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A Novel Stochastic Copula Model for the Texas Energy Market

Author

Listed:
  • Sudeesha Warunasinghe

    (Department of Mathematics and Statistics, University of Calgary, 2500 University Dr NW, Calgary, AB T2N 1N4, Canada
    These authors contributed equally to this work.)

  • Anatoliy Swishchuk

    (Department of Mathematics and Statistics, University of Calgary, 2500 University Dr NW, Calgary, AB T2N 1N4, Canada
    These authors contributed equally to this work.)

Abstract

The simulation of wind power, electricity load, and natural gas prices will allow commodity traders to see the future movement of prices in a more probabilistic manner. The ability to observe possible paths for wind power, electricity load, and natural gas prices enables traders to obtain valuable insights for placing their trades on electricity prices. Since the above processes involve a seasonality factor, the seasonality component was modeled using a truncated Fourier series, and the random component was modeled using stochastic differential equations (SDE). It is evident from the literature that all the above processes are mean-reverting processes; thus, three mean-reverting Ornstein–Uhlenbeck (OU) processes were considered the model for wind power, the electricity load, and natural gas prices. Industry experts believe there is a correlation between wind power, the electricity load, and natural gas prices. For example, when wind power is higher and the electricity load is lower, natural gas prices are relatively low. The novelty of this study is the incorporation of the correlation structure between processes into the mean-reverting OU process using a copula function. Thus, the study utilized a vine copula and integrated it into the simulation. The study was conducted for the Texas energy market and used daily time scales for the simulations, and it was able to conclude that the proposed novel mean-reverting OU process outperforms the classical mean-reverting process in the case of wind power and the electricity load.

Suggested Citation

  • Sudeesha Warunasinghe & Anatoliy Swishchuk, 2025. "A Novel Stochastic Copula Model for the Texas Energy Market," Risks, MDPI, vol. 13(7), pages 1-32, July.
    • Handle: RePEc:gam:jrisks:v:13:y:2025:i:7:p:137-:d:1702957
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    References listed on IDEAS

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