The dynamic risk spillover of higher-order moments in the China's energy market: A time-frequency perspective

This study employs a risk spillover measurement method based on CEEMDAN-SE, GARCHSK, and TVP-VAR-DY models to assess risk spillover among 11 sub-sectors in China's energy market, such as coal, oil, thermal power, and new energy vehicles. The energy sector index return is decomposed into intrinsic mode functions (IMFs) and reconstructed into high, medium, and low-frequency sequences. The GARCHSK model calculates conditional mean, variances, skewness, and kurtosis sequences for these sequences, which are then integrated into the TVP-VAR-DY model to evaluate return, volatility, and higher-order moment risk spillovers. Empirical findings highlight significant time-varying spillover effects, with return and volatility spillovers surpassing average total skewness and kurtosis spillovers. The New Energy Vehicle (NEV) and Electric Power Grid (EPG) sectors act as major risk transmitters, while primary risk receivers vary by frequency and order. Regulatory authorities should develop a real-time surveillance mechanism to monitor the transfer of risks between the NEV sector and the EPG sector. It is essential to foster inter-industry cooperation to facilitate better resource allocation and swift response to emerging challenges. Furthermore, policymakers should focus on bolstering the resilience of pivotal sectors by employing dynamic risk management strategies and providing appropriate incentives.