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A stochastic volatility model for the valuation of temperature derivatives

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  • Aur'elien Alfonsi
  • Nerea Vadillo

Abstract

This paper develops a new stochastic volatility model for the temperature that is a natural extension of the Ornstein-Uhlenbeck model proposed by Benth and Benth (2007). This model allows to be more conservative regarding extreme events while keeping tractability. We give a method based on Conditional Least Squares to estimate the parameters on daily data and estimate our model on eight major European cities. We then show how to calculate efficiently the average payoff of weather derivatives both by Monte-Carlo and Fourier transform techniques. This new model allows to better assess the risk related to temperature volatility.

Suggested Citation

  • Aur'elien Alfonsi & Nerea Vadillo, 2022. "A stochastic volatility model for the valuation of temperature derivatives," Papers 2209.05918, arXiv.org, revised Aug 2023.
    • Handle: RePEc:arx:papers:2209.05918
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    File URL: http://arxiv.org/pdf/2209.05918
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    Cited by:

    1. Ke Wan & Alain Kornhauser, 2023. "Market Making and Pricing of Financial Derivatives based on Road Travel Times," Papers 2305.02523, arXiv.org, revised May 2023.

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