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Hedging Yield with Weather Derivatives: A Role for Options

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  • Manfredo, Mark R.
  • Richards, Timothy J.

Abstract

While there are few risk management alternatives available to specialty crop growers, weather derivatives provide an important advancement. As with the use of any derivatives contract, the behavior of the basis will ultimately determine the net-hedged outcome. However, when using weather derivatives to hedge yield risks for specialty crops, growers face a unique form of basis risk because weather (temperature) and yield are nonlinearly related. Using the forecast encompassing principle, this research shows that the nonlinear relationship between yield and weather creates a role for options in an optimal hedging program. The results suggest that weather derivative instruments with nonlinear payoffs, such as options, be used in combination with linear payoff instruments, such as swaps or futures, to minimize basis risk associated with the nonlinear relationship between yields and weather.

Suggested Citation

  • Manfredo, Mark R. & Richards, Timothy J., 2005. "Hedging Yield with Weather Derivatives: A Role for Options," 2005 Annual meeting, July 24-27, Providence, RI 19369, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    • Handle: RePEc:ags:aaea05:19369
    DOI: 10.22004/ag.econ.19369
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    References listed on IDEAS

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    1. 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.
    2. 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 254-259, April.
    3. Richards, Timothy J. & Manfredo, Mark R. & Sanders, Dwight R., 2004. "Pricing Weather Derivatives," Working Papers 28536, Arizona State University, Morrison School of Agribusiness and Resource Management.
    4. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    5. Fleege, Trevor A. & Richards, Timothy J. & Manfredo, Mark R. & Sanders, Dwight R., 2004. "The Performance Of Weather Derivatives In Managing Risks Of Specialty Crops," 2004 Conference, April 19-20, 2004, St. Louis, Missouri 19026, NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    6. Dwight R. Sanders, 2004. "Pricing Weather Derivatives," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(4), pages 1005-1017.
    7. Granger, C. W. J. & Newbold, Paul, 1986. "Forecasting Economic Time Series," Elsevier Monographs, Elsevier, edition 2, number 9780122951831 edited by Shell, Karl.
    8. David Harvey & Paul Newbold, 2000. "Tests for multiple forecast encompassing," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 471-482.
    9. Sanders, Dwight R. & Manfredo, Mark R., 2004. "Comparing Hedging Effectiveness: An Application of the Encompassing Principle," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 29(1), pages 1-14, April.
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    Cited by:

    1. Mußhoff, O. & Odenin, M. & Wei, X., 2007. "Zur Quantifizierung des Basisrisikos von Wetterderivaten," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 42, March.
    2. Oliver Musshoff & Martin Odening & Wei Xu, 2009. "Management of climate risks in agriculture-will weather derivatives permeate?," Applied Economics, Taylor & Francis Journals, vol. 43(9), pages 1067-1077.

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