中美投资者情绪的动态相依性——基于Copula-DCC-GARCH模型和波动率指数的研究

Dynamic Dependence of Investor Sentiments between China and US——Research Based on Copula-DCC-GARCH Model and Volatility Index

投资者情绪在市场间的传染会加速金融风险的扩散,因此随着中国资本市场的逐步开放,研究投资者情绪传染对中国资本市场的影响越来越迫切。采用波动率指数作为中美投资者情绪的代理指标,并利用Copula-DCC-GARCH模型和结构变点检验方法,对2014年以来中美两国投资者情绪动态相依性的总体特征、结构特征、时变性及突变性进行全面考察,结果表明,总体而言,中美两国投资者情绪具有整体的正向动态相依性,其动态相关系数均值为0.2448,金融风险容易从美国向中国扩散,但是牛市或熊市下投资者情绪的传染没有明显的差异;中美投资者情绪的动态相依性具有时变性,并存在5个变点,这些特征与中国经济金融基本面因素相关,且除了一个区段动态相关系数均值略小于0之外,其他区段动态相关系数均值均远大于0,说明两国投资者情绪间具有很强的相关性。

The contagion of investor sentiments in the market will accelerate the spread of financial risks,which means that with the gradual opening up of China’s capital market,it is increasingly urgent to study the impact of investor sentiment contagion.Using the volatility index as a proxy indicator of Sino-US investor sentiments,and employing the Copula-DCC-GARCH model and structural change point testing method,this study conducts a comprehensive survey of the overall condition,structural characteristics,time-varying attributes,and sudden responses of investor sentiment dynamics between China and the US since 2014.The results of the study show that investor sentiments between China and the US have an overall positive dynamic dependence,with an average value of the dynamic correlation coefficient of 0.2448,suggesting that it is easy for financial risks to spread from the US to China,although there is no obvious difference in the contagion of investor sentiments in a bull market or bear market.The dynamic dependence of investor sentiments between the two countries shows time-varying characteristics,and there are five points of change.These characteristics are related to China’s economic and financial fundamentals.The average value of the dynamic correlation coefficient of only one sector is slightly less than 0,apart from which all other sectors have an average dynamic correlation coefficient far greater than 0,indicating that there is a strong correlation between investor sentiments in the two countries.