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The Valuation of Weather Derivatives Using One Sided Crank–Nicolson Schemes

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  • Peng Li

    (North China University of Water Resources and Electric Power)

Abstract

This paper prices weather derivatives of two typical processes: the Ornstein–Uhlenbeck process and the Ornstein–Uhlenbeck process with jump diffusions. Efficient one sided Crank–Nicolson schemes are developed to solve the convection dominated partial differential and integral-differential equation corresponding to the two processes, respectively. For second order convergence, the one sided Crank–Nicolson schemes may utilize piecewise cubic interpolations to approximate the jump conditions in degree days direction. The unconditional stability is then obtained through the local von Neumann analysis. As extensive numerical experiments shown, the schemes are highly efficient and accurate, and can serve as competitive and practical pricing instruments in weather derivative markets.

Suggested Citation

  • 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.
    • Handle: RePEc:kap:compec:v:58:y:2021:i:3:d:10.1007_s10614-020-10052-y
    DOI: 10.1007/s10614-020-10052-y
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    References listed on IDEAS

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    1. 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.
    2. Groll, Andreas & López-Cabrera, Brenda & Meyer-Brandis, Thilo, 2016. "A consistent two-factor model for pricing temperature derivatives," Energy Economics, Elsevier, vol. 55(C), pages 112-126.
    3. Sean D. Campbell & Francis X. Diebold, 2005. "Weather Forecasting for Weather Derivatives," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 6-16, March.
    4. Guiyuan Ma & Song-Ping Zhu, 2019. "Optimal investment and consumption under a continuous-time cointegration model with exponential utility," Quantitative Finance, Taylor & Francis Journals, vol. 19(7), pages 1135-1149, July.
    5. Hélène Hamisultane, 2008. "Which Method for Pricing Weather Derivatives ?," Working Papers halshs-00355856, HAL.
    6. Gonglin Yuan & Xiangrong Li, 2019. "A Numerical Algorithm for the Coupled PDEs Control Problem," Computational Economics, Springer;Society for Computational Economics, vol. 53(2), pages 697-707, February.
    7. Härdle, Wolfgang Karl & López-Cabrera, Brenda & Ritter, Matthias, 2012. "Forecast based pricing of weather derivatives," SFB 649 Discussion Papers 2012-027, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    8. Peter Alaton & Boualem Djehiche & David Stillberger, 2002. "On modelling and pricing weather derivatives," Applied Mathematical Finance, Taylor & Francis Journals, vol. 9(1), pages 1-20.
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