IDEAS home Printed from https://ideas.repec.org/p/ags/aaea26/404348.html

How Two Trade Wars Have Rewired Soybean Markets: Price Discovery, Risk Spillovers,and Liquidity Effects

Author

Listed:
  • Bobbie, Kelvin

Abstract

This study examines how trade-war shocks reshape soybean markets beyond their effects on prices. Focusing on the 2018–2019 Sino–U.S. trade war and the renewed trade disruptions of 2025, we evaluate whether restrictions on access to China, the world's largest soybean importer, altered price discovery, cross-commodity linkages, risk transmission, and market quality in soybean futures markets. We combine daily futures data from the Chicago Board of Trade (CBOT) and China's Dalian Commodity Exchange (DCE) to compare market responses across the two episodes. Using event-study methods, connectedness measures derived from vector autoregressions, and a copulabased CoVaR framework, we analyze how trade-war shocks affect information leadership in U.S. soybean markets, spillovers across the agricultural complex, and tail-risk transmission between U.S. and Chinese soybean markets. We hypothesize that trade-war disruptions weaken the price discovery role of CBOT soybean futures, intensify risk spillovers, and reduce market quality through higher volatility and lower liquidity. Findings will contribute to understanding how geopolitical trade disruptions affect commodity market resilience, information transmission, and the reliability of benchmark agricultural futures markets.

