Abstract

Extreme weather, as well as policy uncertainties associated with climate change, have fueled global energy market turbulence and cross-market risk contagion, which have had serious effects on the economy. Using time-frequency network analysis based on quantile vector autoregression (QVAR), this study reveals the risk spillovers between China's energy, financial, and carbon markets in different time and frequency domains. The effects of extreme weather and policy uncertainty on market risk spillovers are also examined. The results show that: (1) Risk spillovers vary significantly in different time and frequency domains, and extreme risks tend to occur in the tails of the shock distribution, and market risk spillovers occur mainly in the long term; (2) Extreme weather and policy uncertainty significantly affect energy, financial, and carbon markets, altering their net spillover levels. Among which the coal market is the most volatile and highly sensitive to changes in external conditions; (3) Risk spillovers exhibit distinct time-varying characteristics, with extreme weather, climate policy uncertainty, and trade policy uncertainty exacerbating market risk spillovers. These findings could serve as a reference for monitoring market risk spillovers, facilitating energy transition, and achieving dual‑carbon targets.

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