How connected is the multilayer risk spillover network between worldwide climate policy uncertainty and the Chinese stock market?

Theoretically, worldwide climate policy uncertainty (CPU), including Chinese climate policy uncertainty (CCPU), US climate policy uncertainty (USCPU) and global CPU (GCPU), constitutes a critical risk source for Chinese stock markets. To examine the relationships between worldwide CPU and Chinese stock volatility risks, we construct and compare multilayer risk spillover networks based on the TVP-VAR model. System-level analysis reveals that CCPU has the strongest influence, with three network layers displaying unique evolutionary patterns but structurally intertwined relationships. These impacts all exhibit time-varying patterns driven by external shocks, but the CCPU spillovers are more drastic and sensitive. Node-level analysis indicates that upstream and high-carbon industries are exposed to the most obvious spillovers, and the banking sector exhibits similar vulnerability. Single-layer analysis underestimates the risk during stable periods, yet it surges dramatically during financial stress. We also explore the reasons behind these differences and find that the impact of the global economic situation on the CPU-stock system is more significant. Our findings provide valuable insights for investors as they assess risk and optimize asset allocation, and for regulators to prevent systemic risk.