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Minimizing geographical basis risk of weather derivatives using a multi-site rainfall model

Author

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  • Ritter, Matthias
  • Musshoff, Oliver
  • Odening, Martin

Abstract

Weather risk is one of the main causes for income fluctuation in agriculture. Since 1997, the economic consequences of weather risk can be insured with weather derivatives, which are offered for many different weather events, such as temperature, rainfall, snow or hurricanes. It is well known that the hedging effectiveness of weather derivatives is interfered by the existence of geographical basis risk, i.e., the deviation of weather conditions at different locations. In this paper, we explore how geographical basis risk of rainfall based derivatives can be reduced by regional diversification. Minimizing geographical basis risk requires knowledge of the joint distribution of rainfall at different locations. For that purpose, we estimate a daily multi-site rainfall model from which optimal portfolio weights are derived. We find that this method allows to reduce geographical basis risk more efficiently than simpler approaches as, for example, inverse distance weighting.

Suggested Citation

  • Ritter, Matthias & Musshoff, Oliver & Odening, Martin, 2012. "Minimizing geographical basis risk of weather derivatives using a multi-site rainfall model," 123rd Seminar, February 23-24, 2012, Dublin, Ireland 122527, European Association of Agricultural Economists.
    • Handle: RePEc:ags:eaa123:122527
    DOI: 10.22004/ag.econ.122527
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    References listed on IDEAS

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    1. Wei Xu & Guenther Filler & Martin Odening & Ostap Okhrin, 2010. "On the systemic nature of weather risk," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 70(2), pages 267-284, August.
    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.
    3. López Cabrera, Brenda & Odening, Martin & Ritter, Matthias, 2013. "Pricing rainfall futures at the CME," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4286-4298.
    4. Wei Xu & Guenther Filler & Martin Odening & Ostap Okhrin, 2010. "On the systemic nature of weather risk," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 70(2), pages 267-284, August.
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    9. Chen, Gang & Roberts, Matthew C., 2004. "Weather Derivatives In The Presence Of Index And Geographical Basis Risk: Hedging Dairy Profit Risk," 2004 Conference, April 19-20, 2004, St. Louis, Missouri 19030, NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    10. Yufei Jin & Roderick Rejesus & Bertis Little, 2005. "Binary choice models for rare events data: a crop insurance fraud application," Applied Economics, Taylor & Francis Journals, vol. 37(7), pages 841-848.
    11. Härdle, Wolfgang Karl & Osipenko, Maria, 2011. "Pricing Chinese rain: A multisite mulit-period equilibrium pricing model for rainfall derivatives," SFB 649 Discussion Papers 2011-055, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    12. Denis Nadolnyak & Valentina Hartarska, 2012. "Agricultural disaster payments in the southeastern US: do weather and climate variability matter?," Applied Economics, Taylor & Francis Journals, vol. 44(33), pages 4331-4342, November.
    13. J. P. Hughes & P Guttorp & S. P. Charles, 1999. "A non‐homogeneous hidden Markov model for precipitation occurrence," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 48(1), pages 15-30.
    14. P. M. Bentler & Chih-Ping Chou, 1987. "Practical Issues in Structural Modeling," Sociological Methods & Research, , vol. 16(1), pages 78-117, August.
    15. Martin Odening & Oliver Musshoff & Wei Xu, 2007. "Analysis of rainfall derivatives using daily precipitation models: opportunities and pitfalls," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 67(1), pages 135-156, May.
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    Cited by:

    1. López Cabrera, Brenda & Odening, Martin & Ritter, Matthias, 2013. "Pricing rainfall derivatives at the CME," SFB 649 Discussion Papers 2013-005, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    2. Goodrich, Brittney K. & Davidson, Kelly A., . "Enrollment in Pasture, Rangeland, and Forage Rainfall Index Insurance: Awareness Matters," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 49(2).
    3. 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.
    4. repec:hum:wpaper:sfb649dp2013-005 is not listed on IDEAS
    5. Ceballos, Francisco, 2016. "Estimating spatial basis risk in rainfall index insurance: Methodology and application to excess rainfall insurance in Uruguay," IFPRI discussion papers 1595, International Food Policy Research Institute (IFPRI).
    6. Doms, Juliane, 2017. "Put, call or strangle? About the challenges in designing weather index insurances to hedge performance risk in agriculture," 57th Annual Conference, Weihenstephan, Germany, September 13-15, 2017 261990, German Association of Agricultural Economists (GEWISOLA).
    7. Hang Gao & Shuohua Yang & Xinli Liu, 2024. "Managing Basis Risks in Weather Parametric Insurance: A Quantitative Study of Diversification and Key Influencing Factors," Papers 2409.16599, arXiv.org.
    8. López Cabrera, Brenda & Odening, Martin & Ritter, Matthias, 2013. "Pricing rainfall futures at the CME," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4286-4298.
    9. Matthieu Stigler & David Lobell, 2024. "Optimal index insurance and basis risk decomposition: an application to Kenya," American Journal of Agricultural Economics, John Wiley & Sons, vol. 106(1), pages 306-329, January.
    10. repec:hum:wpaper:sfb649dp2014-020 is not listed on IDEAS
    11. Schmidt, Lorenz & Odening, Martin & Schlanstein, Johann & Ritter, Matthias, 2022. "Exploring the weather-yield nexus with artificial neural networks," Agricultural Systems, Elsevier, vol. 196(C).

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    More about this item

    Keywords

    Risk and Uncertainty;

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • Q14 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Finance
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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