| Summary: | This paper studies the intraday return and volatility spillovers of Chinese CSI 300 industry indices with high-frequency data over the period from May 2012 to June 2016. The dynamic correlation among the industries is calculated with VEC-DCC-GARCH model. The result shows that the correlations between the CSI 300 industry indices are high, but they are susceptible to fluctuation of the index. Furthermore, spillover indicators are calculated with the generalized variance decomposition method with intraday return and volatility, respectively. The time window-rolling method is applied to construct the return and volatility spillover index, which was proposed by Diebold and Yilmaz as connectedness, to discover the dynamic characteristics of CSI 300 industrial return and volatility spillover effect. We conclude that the dynamic characteristics of return and volatility spillover have strong early warning effect on systemic risk, especially the spillover dynamics of the finance and real estate industry. Finally, additional tests are performed with different sample frequencies and forecast steps to prove the robustness of our results.
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