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Forecasting extreme electricity spot prices

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  • Volodymyr Korniichuk

Abstract

We propose a model for forecasting extreme electricity prices in real time (high frequency) settings. The unique feature of our model is its ability to forecast electricity price exceedances over very high thresholds, where only a few (if any) observations are available. The model can also be applied for simulating times of occurrence and magnitudes of the extreme prices. We employ a copula with a changing dependence parameter for capturing serial dependence in the extreme prices and the censored GPD for modelling their marginal distributions. For modelling times of the extreme price occurrences we propose an approach based on a negative binomial distribution. The model is applied to electricity spot prices from Australia's national electricity market.

Suggested Citation

  • Volodymyr Korniichuk, 2012. "Forecasting extreme electricity spot prices," Cologne Graduate School Working Paper Series 03-14, Cologne Graduate School in Management, Economics and Social Sciences.
    • Handle: RePEc:cgr:cgsser:03-14
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    File URL: http://www.cgs.uni-koeln.de/fileadmin/wiso_fak/cgs/pdf/working_paper/cgswp_03-14.pdf
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    References listed on IDEAS

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    1. Claudia Kluppelberg & Thilo Meyer-Brandis & Andrea Schmidt, 2010. "Electricity spot price modelling with a view towards extreme spike risk," Quantitative Finance, Taylor & Francis Journals, vol. 10(9), pages 963-974.
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    10. Eichler, M. & Grothe, O. & Manner, H. & Türk, D.D.T., 2012. "Modeling spike occurrences in electricity spot prices for forecasting," Research Memorandum 029, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    11. Aït-Sahalia, Yacine & Cacho-Diaz, Julio & Laeven, Roger J.A., 2015. "Modeling financial contagion using mutually exciting jump processes," Journal of Financial Economics, Elsevier, vol. 117(3), pages 585-606.
    12. Benoit Mandelbrot, 2015. "The Variation of Certain Speculative Prices," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78, World Scientific Publishing Co. Pte. Ltd..
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    Cited by:

    1. Clements, A.E. & Herrera, R. & Hurn, A.S., 2015. "Modelling interregional links in electricity price spikes," Energy Economics, Elsevier, vol. 51(C), pages 383-393.
    2. Manner, Hans & Türk, Dennis & Eichler, Michael, 2016. "Modeling and forecasting multivariate electricity price spikes," Energy Economics, Elsevier, vol. 60(C), pages 255-265.
    3. Lin Han & Ivor Cribben & Stefan Trueck, 2022. "Extremal Dependence in Australian Electricity Markets," Papers 2202.09970, arXiv.org.

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    More about this item

    Keywords

    electricity spot prices; copula; GPD; negative binomial distribution;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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