We examine the complex dependence structure and risk spillovers between the Chinese stock market and twelve major international markets. To this end, we employ three types of vine copulas and tests for the Granger causality in risk of Hong et al. (2009). The results indicate that the R-vine copula is the optimal model to characterize the high-dimensional dependence structure of the markets after China joined the WTO, which suggests obvious structural differences with varying degrees of mainly positive dependences. Moreover, we identify unilateral extreme risk spillovers from China to the United States, France, and Germany, and either from Japan to China. We also detect bilateral spillovers between China and the United States, Japan, as well as Australia.
An analysis of the dependence structure among certain European indices (FTSE100, CAC40, DAX30, ATX20, PX, BUX and BIST) has been conducted. The main features of the financial data were studied: asymmetry, fat-tailedness (leptokurtosis), variability and mutual dependence. We have fitted a regime switching copula based model including asymmetric and fat-tailed copulas. All the indices are left-skewed and fat-tailed. Large indices are more skewed and less fail-tailed. The findings suggest that size of a market has an influence on its properties. A particular behaviour of the Turkish market suggests the importance of geographical factors. It is also suggested that the maturity of a market is insignificant in the analysis. Another important conclusion drawn from our empirical investigation is that VaR is a less exact risk measure than ES. However, the dynamics of the temporal and statistical properties of both measures are similar
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