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Minimizing Geographical Basis Risk of Weather Derivatives Using A Multi-Site Rainfall Model

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  • M. Ritter
  • O. Mußhoff
  • M. Odening

Abstract

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. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • 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.
    • Handle: RePEc:kap:compec:v:44:y:2014:i:1:p:67-86
    DOI: 10.1007/s10614-013-9410-y
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    1. 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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    9. 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.
    10. Vedenov, Dmitry V. & Barnett, Barry J., 2004. "Efficiency of Weather Derivatives as Primary Crop Insurance Instruments," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 29(3), pages 1-17, December.
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    12. 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.
    13. 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.
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    15. P. M. Bentler & Chih-Ping Chou, 1987. "Practical Issues in Structural Modeling," Sociological Methods & Research, , vol. 16(1), pages 78-117, August.
    16. 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.
    17. Ernst Berg & Bernhard Schmitz, 2008. "Weather‐based instruments in the context of whole‐farm risk management," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 68(1), pages 119-133, May.
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    Citations

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    Cited by:

    1. 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.
    2. 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).
    3. 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.
    4. 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).
    5. repec:hum:wpaper:sfb649dp2013-005 is not listed on IDEAS
    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. 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.
    8. 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.
    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 management; Weather risk; Regional diversification; Portfolio weights;
    All these keywords.

    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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