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Hybrid Modelling Approaches for Forecasting Energy Spot Prices in EPEC market

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  • Tahir Miriyev
  • Alessandro Contu
  • Kevin Schafers
  • Ion Gabriel Ion

Abstract

In this work we considered several hybrid modelling approaches for forecasting energy spot prices in EPEC market. Hybridization is performed through combining a Naive model, Fourier analysis, ARMA and GARCH models, a mean-reversion and jump-diffusion model, and Recurrent Neural Networks (RNN). Training data was given in terms of electricity prices for 2013-2014 years, and test data as a year of 2015.

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  • Tahir Miriyev & Alessandro Contu & Kevin Schafers & Ion Gabriel Ion, 2020. "Hybrid Modelling Approaches for Forecasting Energy Spot Prices in EPEC market," Papers 2010.08400, arXiv.org.
    • Handle: RePEc:arx:papers:2010.08400
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    References listed on IDEAS

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    1. Alvaro Cartea & Marcelo Figueroa, 2005. "Pricing in Electricity Markets: A Mean Reverting Jump Diffusion Model with Seasonality," Applied Mathematical Finance, Taylor & Francis Journals, vol. 12(4), pages 313-335.
    2. Hong, Tao & Pinson, Pierre & Fan, Shu & Zareipour, Hamidreza & Troccoli, Alberto & Hyndman, Rob J., 2016. "Probabilistic energy forecasting: Global Energy Forecasting Competition 2014 and beyond," International Journal of Forecasting, Elsevier, vol. 32(3), pages 896-913.
    3. 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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