Suggested Citation

  • Bobbie, Kelvin, 2026. "How Two Trade Wars Have Rewired Soybean Markets: Price Discovery, Risk Spillovers,and Liquidity Effects," 2026 Annual Meeting, July 26 - 28, 2026, Kansas City, Missouri 404348, Agricultural and Applied Economics Association.
  • Handle: RePEc:ags:aaea26:404348
    DOI: 10.22004/ag.econ.404348
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/404348/files/177464_192235_115232_Kelvin_Bobbie-_How_Two_Trade_Wars_Have_Rewired_US_Soybean_Markets.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.404348?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Adjemian, Michael K. & Smith, Aaron & He, Wendi, 2021. "Estimating the market effect of a trade war: The case of soybean tariffs," Food Policy, Elsevier, vol. 105(C).
    2. Ing-Haw Cheng & Wei Xiong, 2014. "Financialization of Commodity Markets," Annual Review of Financial Economics, Annual Reviews, vol. 6(1), pages 419-441, December.
    3. Jinzhi Li, 2026. "Dynamic risk spillovers from crude oil to agricultural commodities: a Markov-switching copula approach," Empirical Economics, Springer, vol. 70(1), pages 1-31, January.
    4. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    5. repec:ags:jrapmc:122315 is not listed on IDEAS
    6. Karali, Berna, 2012. "Do USDA Announcements Affect Comovements Across Commodity Futures Returns?," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 37(01), pages 1-21, April.
    7. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    8. Scarcioffolo, Alexandre Ribeiro & Etienne, Xiaoli L., 2019. "How connected are the U.S. regional natural gas markets in the post-deregulation era? Evidence from time-varying connectedness analysis," Journal of Commodity Markets, Elsevier, vol. 15(C), pages 1-1.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Evrim Mandacı, Pınar & Cagli, Efe Çaglar & Taşkın, Dilvin, 2020. "Dynamic connectedness and portfolio strategies: Energy and metal markets," Resources Policy, Elsevier, vol. 68(C).
    2. Zhang, Hua & Chen, Jinyu & Shao, Liuguo, 2021. "Dynamic spillovers between energy and stock markets and their implications in the context of COVID-19," International Review of Financial Analysis, Elsevier, vol. 77(C).
    3. Pinto-Ávalos, Francisco & Bowe, Michael & Hyde, Stuart, 2024. "Revisiting the pricing impact of commodity market spillovers on equity markets," Journal of Commodity Markets, Elsevier, vol. 33(C).
    4. Finta, Marinela Adriana, 2025. "Risk premia-return spillovers among commodity-U.S. equity markets," International Review of Economics & Finance, Elsevier, vol. 102(C).
    5. Guhathakurta, Kousik & Dash, Saumya Ranjan & Maitra, Debasish, 2020. "Period specific volatility spillover based connectedness between oil and other commodity prices and their portfolio implications," Energy Economics, Elsevier, vol. 85(C).
    6. Singh, Vipul Kumar & Kumar, Pawan, 2024. "Beyond volatility: Systemic resilience and risk mitigation in interconnected commodity markets," Energy Economics, Elsevier, vol. 140(C).
    7. Mensi, Walid & Gök, Remzi & Gemici, Eray & Kang, Sang Hoon, 2025. "Tail risk contagion and connectedness between crude oil, natural gas, heating oil, precious metals, and international stock markets," International Economics, Elsevier, vol. 181(C).
    8. Qi Xu & Yang Ye, 2023. "Commodity network and predictable returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(10), pages 1423-1449, October.
    9. Baruník, Jozef & Kočenda, Evžen & Vácha, Lukáš, 2017. "Asymmetric volatility connectedness on the forex market," Journal of International Money and Finance, Elsevier, vol. 77(C), pages 39-56.
    10. Shakya, Shishir & Li, Bingxin & Etienne, Xiaoli, 2022. "Shale revolution, oil and gas prices, and drilling activities in the United States," Energy Economics, Elsevier, vol. 108(C).
    11. Umar, Zaghum & Jareño, Francisco & Escribano, Ana, 2021. "Agricultural commodity markets and oil prices: An analysis of the dynamic return and volatility connectedness," Resources Policy, Elsevier, vol. 73(C).
    12. Just, Małgorzata & Kliber, Agata & Echaust, Krzysztof, 2025. "Return connectedness between energy commodities and stock markets: New evidence from 31 energy sector companies in Europe," International Review of Financial Analysis, Elsevier, vol. 103(C).
    13. Hachicha, Néjib & Ben Amar, Amine & Ben Slimane, Ikrame & Bellalah, Makram & Prigent, Jean-Luc, 2022. "Dynamic connectedness and optimal hedging strategy among commodities and financial indices," International Review of Financial Analysis, Elsevier, vol. 83(C).
    14. Libo Yin & Hong Cao, 2024. "Financialization of commodity markets: New evidence from temporal and spatial domains," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(8), pages 1357-1382, August.
    15. Ghaemi Asl, Mahdi & Adekoya, Oluwasegun Babatunde & Rashidi, Muhammad Mahdi & Ghasemi Doudkanlou, Mohammad & Dolatabadi, Ali, 2022. "Forecast of Bayesian-based dynamic connectedness between oil market and Islamic stock indices of Islamic oil-exporting countries: Application of the cascade-forward backpropagation network," Resources Policy, Elsevier, vol. 77(C).
    16. Ordu-Akkaya, Beyza Mina & Soytas, Ugur, 2020. "Unconventional monetary policy and financialization of commodities," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    17. Papież, Monika & Rubaszek, Michał & Szafranek, Karol & Śmiech, Sławomir, 2022. "Are European natural gas markets connected? A time-varying spillovers analysis," Resources Policy, Elsevier, vol. 79(C).
    18. Cui, Jinxin & Maghyereh, Aktham, 2023. "Higher-order moment risk connectedness and optimal investment strategies between international oil and commodity futures markets: Insights from the COVID-19 pandemic and Russia-Ukraine conflict," International Review of Financial Analysis, Elsevier, vol. 86(C).
    19. Juncal Cunado & David Gabauer & Rangan Gupta, 2024. "Realized volatility spillovers between energy and metal markets: a time-varying connectedness approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-17, December.
    20. Yuexiang Jiang & Luyuan Zheng & Jiazhen Wang, 2021. "Research on external financial risk measurement of China real estate," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5472-5484, October.

    More about this item

    Keywords

    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:aaea26:404348. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/aaeaaea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.