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Basis risk and weather hedging effectiveness

Author

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  • Joshua D. Woodard
  • Philip Garcia

Abstract

Basis risk – the risk that payoffs of a hedging instrument do not correspond to the underlying exposures – is cited as a primary concern for implementing weather data, we investigate several dimensions of weather basis risk in the U.S. corn market. Results suggest that while geographic basis risk can be significant, it should not preclude the use of geographic cross-hedging, particularly with temperature as opposed to precipitation derivatives. Risk reduction is appreciable and the degree to which geographic basis risk impedes effective hedging diminishes as spatial aggregation in the risk exposure and hedging instrument increases.

Suggested Citation

  • Joshua D. Woodard & Philip Garcia, 2008. "Basis risk and weather hedging effectiveness," Agricultural Finance Review, Emerald Group Publishing, vol. 68(1), pages 99-117, May.
  • Handle: RePEc:eme:afrpps:v:68:y:2008:i:1:p:99-117
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    Citations

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    Cited by:

    1. Lu Zong & Manuela Ender, 2016. "Spatially-Aggregated Temperature Derivatives: Agricultural Risk Management in China," International Journal of Financial Studies, MDPI, Open Access Journal, vol. 4(3), pages 1-17, September.
    2. Chantarat, Sommarat & Mude, Andrew G. & Barrett, Christopher B. & Turvey, Calum G., 2017. "Welfare Impacts of Index Insurance in the Presence of a Poverty Trap," World Development, Elsevier, vol. 94(C), pages 119-138.
    3. van Kooten, G Cornelis & Guo, Changhao & Sun, Baojing, 2015. "Risking-sharing Efficiency of Hedging Strategies," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205756, Agricultural and Applied Economics Association;Western Agricultural Economics Association.
    4. M. Ritter & O. Mußhoff & M. Odening, 2014. "Minimizing Geographical Basis Risk of Weather Derivatives Using A Multi-Site Rainfall Model," Computational Economics, Springer;Society for Computational Economics, vol. 44(1), pages 67-86, June.
    5. Sheng, Di & Lambert, Dayton M. & Hellwinckel, Chad, 2016. "A Copula-based Approach to Simulate Climate Impacts on Yield: Some Preliminary Findings," 2016 Annual Meeting, February 6-9, 2016, San Antonio, Texas 230006, Southern Agricultural Economics Association.
    6. Jensen, Nathaniel D. & Barrett, Christopher B. & Mude, Andrew G., 2014. "Basis Risk and the Welfare Gains from Index Insurance: Evidence from Northern Kenya," MPRA Paper 59153, University Library of Munich, Germany.
    7. Buchholz, Matthias & Musshoff, Oliver, 2014. "The role of weather derivatives and portfolio effects in agricultural water management," Agricultural Water Management, Elsevier, vol. 146(C), pages 34-44.
    8. Xiaofeng Cao & Ostap Okhrin & Martin Odening & Matthias Ritter, 2015. "Modelling spatio-temporal variability of temperature," Computational Statistics, Springer, vol. 30(3), pages 745-766, September.
    9. Hardaker, J. Brian & Lien, Gudbrand, 2010. "Probabilities for decision analysis in agriculture and rural resource economics: The need for a paradigm change," Agricultural Systems, Elsevier, vol. 103(6), pages 345-350, July.
    10. repec:eee:insuma:v:75:y:2017:i:c:p:1-15 is not listed on IDEAS
    11. Ivana Štulec, 2017. "Effectiveness of Weather Derivatives as a Risk Management Tool in Food Retail: The Case of Croatia," International Journal of Financial Studies, MDPI, Open Access Journal, vol. 5(1), pages 1-15, January.

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