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Methods for Selecting the Optimal Dynamic Hedge When Production is Stochastic

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  • Karp, Larry

Abstract

A dynamic hedging problem with stochastic production is solved. The optimal feedback rules recognize that future hedges will be chosen optimally based on the most current information. The resulting distribution of revenue is analyzed numerically. This analysis enables the hedger to select his appropriate level of risk aversion.

Suggested Citation

  • Karp, Larry, 1986. "Methods for Selecting the Optimal Dynamic Hedge When Production is Stochastic," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt5jp9q454, Department of Agricultural & Resource Economics, UC Berkeley.
    • Handle: RePEc:cdl:agrebk:qt5jp9q454
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    References listed on IDEAS

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    1. Peter Berck, 1981. "Portfolio Theory and the Demand for Futures: The Case of California Cotton," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 63(3), pages 466-474.
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    6. Gershon Feder & Richard E. Just & Andrew Schmitz, 1980. "Futures Markets and the Theory of the Firm under Price Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 94(2), pages 317-328.
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    Citations

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    Cited by:

    1. Sergio H. Lence & Dermot J. Hayes & Yong Sakong, 1994. "Multiperiod Production with Forward and Option Markets," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 76(2), pages 286-295.
    2. Nyassoke Titi Gaston Clément & Jules Sadefo-Kamdem & Louis Aimé Fono, 2019. "Dynamic Optimal Hedge Ratio Design when Price and Production are stochastic with Jump," Working Papers hal-02417401, HAL.
    3. Tronstad, Russell, 1989. "Optimal Cash Grain Sale, Storage, and Hedging Decisions for Grain Producers: A Stochastic Dynamic Programming Analysis," 1989 Annual Meeting, July 30-August 2, Baton Rouge, Louisiana 270518, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    4. Harvey Lapan & Giancarlo Moschini & Steven D. Hanson, 1991. "Production, Hedging, and Speculative Decisions with Options and Futures Markets," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 73(1), pages 66-74.
    5. Kim, Tae-Kyun, 1989. "The factor bias of technical change and technology adoption under uncertainty," ISU General Staff Papers 1989010108000010138, Iowa State University, Department of Economics.
    6. Anderson, Jock R., 2003. "Risk in rural development: challenges for managers and policy makers," Agricultural Systems, Elsevier, vol. 75(2-3), pages 161-197.
    7. Blank, Steven C., 1989. "Research On Futures Markets: Issues, Approaches, And Empirical Findings," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 14(1), pages 1-14, July.
    8. Vadhindran K. Rao, 2011. "Multiperiod Hedging using Futures: Mean Reversion and the Optimal Hedging Path," JRFM, MDPI, vol. 4(1), pages 1-29, December.
    9. Frank, Deon, 1992. "Agricultural Commodity Futures Markets In South Africa," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 31(4), December.
    10. Monson, Steven J., 1991. "Accounting for yield risk in preharvest commodity pricing decisions," ISU General Staff Papers 1991010108000018169, Iowa State University, Department of Economics.
    11. Tronstad, Russell, 1991. "The Effects Of Firm Size And Production Cost Levels On Dynamically Optimal After-Tax Cotton Storage And Hedging Decisions," Southern Journal of Agricultural Economics, Southern Agricultural Economics Association, vol. 23(1), pages 1-15, July.
    12. Nyassoke Titi Gaston Clément & Sadefo Kamdem Jules & Fono Louis Aimé, 2022. "Dynamic optimal hedge ratio design when price and production are stochastic with jump," Annals of Finance, Springer, vol. 18(3), pages 419-428, September.
    13. Zhao, Jieyuan & Goodwin, Barry K., 2012. "Dynamic Cross-Hedge Ratios: An Application of Copula Models," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124610, Agricultural and Applied Economics Association.
    14. Jing-Yi Lai, 2012. "An empirical study of the impact of skewness and kurtosis on hedging decisions," Quantitative Finance, Taylor & Francis Journals, vol. 12(12), pages 1827-1837, December.

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