Stochastic Modeling of Wind Derivatives with Application to the Alberta Energy Market

Sudeesha Warunasinghe () and Anatoliy Swishchuk ()
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Sudeesha Warunasinghe: Department of Mathematics and Statistics, University of Calgary, Calgary, AB T2N 1N4, Canada
Anatoliy Swishchuk: Department of Mathematics and Statistics, University of Calgary, Calgary, AB T2N 1N4, Canada

Risks, 2024, vol. 12, issue 2, 1-26

Abstract: Wind-power generators around the world face two risks, one due to changes in wind intensity impacting energy production, and the second due to changes in electricity retail prices. To hedge these risks simultaneously, the quanto option is an ideal financial tool. The natural logarithm of electricity prices of the study will be modeled with a variance gamma (VG) and normal inverse Gaussian (NIG) processes, while wind speed and power series will be modeled with an Ornstein–Uhlenbeck (OU) process. Since the risk from changing wind-power production and spot prices is highly correlated, we must model this correlation as well. This is reproduced by replacing the small jumps of the Lévy process with a Brownian component and correlating it with wind power and speed OU processes. Then, we will study the income of the wind-energy company from a stochastic point of view, and finally, we will price the quanto option of European put style for the wind-energy producer. We will compare quanto option prices obtained from the VG process and NIG process. The novelty brought into this study is the use of a new dataset in a new geographic location and a new Lévy process, VG, apart from NIG.

Keywords: wind derivatives; quanto options; energy markets; stochastic modeling for wind energy; variance gamma process; normal inverse Gaussian process (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 K2 M2 M4 (search for similar items in EconPapers)
Date: 2024
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