Cross-market spillover effects of energy risks: from the perspective of GARCH-CQR-based CoVaR model

This study quantifies risk spillover effects from multi-dimensional energy markets to China's Guangdong carbon market by constructing an EGARCH-CQR-based CoVaR model, which integrates the Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH) framework to capture volatility leverage effects and clustering, combined with quantile regression for precise characterization of cross-market tail dependencies. Empirical analysis reveals significant structural heterogeneity in energy-to-carbon risk spillovers: traditional energy markets, such as oil and coke, exhibit ‘high-intensity, high-volatility’ shock patterns that transmit abrupt short-term risks during global crises like the COVID-19 outbreak, whereas new energy markets, including new energy vehicles and wind power, demonstrate ‘low-intensity, persistent’ spillover dynamics reflecting stronger market resilience. Additionally, China's ‘Dual Carbon’ policy reinforcement is identified as a critical policy transmission channel that significantly intensifies risk linkages between high-carbon energy sectors and the carbon market, with model validation confirming the robustness and coverage capability of the proposed GARCH-CQR-CoVaR framework.