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A hybrid model for GEFCom2014 probabilistic electricity price forecasting

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  • Maciejowska, Katarzyna
  • Nowotarski, Jakub

Abstract

This paper provides detailed information on Team Poland’s winning methodology in the electricity price forecasting track of GEFCom2014. A new hybrid model extending the Quantile Regression Averaging (QRA) approach of Nowotarski and Weron (2015) is proposed. It consists of four major blocks: point forecasting, pre-filtering, quantile regression modeling and post-processing. This universal model structure enables a single block to be developed independently, without the performances of the remaining blocks being affected. The four-block model design is complemented by the inclusion of expert judgement, which may be of great importance in periods of unusually high or low electricity demand.

Suggested Citation

  • Maciejowska, Katarzyna & Nowotarski, Jakub, 2016. "A hybrid model for GEFCom2014 probabilistic electricity price forecasting," International Journal of Forecasting, Elsevier, vol. 32(3), pages 1051-1056.
  • Handle: RePEc:eee:intfor:v:32:y:2016:i:3:p:1051-1056
    DOI: 10.1016/j.ijforecast.2015.11.008
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    References listed on IDEAS

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    2. Nowotarski, Jakub & Raviv, Eran & Trück, Stefan & Weron, Rafał, 2014. "An empirical comparison of alternative schemes for combining electricity spot price forecasts," Energy Economics, Elsevier, vol. 46(C), pages 395-412.
    3. Maciejowska, Katarzyna & Nowotarski, Jakub, 2016. "A hybrid model for GEFCom2014 probabilistic electricity price forecasting," International Journal of Forecasting, Elsevier, vol. 32(3), pages 1051-1056.
    4. Weron, Rafał, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1030-1081.
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Probabilistic forecasting; Hybrid model; Quantile regression; Electricity spot price; Forecasts combination; Pinball function;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • 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
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

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