Abstract
The increasingly predominant financial attributes of China's carbon market elevate tail risk exposure, necessitating a comprehensive analysis of multiscale risk contagion to inform responsive supervision and targeted risk prevention. This study employs the conditional autoregressive value at risk (CAViaR) model and the time-frequency connectedness approach to explore the multiscale tail risk contagion across carbon, rare earth, and energy markets in China. Further, we apply the multivariate quantile-on-quantile regression approach to examine the extent to which tail risk spillover is driven by China's climate and economic policy uncertainties, and geopolitical risk. Empirical results reveal that the carbon pilots shift their roles from short-term net recipients of rare earth market risks to long-term sources of risk transmitters to the rare earth market. During extreme intermediate-and long-term spillovers, economic policy uncertainty magnifies risk spillovers, whereas climate policy uncertainty suppresses them. Geopolitical risk generally dampens tail risk spillover but amplifies it at extreme highs. These findings facilitate the development of a risk warning system tailored to various timeframes within China's carbon trading framework, thereby improving risk management strategies amid uncertainties.
