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Price and Volatility Transmission in International Wheat Futures

Author

Listed:
  • Jian Yang

    (Department of Accounting, Finance and Information Systems, Prairie View A&M University)

  • Jin Zhang

    (Department of Agricultural Economics, Texas A&M University)

  • David J. Leatham

    (Department of Agricultural Economics, Texas A&M University)

Abstract

This study examines futures price and volatility transmissions among three major wheat production and exporting regions, the United States (US), Canada and the European Union (EU) over the recent six-year study period of 1996 - 2002. The price transmission pattern shows that Canadian prices are much more influenced by the US prices than the US prices are influenced by Canadian prices. The EU is highly self-dependent and may exert some influence on the US prices in the long run but not vice versa. The volatility transmission pattern, however, shows that volatility is transmitted from Canada and the EU to the US but not vice versa. The volatility is also transmitted from the EU to Canada but not vice versa. Overall, there is no distinctive leadership role in international wheat markets, with all three markets exhibiting features of price leadership to some extent.

Suggested Citation

  • Jian Yang & Jin Zhang & David J. Leatham, 2003. "Price and Volatility Transmission in International Wheat Futures," Annals of Economics and Finance, Society for AEF, vol. 4(1), pages 37-50, May.
    • Handle: RePEc:cuf:journl:y:2003:v:4:i:1:p:37-50
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    References listed on IDEAS

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    3. Du, Wen, 2004. "International Market Integration Under Wto: Evidence In The Price Behaviors Of Chinese And Us Wheat Futures," 2004 Annual meeting, August 1-4, Denver, CO 20115, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    4. Manuel A. Hernandez & Raul Ibarra & Danilo R. Trupkin, 2014. "How far do shocks move across borders? Examining volatility transmission in major agricultural futures markets," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 41(2), pages 301-325.
    5. Ida Farida & Faurani Santi Singagerda, 2021. "Volatilitiy of World Food Commodity Prices and Renewable Fuel Standard Policy," International Journal of Energy Economics and Policy, Econjournals, vol. 11(1), pages 516-527.
    6. Ge, Yuanlong & Wang, H. Holly & Ahn, Sung K., 2008. "Implication of Cotton Price Behavior on Market Integration," 2008 Conference, April 21-22, 2008, St. Louis, Missouri 37623, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    7. Ben Shepherd, 2005. "Market Power in International Commodity Processing Chains: Preliminary Results from the Coffee Market," International Trade 0511013, University Library of Munich, Germany.
    8. José César Cruz Junior & Daniel H D Capitani & Rodrigo L F Silveira, 2018. "The effect of Brazilian corn and soybean crop expansion on price and volatility transmission," Economics Bulletin, AccessEcon, vol. 38(4), pages 2273-2283.
    9. Li, Wei-Xuan & Chen, Clara Chia-Sheng & Nguyen, James, 2022. "Which market dominates the price discovery in currency futures? The case of the Chicago Mercantile Exchange and the Intercontinental Exchange," Global Finance Journal, Elsevier, vol. 52(C).
    10. Kong, Minji & Han, Doo Bong & Nayga, Rodolfo M., Jr., 2012. "Interrelationship and Volatility Transmission between Grain and Oil Prices," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124377, Agricultural and Applied Economics Association.
    11. Philipp Adämmer & Martin T. Bohl & Ernst-Oliver Ledebur, 2015. "Price Transmissions During Financialization and Turmoil: New Evidence from North American and European Agricultural Futures," CQE Working Papers 3815, Center for Quantitative Economics (CQE), University of Muenster.
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    13. Xiaojie Xu & Yun Zhang, 2022. "Forecasting the total market value of a shares traded in the Shenzhen stock exchange via the neural network," Economics Bulletin, AccessEcon, vol. 42(3), pages 1266-1279.
    14. Yuanlong Ge & Holly H. Wang & Sung K. Ahn, 2010. "Cotton market integration and the impact of China's new exchange rate regime," Agricultural Economics, International Association of Agricultural Economists, vol. 41(5), pages 443-451, September.
    15. Xiaojie Xu & Yun Zhang, 2023. "Coking coal futures price index forecasting with the neural network," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 36(2), pages 349-359, June.
    16. Mofleh Alshogeathri & Jamel Jouini, 2017. "Linkages Between Equity and Global Food Markets: New Evidence from Including Structural Changes," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 67(3), pages 166-198, June.
    17. VAN BINH, Tu & DUMONT, Michel, 2008. "A fishing expedition in the Mekong Delta: Market volatility and price substitutes for Vietnamese fresh water fish," Working Papers 2008002, University of Antwerp, Faculty of Business and Economics.
    18. Cruz, Jose Cesar Jr. & Silveira, Rodrigo L. F. & Capitani, Daniel H. D. & Urso, Fabiana S. P. & Martines, Joao G. Filho, 2016. "The effect of Brazilian corn and soybean crop expansion on price and volatility transmission," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 236127, Agricultural and Applied Economics Association.
    19. Philipp Adämmer & Martin T. Bohl & Ernst-Oliver Ledebur, 2017. "Dynamics Between North American And European Agricultural Futures Prices During Turmoil And Financialization," Bulletin of Economic Research, Wiley Blackwell, vol. 69(1), pages 57-76, January.
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    More about this item

    Keywords

    Price and volatility transmission; Generalized forecast error variance decomposition; Generalized impulse response analysis; Multivariate GARCH;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • L13 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Oligopoly and Other Imperfect Markets

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