Department of Economics and Business Economics

A regime-switching stochastic volatility model for forecasting electricity prices

Publication: ResearchWorking paper

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  • rp17_03

    Final published version, 735 KB, PDF-document

  • Peter Exterkate
    Peter ExterkateUniversity of Sydney and CREATESAustralia
  • Oskar Knapik
In a recent review paper, Weron (2014) pinpoints several crucial challenges outstanding in the area of electricity price forecasting. This research attempts to address all of them by i) showing the importance of considering fundamental price drivers in modeling, ii) developing new techniques for probabilistic (i.e. interval or density) forecasting of electricity prices, iii) introducing an universal technique for model comparison. We propose new regime-switching stochastic volatility model with three regimes (negative jump, normal price, positive jump (spike)) where the transition matrix depends on explanatory variables. Bayesian inference is explored in order to obtain predictive densities. The main focus of the paper is on shorttime density forecasting in Nord Pool intraday market. We show that the proposed model outperforms several benchmark models at this task.
Original languageEnglish
Place of PublicationAarhus
PublisherInstitut for Økonomi, Aarhus Universitet
Number of pages25
StatePublished - 30 Jan 2017
SeriesCREATES Research Papers
Number2017-03

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