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Outlook vs. Futures: Three Decades of Evidence in Hog and Cattle Markets

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  • Evelyn V. Colino
  • Scott H. Irwin

Abstract

The accuracy of hog and cattle price forecasts from four outlook programs is compared with forecasts derived from futures markets. Most of the series begin in the mid to late 1970s and end in 2007. Root mean squared error (RMSE) comparisons indicate the difference between outlook and futures RMSE is relatively small in most cases. In directional terms, outlook forecasts beat futures prices only 2 out of 11 times in hogs, and 1 out of 7 times in cattle. However, the null hypothesis that futures encompasses outlook is rejected in 5 of 11 cases for hogs, and 4 of 7 cases for cattle. Copyright 2010, Oxford University Press.

Suggested Citation

  • Evelyn V. Colino & Scott H. Irwin, 2010. "Outlook vs. Futures: Three Decades of Evidence in Hog and Cattle Markets," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 92(1), pages 1-15.
    • Handle: RePEc:oup:ajagec:v:92:y:2010:i:1:p:1-15
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    File URL: http://hdl.handle.net/10.1093/ajae/aap013
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    1. Colino, Evelyn V. & Irwin, Scott H. & Garcia, Philip, 2009. "Do Composite Procedures Really Improve the Accuracy of Outlook Forecasts?," 2009 Conference, April 20-21, 2009, St. Louis, Missouri 53052, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    2. Verteramo Chiu, Leslie J. & Tomek, William G., 2016. "Anticipatory Signals of Changes in Corn Demand," Working Papers 250032, Cornell University, Department of Applied Economics and Management.
    3. Xu Xiaojie, 2018. "Using Local Information to Improve Short-Run Corn Price Forecasts," Journal of Agricultural & Food Industrial Organization, De Gruyter, vol. 16(1), pages 1-15, January.
    4. Tannura, Michael A. & Irwin, Scott H. & Good, Darrel L., 2008. "Weather, Technology, and Corn and Soybean Yields in the U.S. Corn Belt," Marketing and Outlook Research Reports 37501, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics.
    5. 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.
    6. Irwin, Scott H. & Sanders, Dwight R. & Good, Darrel L., 2014. "Evaluation of Selected USDA WAOB and NASS Forecasts and Estimates in Corn and Soybeans," Marketing and Outlook Research Reports 183477, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics.
    7. Ates, Aaron M. & Lusk, Jayson L. & Brorsen, B. Wade, 2019. "Forecasting Meat Prices Using Consumer Expectations from the Food Demand Survey (FooDS)," Journal of Food Distribution Research, Food Distribution Research Society, vol. 50(01), March.
    8. Paolo Libenzio Brignoli & Alessandro Varacca & Cornelis Gardebroek & Paolo Sckokai, 2024. "Machine learning to predict grains futures prices," Agricultural Economics, International Association of Agricultural Economists, vol. 55(3), pages 479-497, May.
    9. Verteramo Chiu, Leslie J. & Tomek, William G., "undated". "Insights from Anticipatory Prices," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258115, Agricultural and Applied Economics Association.
    10. Xiaojie Xu, 2018. "Cointegration and price discovery in US corn cash and futures markets," Empirical Economics, Springer, vol. 55(4), pages 1889-1923, December.
    11. Elham Rahmani & Mohammad Khatami & Emma Stephens, 2024. "Using Probabilistic Machine Learning Methods to Improve Beef Cattle Price Modeling and Promote Beef Production Efficiency and Sustainability in Canada," Sustainability, MDPI, vol. 16(5), pages 1-19, February.
    12. Xiaojie Xu, 2017. "Short-run price forecast performance of individual and composite models for 496 corn cash markets," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(14), pages 2593-2620, October.
    13. Xiaojie Xu, 2019. "Price dynamics in corn cash and futures markets: cointegration, causality, and forecasting through a rolling window approach," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 33(2), pages 155-181, June.
    14. J. Yang & J. Beirne & G. Liu & P. Sheng, 2013. "Labour supply and pollution in China," Applied Economics Letters, Taylor & Francis Journals, vol. 20(10), pages 949-952, July.
    15. Verteramo Chiu, Leslie & Tomek, William, 2016. "Anticipatory Signals of Changes in U.S. Corn Demand," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235869, Agricultural and Applied Economics Association.
    16. Bekkerman, Anton & Brester, Gary W. & Taylor, Mykel, 2016. "Forecasting a Moving Target: The Roles of Quality and Timing for Determining Northern U.S. Wheat Basis," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 41(01), pages 1-17, January.
    17. Xiaojie Xu, 2020. "Corn Cash Price Forecasting," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(4), pages 1297-1320, August.
    18. Etienne, Xiaoli L. & Farhangdoost, Sara & Hoffman, Linwood A. & Adam, Brian D., 2023. "Forecasting the U.S. season-average farm price of corn: Derivation of an alternative futures-based forecasting model," Journal of Commodity Markets, Elsevier, vol. 30(C).

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