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Forecasting electricity spot prices using time-series models with a double temporal segmentation


  • Marie Bessec

    (LEDa - Laboratoire d'Economie de Dauphine - Université Paris-Dauphine)

  • Julien Fouquau

    (LEDa - Laboratoire d'Economie de Dauphine - Université Paris-Dauphine)

  • Sophie Méritet

    (LEDa - Laboratoire d'Economie de Dauphine - Université Paris-Dauphine)


The French wholesale market is set to expand in the next few years under European pressure and national decisions. In this paper, we assess the forecasting ability of several classes of time series models for electricity wholesale spot prices at a day-ahead horizon in France. Electricity spot prices display a strong seasonal pattern, particularly in France given the high share of electric heating in housing during winter time. To deal with this pattern, we implement a double temporal segmentation of the data. For each trading period and season, we use a large number of specifications based on market fundamentals: linear regressions, Markov-switching models, threshold models with a smooth transition. An extensive evaluation on French data shows that modeling each season independently leads to better results. Among non-linear models, MS models designed to capture the sudden and fast-reverting spikes in the price dynamics yield more accurate forecasts. Finally, pooling forecasts gives more reliable results.

Suggested Citation

  • Marie Bessec & Julien Fouquau & Sophie Méritet, 2014. "Forecasting electricity spot prices using time-series models with a double temporal segmentation," Post-Print hal-01502835, HAL.
  • Handle: RePEc:hal:journl:hal-01502835
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    References listed on IDEAS

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    Cited by:

    1. Bessec, Marie & Fouquau, Julien, 2018. "Short-run electricity load forecasting with combinations of stationary wavelet transforms," European Journal of Operational Research, Elsevier, vol. 264(1), pages 149-164.
    2. Bartosz Uniejewski & Jakub Nowotarski & Rafał Weron, 2016. "Automated Variable Selection and Shrinkage for Day-Ahead Electricity Price Forecasting," Energies, MDPI, Open Access Journal, vol. 9(8), pages 1-22, August.
    3. repec:ipg:wpaper:2014-514 is not listed on IDEAS

    More about this item


    Electricity spot prices; forecasting; regime-switching;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting


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