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.
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Giorgini, A., Mamon, R. S., & Rodrigo, M. R. (2021). A stochastic harmonic oscillator temperature model for the valuation of weather derivatives. Mathematics, 9(22). https://doi.org/10.3390/math9222890
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