Abstract

In this paper, we investigate the impact of economic policy uncertainty on the conditional dependence between China and U.S. stock markets by employing the Copula-mixed-data sampling framework. In the case of EPU, we consider the global EPU, the American EPU, and the China EPU. The empirical analysis based on the Shanghai Stock Exchange Composite index in China and the S&P 500 index in the U.S. shows that the tail dependence between China and U.S. stock markets is symmetrical, and the t Copula outperforms alternative Copulas in terms of in-sample goodness of fit. In particular, we find that the t Copula-MIDAS model with EPU dominates the traditional time-varying t Copula in terms of in-sample fitting. Moreover, we observe that both the GEPU and AEPU have a significantly positive impact on the conditional dependence between China and U.S. stock markets, whereas CEPU has no significant impact. The tail dependence between China and U.S. stock markets exhibits an increasing trend, particularly in the recent years.