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Pricing And Hedging Of Temperature Derivatives In A Model With Memory

Author

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  • MARKUS HESS

    (Department of Mechanical and Process Engineering, University of Kaiserslautern-Landau, Gottlieb-Daimler-Straße, 67663 Kaiserslautern, Germany)

Abstract

With view on global warming and the ongoing climate change, weather derivatives play an increasingly important role for many companies and financial investors, as they constitute useful hedging instruments against disadvantageous weather conditions. In this paper, we present a new temperature model based on generalized Langevin equations driven by Lévy processes. The proposed arithmetic approach captures numerous stylized facts of empirical temperature behavior like seasonal variations, time-dependent volatilities, memory effects, heavy tails and skewness. We further derive a representation for the related meteorological temperature forecast curve and infer the risk-neutral price dynamics of temperature derivatives like CAT, CDD and HDD futures. We finally deduce the minimal variance hedging portfolio in a specific temperature futures market by an application of a stochastic maximum principle and present several practical examples.

Suggested Citation

  • Markus Hess, 2024. "Pricing And Hedging Of Temperature Derivatives In A Model With Memory," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 27(01), pages 1-34, February.
    • Handle: RePEc:wsi:ijtafx:v:27:y:2024:i:01:n:s0219024923500310
    DOI: 10.1142/S0219024923500310
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