With the growing financialization of energy markets, financial and energy security have become critical global concerns. This study overcomes the limitations of traditional methods in analyzing extreme events by adopting a conditional quantile spillover index approach. Using China’s energy market prices and financial sub-market pressure indices, it constructs Quantile Vector Autoregressive (QVAR) models for both traditional and new energy-finance systems to examine their time-varying risk spillovers. Key findings are: (1) A significant risk spillover effect exists within China’s energy-finance system. The energy market acts as the primary risk transmitter, driven by both industrial policy and market demand, while capital and foreign exchange markets are the main risk absorbers. (2) The system exhibits significant tail spillover and asymmetry. The traditional energy market is more sensitive to upside extreme risks, whereas the new energy market is more sensitive to downside extremes. (3) Uncertainties like supply demand imbalances, policy shifts, and changing domestic/international conditions are major volatility drivers. Supply demand issues primarily affect the traditional energy market, while policy adjustments trigger chain reactions in the new energy sector. Based on these insights, the paper proposes recommendations to prevent systemic risks and potential energy crises.
Du et al. (Tue,) studied this question.