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中国管理科学 ›› 2023, Vol. 31 ›› Issue (12): 1-10.doi: 10.16381/j.cnki.issn1003-207x.2022.2789

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基于动态模型平均的大豆期货市场风险溢出研究

叶五一,李艾琳,焦守坤()   

  1. 中国科学技术大学管理学院,安徽 合肥 230026
  • 收稿日期:2022-07-14 修回日期:2023-06-09 出版日期:2023-12-15 发布日期:2024-01-06
  • 通讯作者: 焦守坤 E-mail:jsk@ustc.edu.cn
  • 基金资助:
    国家自然科学基金资助面上项目(72371230);安徽省杰出青年基金资助项目(2208085J41)

Risk Spillover of Soybean Futures Market Based on Dynamic Model Averaging

Wu-yi YE,Ai-lin LI,Shou-kun JIAO()   

  1. School of Management,University of Science and Technology of China,Hefei 230026,China
  • Received:2022-07-14 Revised:2023-06-09 Online:2023-12-15 Published:2024-01-06
  • Contact: Shou-kun JIAO E-mail:jsk@ustc.edu.cn

摘要:

针对农产品期货市场风险规避问题,研究极端情况下中美大豆期货市场间的风险溢出效应具有重要意义。本文结合动态模型平均方法与局部分位数条件风险价值法,研究了受政策实施和经济环境变化影响的美国大豆期货市场对中国大豆期货市场的风险溢出效应,并分析了现货市场、大豆下游产品、宏观经济变量和国际市场交易等外生变量对风险溢出的影响。研究发现:不同政策和经济环境通过不同的途径对中美大豆期货市场风险溢出效应产生影响,如临时收储政策稳定了我国大豆期货价格的波动,夜盘交易制度增加了中美农产品期货市场的联动,汇改政策加大了国际市场对国内市场的影响程度。同时得到各外生变量在不同时期对中美大豆期货市场风险溢出效应变化的贡献不同,如夜盘交易制度初期,豆油期货价格和WTI原油价格对风险溢出有较大影响;而新冠疫情期间,航运指数、汇率和WTI原油价格等因素的影响处于较低水平。

关键词: 大豆期货, 风险溢出效应, CoVaR, 动态模型平均

Abstract:

It is of great significance to study the risk spillover effect between soybean futures markets in China and the United States under extreme circumstances. A dynamic model based on the average method and the method of the bureau of digit conditional value at risk are combined to study. The risk spillover effects of Chinese soybean futures market influenced by policy and economic environment change is studied. And it analyses the risk spillover effects influenced by spot market, downstream products of soybean, macro-economic variables, international market trading, etc. It is found that different policies and economic environments affected the soybean futures market risk spillover effects in different ways, such as reserve policy stability of China’s soybean futures price fluctuations, the night trading system to increase the interaction of the agricultural product futures market of China and the United States to increase the degree of impact on the domestic market in the international market. At the same time, the study shows that each control variable has a different contribution to the change in the risk spillover effect of the Chinese and American agricultural futures markets in different periods. For example, soybean oil futures price and WTI crude oil price have a great influence on the risk spillover effect in the early stage of the night trading system. The impact of shipping indices, exchange rates and WTI crude oil prices was at a low level during the COVID-19 pandemic.

Key words: soybean futures? risk spillover? CoVaR? dynamic model averaging

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