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The Long-Term Structure of Commodity Futures

Author

Listed:
  • Jin, Na
  • Lence, Sergio H.
  • Hart, Chad E.
  • Hayes, Dermot J.

Abstract

Futures markets on agricultural commodities typically trade with maximum maturity dates of less than four years. If these markets did trade with maturities eight or ten years distant, futures prices would have value as price forecasts and as a way to structure long-term swaps and insurance contracts. Agricultural commodity markets generally exhibit mean reversion in spot prices and convenience yields. Spot markets also exhibit seasonality. This study develops and implements a procedure to generate long-term futures curves from existing futures prices. Data on lean hogs and soybeans are used to show that the method provides plausible results.

Suggested Citation

  • Jin, Na & Lence, Sergio H. & Hart, Chad E. & Hayes, Dermot J., 2012. "The Long-Term Structure of Commodity Futures," Staff General Research Papers Archive 34992, Iowa State University, Department of Economics.
    • Handle: RePEc:isu:genres:34992
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    References listed on IDEAS

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    Cited by:

    1. Zhu, Xiaohong, 2016. "New models to estimate costs of US farm programs," ISU General Staff Papers 201601010800006209, Iowa State University, Department of Economics.
    2. Li, Lisha, 2015. "Three essays on crop yield, crop insurance and climate change," ISU General Staff Papers 201501010800005371, Iowa State University, Department of Economics.
    3. Delbridge, Timothy A. & King, Robert P., 2016. "Transitioning to Organic Crop Production: A Dynamic Programming Approach," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 41(3), pages 1-18, September.
    4. Chad E. Hart & Sergio H. Lence & Dermot J. Hayes & Na Jin, 2016. "Price Mean Reversion, Seasonality, and Options Markets," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 98(3), pages 707-725.
    5. Zhu, Xiaohong, 2016. "New models to estimate costs of US farm programs," ISU General Staff Papers 3547, Iowa State University, Department of Economics.
    6. Shao, Chengwu & Bhar, Ramaprasad & Colwell, David B., 2015. "A multi-factor model with time-varying and seasonal risk premiums for the natural gas market," Energy Economics, Elsevier, vol. 50(C), pages 207-214.
    7. Zhou, Wei, 2015. "Three essays on modeling biofuel feedstock supply," ISU General Staff Papers 201501010800005728, Iowa State University, Department of Economics.
    8. Zhou, Wei & Babcock, Bruce A., 2014. "Endogenous Price in a Dynamic Model for Agricultural Supply Analysis," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170584, Agricultural and Applied Economics Association.
    9. Yang, Linghubo & Zhang, Dongxiang, 2013. "Can futures price be a powerful predictor? Frequency domain analysis on Chinese commodity market," Economic Modelling, Elsevier, vol. 35(C), pages 264-271.

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