This study investigates risk spillovers between the US dollar and Chinese stock markets through a higher‐moment analytical framework, incorporating realized volatility, skewness, kurtosis, and jumps. Using 15‐min high‐frequency data from January 3, 2016, to June 30, 2024, we construct robust estimators for higher‐order moments and employ Granger causality tests and generalized impulse response analysis within a quad‐variate VAR system. Empirical results reveal that the US dollar acts as a key driver of volatility spillovers to China’s Shanghai Composite Index, Shenzhen Component Index, and Hang Seng Index, with bidirectional volatility linkages between mainland markets and unidirectional spillovers from Hong Kong to the mainland. Notably, skewness spillovers indicate that tail risk asymmetry in the US dollar propagates to Chinese equities, while kurtosis and jump spillovers highlight the transmission of extreme risk and discontinuous price movements. These findings underscore the importance of higher‐order moments in capturing asymmetric and extreme risk channels, which traditional correlation‐based models overlook. The study provides critical insights for investors to optimize cross‐border tail risk hedging and for policymakers to monitor systemic risks, emphasizing the need for comprehensive risk management frameworks in emerging markets.
Zongfeng et al. (Thu,) studied this question.