Abstract

We provide a systematic framework for studying high-frequency risk connectedness among world stock markets. Our framework, based on high-frequency realized volatility decompositions, TVP-VAR networks, and innovative extensions, shows risk connectedness among 16 world stock markets with respect to seven levels of high-frequency volatility. The findings are as follows. First, all seven levels of risk connectedness are significantly enhanced in response to extreme event shocks. The COVID-19 event led to a peak in total connectedness, and the event changed the structure of the spillover network the most, with markets in Asia-Pacific continent being the most affected by this event. The transmission of information is unique to different levels, with the “bad” volatility level being the strongest and the jump volatility level being the most sensitive. Second, there is a geographical effect on stock market performance, with the U.S. stock market being the most stable and dominant. The mainland Chinese stock market is the most vulnerable to volatility, being a net receiver of volatility 91.04% of the time. Third, we provide evidence of asymmetric spillovers at the level of “good-bad” volatility and “good-bad” jumps. The similarity between these two asymmetric effects is that the negative asymmetry is substantial and more pronounced in response to risky event shocks. The difference is that the asymmetry of “good-bad” jumps reflects more strongly the impact of crisis event shocks. Seven countries are dominated by pessimism most of the time, with the UK, Canada and Mexico being the main transmitters of pessimism, and their ability to transmit pessimism has increased during the crisis.

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