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Due to the advent of deglobalization and regional integration, this article aims to adopt LASSO-based network connectedness to estimate the multiscale tail risk spillover effects of global stock markets. The results show that tail risk varies across frequencies and shocks. In static analysis, the risk is centered mostly on the developed European and North American markets at a low frequency (long term), and regionalization is imposed on the moderate frequency (midterm). Moreover, emerging markets could be sources of risk spillover, especially at the highest frequency (short term) where there is no absolute risk center. In dynamic analysis, we use rolling window estimation and find that different frequencies identify distinct episodes of shocks, which provides us with the reason for the diverse risk centers at different time scales in static analysis. Our findings provide heterogeneous financial practitioners, regulators, and investors with diverse characteristics of stock markets under multiple time horizons and help them operate their own trading strategies.

This paper proposes a new network topology approach to identify the contemporaneous and noncontemporaneous idiosyncratic spillovers of lowermoment and higher-moment risks in commodity futures markets using highfrequency data. Our results show that contemporaneous information has more explanatory power in constructing a network than noncontemporaneous information, especially for higher-moment risk spillover networks. In contemporaneous spillover networks, the role of one commodity future and the structure of the networks vary across different realized estimators. Specifically, gold, silver, and wheat are the main volatility and kurtosis risk transmitters, while corn and silver are the main skewness spillover transmitters. Agricultural futures markets are relatively closed in the volatility and kurtosis risk spillover networks, while in the skewness network, they become closer to precious metal futures. Furthermore, crisis events can enlarge the idiosyncratic volatility spillovers in commodity markets. The total spillover effects of higher-moment risk are stronger than those of lower-moment risk.