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Bayesian Cross Hedging: An Example From the Soybean Market

Author

Listed:
  • F. Douglas Foster

    (Australian Graduate School of Management, UNSW, Sydney, NSW 2052. Email: fd.foster@unsw.edu.au.)

  • Charles H. Whiteman

    (Department of Economics, The University of Iowa, Iowa City, IA, 52242 USA. Email: whiteman@uiowa.edu.)

Abstract

Following Lence and Hayes (1994a), we study the problem faced by an Iowa farmer who wishes to hedge a soybean harvest using Chicago futures contracts. A time-series model for spot and futures prices is postulated, and numerical Bayesian procedures are used to calculate predictive densities and optimal hedges. The numerical procedures extend earlier analytical work, and easily accommodate alternative views about specification (levels vs. logarithms, trends vs. no trends, etc.), uncertainty about parameterisations (estimation risk), as well as other non-sample information (the likely size of the difference between spot prices in Iowa and Chicago, the tendency of the basis to be large in the spring, the shrinking of the basis as expiration of the future looms, etc.)

Suggested Citation

  • F. Douglas Foster & Charles H. Whiteman, 2002. "Bayesian Cross Hedging: An Example From the Soybean Market," Australian Journal of Management, Australian School of Business, vol. 27(2), pages 95-122, December.
    • Handle: RePEc:sae:ausman:v:27:y:2002:i:2:p:95-122
    DOI: 10.1177/031289620202700201
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    References listed on IDEAS

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    1. Alexander, Gordon J & Resnick, Bruce G, 1985. "More on Estimation Risk and Simple Rules for Optimal Portfolio Selection," Journal of Finance, American Finance Association, vol. 40(1), pages 125-133, March.
    2. Clarkson, Peter M & Thompson, Rex, 1990. "Empirical Estimates of Beta When Investors Face Estimation Risk," Journal of Finance, American Finance Association, vol. 45(2), pages 431-453, June.
    3. Chen, Son-Nan & Brown, Stephen J, 1983. "Estimation Risk and Simple Rules for Optimal Portfolio Selection," Journal of Finance, American Finance Association, vol. 38(4), pages 1087-1093, September.
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    Cited by:

    1. Yang (Greg) Hou & Mark Holmes, 2020. "Do higher order moments of return distribution provide better decisions in minimum-variance hedging? Evidence from US stock index futures," Australian Journal of Management, Australian School of Business, vol. 45(2), pages 240-265, May.
    2. David J. Pannell & Getu Hailu & Alfons Weersink & Amanda Burt, 2008. "More reasons why farmers have so little interest in futures markets," Agricultural Economics, International Association of Agricultural Economists, vol. 39(1), pages 41-50, July.
    3. Stutzer, Michael, 2013. "Optimal hedging via large deviation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(15), pages 3177-3182.
    4. Chris Brooks & Ryan J. Davies & Sang Soo Kim, 2005. "Cross Hedging with Single Stock Futures," ICMA Centre Discussion Papers in Finance icma-dp2004-15, Henley Business School, University of Reading.
    5. Wei Shi & Scott H. Irwin, 2005. "Optimal Hedging with a Subjective View: An Empirical Bayesian Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(4), pages 918-930.
    6. Rozaimah Zainudin & Roselee Shah Shaharudin, 2011. "Multi Mean Garch Approach to Evaluating Hedging Performance in the Crude Palm Oil Futures Market," Asian Academy of Management Journal of Accounting and Finance (AAMJAF), Penerbit Universiti Sains Malaysia, vol. 7(1), pages 111-130.

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