Pearson correlations of regression variables.

The linkages between the US and China, the world’s two major agricultural powers, have brought great uncertainty to the global food markets. Inspired by these, this paper examines the extreme risk spillovers between US and Chinese agricultural futures markets during significant crises. We use a copula-conditional value at risk (CoVaR) model with Markov-switching regimes to capture the tail dependence in their pair markets. The study covers the period from January 2006 to December 2022 and identifies two distinct dependence regimes (stable and crisis periods). Moreover, we find significant and asymmetric upside/downside extreme risk spillovers between the US and Chinese markets, which are highly volatile in crises. Additionally, the impact of international capital flows (the financial channel) on risk spillovers is particularly pronounced during the global financial crisis. During the period of the COVID-19 pandemic and the Russia-Ukraine 2022 war, the impact of supply chain disruptions (the non-financial channel) is highlighted. Our findings provide a theoretical reference for monitoring the co-movements in agricultural futures markets and practical insights for managing investment portfolios and enhancing food market stability during crises.

作为全球两大农业强国的美国与中国之间的联动关系，为全球粮食市场带来了极大的不确定性。基于此背景，本文针对重大危机时期中美农产品期货市场间的极端风险溢出效应展开研究。我们采用带有马尔可夫区制转换（Markov-switching regimes）的Copula-条件风险价值（Copula-Conditional Value at Risk, CoVaR）模型，以捕捉两国配对期货市场的尾部相依性。本研究的样本区间为2006年1月至2022年12月，并识别出两种截然不同的相依性区制：平稳期与危机期。此外，研究发现中美两国市场间存在显著且非对称的上行/下行极端风险溢出效应，且该效应在危机时期波动剧烈。进一步来看，国际资本流动（金融渠道）对风险溢出的影响在全球金融危机期间尤为显著；而在新冠疫情大流行及2022年俄乌冲突时期，供应链中断（非金融渠道）的影响则更为突出。本研究结论可为监测农产品期货市场的联动性提供理论参考，同时也为危机时期的投资组合管理以及提升粮食市场稳定性提供实践启示。