Stochastic Modeling of Wind Derivatives in Energy Markets

Fred Espen Benth, Luca Di Persio and Silvia Lavagnini
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Fred Espen Benth: Department of Mathematics, University of Oslo, 0316 Blindern, Norway
Luca Di Persio: Department of Computer Science, University of Verona, 37134 Verona, Italy
Silvia Lavagnini: Department of Mathematics, University of Oslo, 0316 Blindern, Norway

Risks, 2018, vol. 6, issue 2, 1-21

Abstract: We model the logarithm of the spot price of electricity with a normal inverse Gaussian (NIG) process and the wind speed and wind power production with two Ornstein–Uhlenbeck processes. In order to reproduce the correlation between the spot price and the wind power production, namely between a pure jump process and a continuous path process, respectively, we replace the small jumps of the NIG process by a Brownian term. We then apply our models to two different problems: first, to study from the stochastic point of view the income from a wind power plant, as the expected value of the product between the electricity spot price and the amount of energy produced; then, to construct and price a European put-type quanto option in the wind energy markets that allows the buyer to hedge against low prices and low wind power production in the plant. Calibration of the proposed models and related price formulas is also provided, according to specific datasets.

Keywords: energy markets; weather derivatives; quanto option; normal inverse Gaussian process; stochastic models for wind energy (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 K2 M2 M4 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (20)

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