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Robust estimation and forecasting of the long-term seasonal component of electricity spot prices

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  • Nowotarski, Jakub
  • Tomczyk, Jakub
  • Weron, Rafał

Abstract

We present the results of an extensive study on estimation and forecasting of the long-term seasonal component (LTSC) of electricity spot prices. We consider a battery of over 300 models, including monthly dummies and models based on Fourier or wavelet decomposition combined with linear or exponential decay. We find that the considered wavelet-based models are significantly better in terms of forecasting spot prices up to a year ahead than the commonly used monthly dummies and sine-based models. This result questions the validity and usefulness of stochastic models of spot electricity prices built on the latter two types of LTSC models.

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Bibliographic Info

Article provided by Elsevier in its journal Energy Economics.

Volume (Year): 39 (2013)
Issue (Month): C ()
Pages: 13-27

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Handle: RePEc:eee:eneeco:v:39:y:2013:i:c:p:13-27

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Web page: http://www.elsevier.com/locate/eneco

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Keywords: Electricity spot price; Long-term seasonal component; Robust modeling; Forecasting; Wavelets;

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References

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Citations

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Cited by:
  1. Fouquau, Julien & Bessec, Marie & Méritet, Sophie, 2014. "Forecasting electricity spot prices using time-series models with a double temporal segmentation," Economics Papers from University Paris Dauphine 123456789/13532, Paris Dauphine University.
  2. Joanna Janczura, 2014. "Pricing electricity derivatives within a Markov regime-switching model: a risk premium approach," Computational Statistics, Springer, vol. 79(1), pages 1-30, February.
  3. Jakub Nowotarski & Eran Raviv & Stefan Trueck & Rafal Weron, 2013. "An empirical comparison of alternate schemes for combining electricity spot price forecasts," HSC Research Reports HSC/13/07, Hugo Steinhaus Center, Wroclaw University of Technology.
  4. Kriechbaumer, Thomas & Angus, Andrew & Parsons, David & Rivas Casado, Monica, 2014. "An improved wavelet–ARIMA approach for forecasting metal prices," Resources Policy, Elsevier, vol. 39(C), pages 32-41.

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