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Forecast Encompassing as the Necessary Condition to Reject Futures Market Efficiency: Fluid Milk Futures

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  • Dwight R. Sanders
  • Mark R. Manfredo

Abstract

The traditional necessary condition for futures market inefficiency is the existence of alternative forecasting methods that produce mean squared forecast errors smaller than the futures market. Here, a more exacting requirement for futures market efficiency is proposed—forecast encompassing. Using the procedure of Harvey and Newbold, multiple forecast encompassing is tested using Chicago Mercantile Exchange fluid milk futures. Time series models and USDA experts provide competing forecasts. Results suggest milk futures do not encompass the information contained in the USDA forecasts at a two-quarter horizon. While the competing forecasts generate positive revenues, it is unlikely that returns exceed transaction costs in this relatively new market. Copyright 2005, Oxford University Press.

Suggested Citation

  • Dwight R. Sanders & Mark R. Manfredo, 2005. "Forecast Encompassing as the Necessary Condition to Reject Futures Market Efficiency: Fluid Milk Futures," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(3), pages 610-620.
    • Handle: RePEc:oup:ajagec:v:87:y:2005:i:3:p:610-620
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    File URL: http://hdl.handle.net/10.1111/j.1467-8276.2005.00751.x
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    Cited by:

    1. Sanders, Dwight R. & Garcia, Philip & Manfredo, Mark R., 2008. "Information Content in Deferred Futures Prices: Live Cattle and Hogs," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 33(1), pages 1-12, April.
    2. Scott, Ayesha & Schoen, Tilman & Fernandez-Perez, Adrian, 2020. "The Predictive Power of NZX Dairy Futures," 2020 Conference (64th), February 12-14, 2020, Perth, Western Australia 305230, Australian Agricultural and Resource Economics Society.
    3. 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.
    4. 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.
    5. 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(1), March.
    6. 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.
    7. No, Sung Chul & Salassi, Michael E., 2008. "A Sequential Rationality and Efficiency Test of U.S. Department of Agriculture Program Crop Price Estimates: Rice, Wheat, and Soybeans," 2008 Annual Meeting, February 2-6, 2008, Dallas, Texas 6814, Southern Agricultural Economics Association.
    8. 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).
    9. Glynn Tonsor & Ted Schroeder, 2011. "Multivariate forecasting of a commodity portfolio: application to cattle feeding margins and risk," Applied Economics, Taylor & Francis Journals, vol. 43(11), pages 1329-1339.

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