金融市场之间相关性的研究一直备受重视。金融危机等极端事件的发生增加了市场之间的尾部相关性。TailCoR模型是一种新的度量尾部相关性的方法，它将相关性分解为线性和非线性两种成分，该模型在小样本下表现良好。为刻画金融市场之间的动态相关性，提出动态TailCoR模型，并基于动态TailCoR模型将相关性分解为动态线性和动态非线性相关系数，其中动态线性相关系数基于DCC-GARCH模型进行估计，将动态TailCoR除以动态线性相关系数的余下部分定义为动态非线性相关系数。最后，基于动态TailCoR模型研究国内4家大型银行股价收益率的尾部相关性，发现尾部相关性在两个时间段出现显著上升，分别是2008年和2015—2016年初，并且尾部相关性的上升主要是由非线性相关性引起的。本文提出的方法能够用于动态非线性相关性的度量，可在组合投资和风险度量等方面获得应用。
The research on the correlation between financial markets has been valued by scholars. The occurrence of extreme events such as financial crisis increases the tail correlation between markets. The TailCoR model is a new method for measuring the tail correlation, which decomposes the correlation into linear and nonlinear components and performs well in small samples. In order to describe the dynamic correlation between financial markets, we propose dynamic TailCoR model, and decompose the correlation into dynamic linear and nonlinear correlation coefficients based on the dynamic TailCoR model. The dynamic linear correlation coefficient is estimated based on DCC-GARCH. The remainder of the dynamic TailCoR divided by the dynamic linear correlation coefficient is defined as the dynamic nonlinear correlation coefficient. Finally, based on the dynamic TailCoR model, the tail correlation of the stock returns of the four large domestic banks is studied. It is found that the tail correlations increase significantly in two periods, namely, in 2008 and from 2015 to early 2016, and the tail correlation rise is mainly caused by the nonlinear correlation. The research methods proposed in this paper give dynamic nonlinear correlation metrics, which can be well applied in investment and risk measurement.
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