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A Stochastic Harmonic Oscillator Temperature Model for the Valuation of Weather Derivatives

Author

Listed:
  • Alessio Giorgini

    (Chief Risk Officer Department, FinecoBank, 20131 Milan, Italy)

  • Rogemar S. Mamon

    (Department of Statistical and Actuarial Sciences, University of Western Ontario, London, ON N6A 5B7, Canada)

  • Marianito R. Rodrigo

    (School of Mathematics and Applied Statistics, University of Wollongong, Wollongong, NSW 2522, Australia)

Abstract

Stochastic processes are employed in this paper to capture the evolution of daily mean temperatures, with the goal of pricing temperature-based weather options. A stochastic harmonic oscillator model is proposed for the temperature dynamics and results of numerical simulations and parameter estimation are presented. The temperature model is used to price a one-month call option and a sensitivity analysis is undertaken to examine how call option prices are affected when the model parameters are varied.

Suggested Citation

  • Alessio Giorgini & Rogemar S. Mamon & Marianito R. Rodrigo, 2021. "A Stochastic Harmonic Oscillator Temperature Model for the Valuation of Weather Derivatives," Mathematics, MDPI, vol. 9(22), pages 1-15, November.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:22:p:2890-:d:678519
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    References listed on IDEAS

    as
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    6. Elias, R.S. & Wahab, M.I.M. & Fang, L., 2014. "A comparison of regime-switching temperature modeling approaches for applications in weather derivatives," European Journal of Operational Research, Elsevier, vol. 232(3), pages 549-560.
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    8. Tak Kuen Siu & Christina Erlwein & Rogemar Mamon, 2008. "The Pricing of Credit Default Swaps under a Markov-Modulated Merton’s Structural Model," North American Actuarial Journal, Taylor & Francis Journals, vol. 12(1), pages 18-46.
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