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Modeling electricity spot prices: combining mean reversion, spikes, and stochastic volatility

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  • Klaus Mayer
  • Thomas Schmid
  • Florian Weber

Abstract

With the liberalization of electricity trading, the electricity market has grown rapidly over the last decade. However, while spot and future markets are currently rather liquid, option trading is still limited. One of the potential reasons for this is that the electricity spot price process remains a puzzle to researchers and practitioners. In this paper, we propose an approach to model electricity spot prices that combines mean reversion, spikes, negative prices, and stochastic volatility. Thereby, we use different mean reversion rates for 'normal' and 'extreme' (spike) periods. Furthermore, all model parameters can easily be estimated using historical data. Consequently, we argue that this model does not only extend the academic literature on electricity spot price modeling, but is also suitable for practical purposes, such as an underlying price model for option pricing.

Suggested Citation

  • Klaus Mayer & Thomas Schmid & Florian Weber, 2015. "Modeling electricity spot prices: combining mean reversion, spikes, and stochastic volatility," The European Journal of Finance, Taylor & Francis Journals, vol. 21(4), pages 292-315, March.
    • Handle: RePEc:taf:eurjfi:v:21:y:2015:i:4:p:292-315
    DOI: 10.1080/1351847X.2012.716775
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    Citations

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    Cited by:

    1. Nikkinen, Jussi & Rothovius, Timo, 2019. "Market specific seasonal trading behavior in NASDAQ OMX electricity options," Journal of Commodity Markets, Elsevier, vol. 13(C), pages 16-29.
    2. Hosius, Emil & Seebaß, Johann V. & Wacker, Benjamin & Schlüter, Jan Chr., 2023. "The impact of offshore wind energy on Northern European wholesale electricity prices," Applied Energy, Elsevier, vol. 341(C).
    3. Chih-Chen Hsu & An-Sing Chen & Shih-Kuei Lin & Ting-Fu Chen, 2017. "The affine styled-facts price dynamics for the natural gas: evidence from daily returns and option prices," Review of Quantitative Finance and Accounting, Springer, vol. 48(3), pages 819-848, April.
    4. Volk-Makarewicz, Warren & Borovkova, Svetlana & Heidergott, Bernd, 2022. "Assessing the impact of jumps in an option pricing model: A gradient estimation approach," European Journal of Operational Research, Elsevier, vol. 298(2), pages 740-751.
    5. Russo, Marianna & Bertsch, Valentin, 2020. "A looming revolution: Implications of self-generation for the risk exposure of retailers," Energy Economics, Elsevier, vol. 92(C).
    6. Luis M. Abadie, 2021. "Energy Market Prices in Times of COVID-19: The Case of Electricity and Natural Gas in Spain," Energies, MDPI, vol. 14(6), pages 1-17, March.
    7. Gaurav Kapoor & Nuttanan Wichitaksorn & Wenjun Zhang, 2023. "Analyzing and forecasting electricity price using regime‐switching models: The case of New Zealand market," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 2011-2026, December.

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