This paper aims to study the dynamic risk connection between the Climate Policy Uncertainty Index (CPU) of the United States and the grain commodity market. Our findings denote that (a) quantile spillover is stronger at extreme than median levels, underscoring the value of systematic risk spillovers in extreme market conditions. (b) Wavelet coherence analysis proposes that the structure of the CPU connection with the grain commodity market is heterogeneous at time–frequency scales. (c) Under conditions of market stability, CPU's capability to predict risks in the most segmented grain commodity markets was not as pronounced as in extreme market scenarios. (d) The spillovers between CPU and major grain commodities under diverse quantile states were significantly influenced by climate change. Results from this paper have practical implications for investors managing climate‐related risk exposures and will also assist policymakers in developing countries to develop a sensible policy package.

We first employ the method of multivariate GARCH models and Vine-Copula-CoVaR to analyse relationships between dependence, systematic risk spillover, and volatility spillover between the USD/CNY exchange rate and the returns on WTI crude oil futures and the Chinese stock market since China's 2005 foreign exchange reform. We utilise daily data from 2005 to 2020. We find a more complex dependence of the USD/CNY exchange rate on stock markets and WTI crude oil prices. All have negative risk spillovers among paired markets, with WTI having the most substantial risk spillover. However, the strength of the systematic risk spillover varies across markets. Based on the results of the VAR(1)-BEKK-GARCH $(1,1)$ and Wald tests confirm that there is a substantial mean spillover from the Chinese stock market and the USD/CNY exchange rate to the WTI crude oil price, whereas there is a more significant spillover from the WTI crude oil price to Chinese stock market volatility. The empirical findings extend the systematic understanding of the international crude oil price shocks to the dependence and transmission mechanism between the Chinese stock market and the USD/CNY exchange rate (USD/CNY). Our findings can help investors and policymakers to manage risk better and develop more sensible market rules.