Time-frequency spillover and early warning of climate risk in international energy markets and carbon markets: From the perspective of complex network and machine learning

On the road to a new green economy, it is necessary to clarify the synergistic movement between climate risk, international energy markets and carbon markets. After comprehensively considering climate supervision and investors' concern to assess climate risk, this paper selects the monthly price data of international energy markets and carbon markets from 2012 to 2023, analyzes the dynamic spillover in “climate - energy - carbon” system by using TVP-VAR-BK spillover index model, complex network method and GA-WLSSVM model, reveals the infection path of climate risk, and realizes cross-markets early warning of climate risk. The findings indicate that: (1) The interactive overflow between climate risk, international energy markets and carbon markets is time-varying and heterogeneous. (2) As the time period lengthens, climate risk and carbon markets gradually become the importers of spillovers, and clean energy gradually becomes the recipients of spillovers. (3) Climate risk is the key node in the connectivity network. Cross-markets risk mainly diffuses along the path of "clean energy markets – traditional energy markets - carbon markets". (4) Machine learning model can timely and effectively carry out climate risk early warning from the perspective of system connectivity.