这种增加只是暂时的。
In this paper, static and dynamic Copula functions and Rank-based Maximum Likelihood Estimation (MLE) are used to study the tail correlation of the stock market in the basic materials industry between China and the United States. First, the heavy-tailed nature of the sample data is briefly described. After that, static and dynamic Copula After the analysis, it is concluded that the heavy tail characteristic of the stock market returns in the US based material industry is significantly higher than that in China, and the results of the sample data from the two countries show that the left tail is correlated Above the right; the U.S. basic materials industry has a significant mapping effect on the left tail of the stock market of China’s basic materials industry, while China’s energy industry does not have a mapping effect on the US energy industry; the financial crisis has caused a significant increase in the stock market correlation between the two countries , But this increase is only temporary.