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Generalized Hedge Ratio Estimation With An Unknown Model

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  • Dorfman, Jeffrey H.
  • Sanders, Dwight R.

Abstract

Myers and Thompson (1989) pioneered the concept of a generalized approach to estimating hedge ratios, pointing out that the model specification could have a large impact on the hedge ratio estimated. While a huge empirical literature exists on estimating hedge ratios, the literature is lacking a formal treatment of model specification uncertainty. This research accomplishes that task by taking a Bayesian approach to hedge ratio estimation, where specification uncertainty is explicitly modeled. Specifically, we present a Bayesian approach to hedge ratio estimation that integrates over model specification uncertainty, yielding an optimal hedge ratio estimator that is robust to possible model specification because it is an average across a set of hedge ratios conditional on di erent models. Model specifications vary by exogenous variables (such as exports, stocks, and interest rates) and lag lengths included. The methodology is applied to data on corn and soybeans and results show the potential benefits and insights gained from such an approach.

Suggested Citation

  • Dorfman, Jeffrey H. & Sanders, Dwight R., 2004. "Generalized Hedge Ratio Estimation With An Unknown Model," 2004 Conference, April 19-20, 2004, St. Louis, Missouri 19024, NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
  • Handle: RePEc:ags:ncrfou:19024
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    File URL: http://ageconsearch.umn.edu/record/19024/files/cp04do01.pdf
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    References listed on IDEAS

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    1. Sergio H. Lence & Dermot J. Hayes, 1993. "Empirical Minimum Variance Hedge, The," Center for Agricultural and Rural Development (CARD) Publications 93-wp109, Center for Agricultural and Rural Development (CARD) at Iowa State University.
    2. Myers, Robert J. & Thompson, Stanley R., 1988. "Generalized Optimal Hedge Ratio Estimation," Staff Paper Series 200967, Michigan State University, Department of Agricultural, Food, and Resource Economics.
    3. Dorfman, J.H. & Lastrapes, W.D., 1993. "The Dynamic Responses of Crop and Livestock Prices to Money Supply Shocks: A Bayesian Analysis using Long Run Restrictions," Papers 429, Georgia - College of Business Administration, Department of Economics.
    4. B. Wade Brorsen & Darren W. Buck & Stephen R. Koontz, 1998. "Hedging hard red winter wheat: Kansas City versus Chicago," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 18(4), pages 449-466, June.
    5. Jeffrey H. Dorfman & William D. Lastrapes, 1996. "The Dynamic Responses of Crop and Livestock Prices to Money-Supply Shocks: A Bayesian Analysis Using Long-Run Identifying Restrictions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 78(3), pages 530-541.
    6. Anderson, Ronald W & Danthine, Jean-Pierre, 1981. "Cross Hedging," Journal of Political Economy, University of Chicago Press, vol. 89(6), pages 1182-1196, December.
    7. Sergio H. Lence & Dermot J. Hayes, 1994. "The Empirical Minimum-Variance Hedge," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 76(1), pages 94-104.
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    Cited by:

    1. Power, Gabriel J. & Vedenov, Dmitry V., 2008. "The Shape of the Optimal Hedge Ratio: Modeling Joint Spot-Futures Prices using an Empirical Copula-GARCH Model," 2008 Conference, April 21-22, 2008, St. Louis, Missouri 37609, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.

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    Keywords

    Marketing;

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