Multiscale extreme risk spillovers among the Chinese mainland, Hong Kong, and London stock markets: Comparing the impacts of three Stock Connect programs

This paper investigates the multiscale extreme risk spillovers among Shanghai, Shenzhen, Hong Kong, and London stock markets by combining the wavelet decomposition and time-varying copula-CoVaR methods, and compares the impacts of three Stock Connect programs proposed by China. Based on the daily closing prices of four stock indexes ranging from Jan 4, 2013, to Jan 21, 2022, we find that multiscale extreme risk spillovers significantly exist among four stock markets with dynamic and asymmetric characteristics. The magnitudes of risk spillover effects decrease as the time scale increases. The implementation of the SH-HK and SH-L programs could improve the spillovers between related stock markets, while the SZ-HK program possesses a slightly decreasing effect, and their impacts are lower than the external shock events. These results systematically reveal the extreme risk transmission features among four stock markets, which are beneficial for practical portfolio optimization and risk management in the opening stock markets.

Automated summary

This paper investigates the multiscale extreme risk spillovers among Shanghai, Shenzhen, Hong Kong, and London stock markets by combining the wavelet decomposition and time-varying copula-CoVaR methods, and compares the impacts of three Stock Connect programs proposed by China. The results show that there are dynamic and asymmetric multiscale extreme risk spillovers among the four stock markets, and the magnitudes of risk spillover effects decrease as the time scale increases. The implementation of the stock connect programs can improve the spillovers between related stock markets, but their impacts are lower than external shock events.