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Minimum Variance Hedging And The Encompassing Principle: Assessing The Effectiveness Of Futures Hedges

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  • Manfredo, Mark R.
  • Sanders, Dwight R.
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    Abstract

    An empirical methodology is developed for statistically testing the hedging effectiveness among competing futures contracts. The presented methodology is based on the encompassing principle, widely used in the forecasting literature, and applied here to minimum variance hedging regressions. Intuitively, the test is based on an alternative futures contract's ability to reduce residual basis risk by offering either diversification or a smaller absolute level of basis risk than a preferred futures contract. The methodology is also easily extended to cases involving multiple hedging instruments and general hedge ratio models. The methodology is demonstrated by evaluating the hedging effectiveness of Chicago Board of Trade's (CBOT) corn futures versus the Minneapolis Grain Exchange's National Corn Index (NCI) futures. The results indicate that the NCI futures encompass the CBOT futures for hedging country-level corn price risk in North Central Iowa; but, the NCI and CBOT futures are complementary in hedging terminal-level corn price risk at the U.S. Gulf.

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    Bibliographic Info

    Paper provided by American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association) in its series 2003 Annual meeting, July 27-30, Montreal, Canada with number 22247.

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    Date of creation: 2003
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    Handle: RePEc:ags:aaea03:22247

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    Keywords: encompassing; hedging effectiveness; corn futures; Agribusiness;

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    1. Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
    2. Ederington, Louis H, 1979. "The Hedging Performance of the New Futures Markets," Journal of Finance, American Finance Association, vol. 34(1), pages 157-70, March.
    3. Russell Davidson & James G. MacKinnon, 1980. "Several Tests for Model Specification in the Presence of Alternative Hypotheses," Working Papers 378, Queen's University, Department of Economics.
    4. Anderson, Ronald W & Danthine, Jean-Pierre, 1981. "Cross Hedging," Journal of Political Economy, University of Chicago Press, vol. 89(6), pages 1182-96, December.
    5. David Harvey & Paul Newbold, 2000. "Tests for multiple forecast encompassing," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 471-482.
    6. West, Kenneth D, 2001. "Tests for Forecast Encompassing When Forecasts Depend on Estimated Regression Parameters," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(1), pages 29-33, January.
    7. Mizon, Grayham E & Richard, Jean-Francois, 1986. "The Encompassing Principle and Its Application to Testing Non-nested Hypotheses," Econometrica, Econometric Society, vol. 54(3), pages 657-78, May.
    8. Castelino, Mark G & Francis, Jack C & Wolf, Avner, 1991. "Cross-Hedging: Basis Risk and Choice of the Optimal Hedging Vehicle," The Financial Review, Eastern Finance Association, vol. 26(2), pages 179-210, May.
    9. Roger A. Dahlgran, 2000. "Cross-hedging the cottonseed crush: A case study," Agribusiness, John Wiley & Sons, Ltd., vol. 16(2), pages 141-158.
    10. Joost M. E. Pennings & Matthew T. G. Meulenberg, 1997. "The hedging performance in new agricultural futures markets: A note," Agribusiness, John Wiley & Sons, Ltd., vol. 13(3), pages 295-300.
    11. Ditsch, Mark W. & Leuthold, Raymond M., 1996. "Evaluating The Hedging Potential Of The Lean Hog Futures Contract," ACE OFOR Reports 14769, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics.
    12. Elam, Emmett W., 1988. "Estimated Hedging Risk With Cash Settlement Feeder Cattle Futures," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 13(01), July.
    13. Harvey, David I & Leybourne, Stephen J & Newbold, Paul, 1998. "Tests for Forecast Encompassing," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 254-59, April.
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