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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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    Cited by:

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    2. Rui Zhou & Johnny Siu-Hang Li & Jeffrey Pai, 2019. "Pricing temperature derivatives with a filtered historical simulation approach," The European Journal of Finance, Taylor & Francis Journals, vol. 25(15), pages 1462-1484, October.
    3. Härdle, Wolfgang Karl & Osipenko, Maria, 2017. "Dynamic valuation of weather derivatives under default risk," SFB 649 Discussion Papers 2017-005, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    4. 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.
    5. 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.
    6. 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.
    7. repec:hum:wpaper:sfb649dp2017-020 is not listed on IDEAS
    8. Bertrand, Jean-Louis & Parnaudeau, Miia, 2019. "Understanding the economic effects of abnormal weather to mitigate the risk of business failures," Journal of Business Research, Elsevier, vol. 98(C), pages 391-402.
    9. 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.
    10. Simona Franzoni & Cristian Pelizzari, 2021. "Rainfall option impact on profits of the hospitality industry through scenario correlation and copulas," Annals of Operations Research, Springer, vol. 299(1), pages 939-962, April.
    11. Tong, Zhigang & Liu, Allen, 2021. "A censored Ornstein–Uhlenbeck process for rainfall modeling and derivatives pricing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
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    13. Wolfgang Karl Härdle & Brenda López Cabrera & Awdesch Melzer, 2021. "Pricing wind power futures," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(4), pages 1083-1102, August.
    14. Wolfgang Karl Härdle & Maria Osipenko, 2017. "A Dynamic Programming Approach for Pricing Weather Derivatives under Issuer Default Risk," IJFS, MDPI, vol. 5(4), pages 1-18, October.
    15. Melzer, Awdesch & Härdle, Wolfgang Karl & López Cabrera, Brenda, 2017. "Pricing Green Financial Products," SFB 649 Discussion Papers 2017-020, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    16. 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.
    17. Peng Li, 2021. "The Valuation of Weather Derivatives Using One Sided Crank–Nicolson Schemes," Computational Economics, Springer;Society for Computational Economics, vol. 58(3), pages 825-847, October.

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    More about this item

    Keywords

    Weather derivatives; Precipitation; Esscher transform; Market price of risk;
    All these keywords.

    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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