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Pricing rainfall futures at the CME

Author

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  • López Cabrera, Brenda
  • Odening, Martin
  • Ritter, Matthias

Abstract

Many business people such as farmers and financial investors are affected by indirect losses caused by scarce or abundant rainfall. Because of the high potential of insuring rainfall risk, the Chicago Mercantile Exchange (CME) began trading rainfall derivatives in 2011. Compared to temperature derivatives, however, pricing rainfall derivatives is more difficult. In this article, we propose to model rainfall indices via a flexible type of distribution, namely the normal-inverse Gaussian distribution, which captures asymmetries and heavy-tail behaviour. The prices of rainfall futures are computed by employing the Esscher transform, a well-known tool in actuarial science. This approach is flexible enough to price any rainfall contract and to adjust theoretical prices to market prices by using the calibrated market price of risk. The empirical analysis is conducted with US precipitation data and CME futures data providing first results on the market price of risk for rainfall derivatives.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:jbfina:v:37:y:2013:i:11:p:4286-4298
    DOI: 10.1016/j.jbankfin.2013.07.042
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. 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).
    2. Edimilson Costa Lucas & Wesley Mendes Da Silva & Gustavo Silva Araujo, 2017. "Does Extreme Rainfall Lead to Heavy Economic Losses in the Food Industry?," Working Papers Series 462, Central Bank of Brazil, Research Department.
    3. 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.
    4. Awdesch Melzer & Wolfgang K. Härdle & Brenda López Cabrera, 2017. "Pricing Green Financial Products," SFB 649 Discussion Papers SFB649DP2017-020, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    5. Truong, Chi & Trück, Stefan, 2016. "It’s not now or never: Implications of investment timing and risk aversion on climate adaptation to extreme events," European Journal of Operational Research, Elsevier, vol. 253(3), pages 856-868.
    6. CMaria Osipenko & Wolfgang Karl Härdle, 2017. "Dynamic Valuation of Weather Derivatives under Default Risk," SFB 649 Discussion Papers SFB649DP2017-005, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    7. Karl Härdle, Wolfgang & López-Cabrera, Brenda & Teng, Huei-Wen, 2015. "State price densities implied from weather derivatives," Insurance: Mathematics and Economics, Elsevier, vol. 64(C), pages 106-125.
    8. repec:gam:jijfss:v:5:y:2017:i:4:p:23-:d:115840 is not listed on IDEAS
    9. Ragnhild Noven & Almut Veraart & Axel Gandy, 2015. "A Lévy-driven rainfall model with applications to futures pricing," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 99(4), pages 403-432, October.

    More about this item

    Keywords

    Weather derivatives; Precipitation; Esscher transform; Market price of risk;

    JEL classification:

    • G19 - Financial Economics - - General Financial Markets - - - Other
    • G29 - Financial Economics - - Financial Institutions and Services - - - Other
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • Q59 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Other

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