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Futures-Based Forecasts of U.S. Crop Prices

Author

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  • Zhu, Jiafeng
  • Isengildina-Massa, Olga Isengildina-

Abstract

This study proposed two futures-based models for forecasting cash prices of corn, soybeans, wheat and cotton over the period 2000-2016. The difference model predicts changes in cash prices as a function of changes in futures prices. The regime model specifies different market regimes and models cash price levels based on observed futures prices in various regimes. The out-of-sample performance of both models was compared to the benchmark of a 5-year moving average over the 2013-2016 sub-period. Our results suggest that the regime model performed best for corn and soybeans. While, neither model beat the benchmark for wheat at the longer forecasted horizons, the difference model performed well at short forecast horizons (up to 5-months ahead). Both models performed better than the benchmark for cotton price forecasts, but they were not significantly different from each other.

Suggested Citation

  • Zhu, Jiafeng & Isengildina-Massa, Olga Isengildina-, 2017. "Futures-Based Forecasts of U.S. Crop Prices," 2017 Conference, April 24-25, 2017, St. Louis, Missouri 285881, NCR-134/ NCCC-134 Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    • Handle: RePEc:ags:n13417:285881
    DOI: 10.22004/ag.econ.285881
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    References listed on IDEAS

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    1. C. Pederzoli & C. Torricelli, 2013. "Efficiency and unbiasedness of corn futures markets: new evidence across the financial crisis," Applied Financial Economics, Taylor & Francis Journals, vol. 23(24), pages 1853-1863, December.
    2. Trevor A. Reeve & Robert J. Vigfusson, 2011. "Evaluating the forecasting performance of commodity futures prices," International Finance Discussion Papers 1025, Board of Governors of the Federal Reserve System (U.S.).
    3. Irwin, Scott & Good, Darrel, . "The New Era of Corn and Soybean Prices Is Still Alive and Kicking," farmdoc daily, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics, vol. 6.
    4. Irwin, Scott & Good, Darrel, . "The Relationship between Stocks-to-Use and Corn and Soybean Prices: An Alternative View," farmdoc daily, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics, vol. 6.
    5. Algieri, Bernardina & Kalkuhl, Matthias, 2014. "Back to the Futures: An Assessment of Commodity Market Efficiency and Forecast Error Drivers," Discussion Papers 187159, University of Bonn, Center for Development Research (ZEF).
    6. Menzie D. Chinn & Olivier Coibion, 2014. "The Predictive Content of Commodity Futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 34(7), pages 607-636, July.
    7. Colino, Evelyn V. & Irwin, Scott H. & Garcia, Philip, 2008. "How Much Can Outlook Forecasts be Improved? An Application to the U.S. Hog Market," 2008 Conference, April 21-22, 2008, St. Louis, Missouri 37620, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    8. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
    9. William G. Tomek, 1997. "Commodity Futures Prices as Forecasts," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 19(1), pages 23-44.
    10. Westcott, Paul C. & Hoffman, Linwood A., 1999. "Price Determination for Corn and Wheat: The Role of Market Factors and Government Programs," Technical Bulletins 33581, United States Department of Agriculture, Economic Research Service.
    11. Verteramo, Leslie J. & Tomek, William G., 2015. "Anticipatory Signals of Changes in Corn Demand," 2015 Conference, April 20-21, 2015, St. Louis, Missouri 285843, NCR-134/ NCCC-134 Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    12. Irwin, Scott & Good, Darrel, . "Forming Corn and Soybean Price Expectations for 2016-17," farmdoc daily, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics, vol. 6.
    13. Linwood A. Hoffman & Xiaoli L. Etienne & Scott H. Irwin & Evelyn V. Colino & Jose I. Toasa, 2015. "Forecast performance of WASDE price projections for U.S. corn," Agricultural Economics, International Association of Agricultural Economists, vol. 46(S1), pages 157-171, November.
    14. Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 2(2), pages 111-120, July.
    15. C. Pederzoli & C. Torricelli, 2013. "Efficiency and unbiasedness of corn futures markets: new evidence across the financial crisis," Applied Financial Economics, Taylor & Francis Journals, vol. 23(24), pages 1853-1863, December.
    16. Fernandez, Viviana, 2017. "A historical perspective of the informational content of commodity futures," Resources Policy, Elsevier, vol. 51(C), pages 135-150.
    17. Irwin, Scott & Good, Darrel, . "New Corn and Soybean Pricing Models and World Stocks-to-Use Ratios," farmdoc daily, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics, vol. 6.
    18. Mark R. Manfredo & Dwight R. Sanders, 2004. "The forecasting performance of implied volatility from live cattle options contracts: Implications for agribusiness risk management," Agribusiness, John Wiley & Sons, Ltd., vol. 20(2), pages 217-230.
    19. Irwin, Scott & Good, Darrel, . "Sensitivity Analysis of New Corn and Soybean Pricing Models," farmdoc daily, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics, vol. 6.
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