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Optimal Length of Moving Average to Forecast Futures Basis

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  • Hatchett, Robert B.
  • Brorsen, B. Wade
  • Anderson, Kim B.

Abstract

Futures prices when combined with a basis forecast provide a reliable way to forecast cash prices. The most popular method of forecasting basis is historical moving averages. Given the recent failure of longer moving averages proposed by previous studies, this research reassesses past recommendations about the best length of moving average to use in forecasting basis. This research compares practical preharvest and storage period basis forecasts for hard wheat, soft wheat, corn and soybeans to identify the optimal amount of historical information to include in moving average forecasts. Only with preharvest hard wheat forecasts are the best moving averages longer than 3 years. The differences in forecast accuracy among the different moving averages are small and in most cases the differences are not statistically significant. The recommendation is to use longer moving averages during time periods (or at locations) when there have been no structural changes and use last year’s basis after it appears that a structural change has occurred.

Suggested Citation

  • Hatchett, Robert B. & Brorsen, B. Wade & Anderson, Kim B., 2009. "Optimal Length of Moving Average to Forecast Futures Basis," 2009 Conference, April 20-21, 2009, St. Louis, Missouri 53048, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    • Handle: RePEc:ags:nccc09:53048
    DOI: 10.22004/ag.econ.53048
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    Cited by:

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    2. Lee, Yoonsuk & Brorsen, B. Wade, 2012. "Impacts of Permanent and Transitory Shocks on Optimal Length of Moving Average to Predict Wheat Basis," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 125001, Agricultural and Applied Economics Association.
    3. Fernandez-Perez, Adrian & Frijns, Bart & Gafiatullina, Ilnara & Tourani-Rad, Alireza, 2022. "Profit margin hedging in the New Zealand dairy farming industry," Journal of Commodity Markets, Elsevier, vol. 26(C).
    4. Coffey, Brian K. & Tonsor, Glynn T. & Schroeder, Ted C., 2018. "Impacts of Changes in Market Fundamentals and Price Momentum on Hedging Live Cattle," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 43(1), January.
    5. Hayhurst, Emma & Brorsen, B. Wade, 2023. "Resilience of Grain Storage Markets to Upheaval in Futures Markets," Research on World Agricultural Economy, Nan Yang Academy of Sciences Pte Ltd (NASS), vol. 4(2), April.
    6. Marie Coiffard & Laëtitia Guilhot, 2012. "Migrations internationales : la mobilité des Hommes, facteur d'intégration régionale en Asie Orientale ?," Post-Print halshs-00755102, HAL.
    7. Rangga Handika & Sania Ashraf, 2018. "Financialized Commodities and Stock Indices Volatilities," European Research Studies Journal, European Research Studies Journal, vol. 0(1), pages 153-164.
    8. 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(1), pages 1-17, January.
    9. Onel, Gulcan & Karali, Berna, 2014. "Relative Performance of Semi-Parametric Nonlinear Models in Forecasting Basis," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 169795, Agricultural and Applied Economics Association.

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