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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, Rafal

Abstract

When building stochastic models for electricity spot prices the problem of uttermost importance is the estimation and consequent forecasting of a component to deal with trends and seasonality in the data. While the short-term seasonal components (daily, weekly) are more regular and less important for valuation of typical power derivatives, the long-term seasonal components (LTSC; seasonal, annual) are much more difficult to tackle. Surprisingly, in many academic papers dealing with electricity spot price modeling the importance of the seasonal decomposition is neglected and the problem of forecasting it is not considered. With this paper we want to fill the gap and present a thorough study on estimation and forecasting of the LTSC of electricity spot prices. We consider a battery of models based on Fourier or wavelet decomposition combined with linear or exponential decay. We find that all considered wavelet-based models are significantly better in terms of forecasting spot prices up to a year ahead than all considered sine-based models. This result questions the validity and usefulness of stochastic models of spot electricity prices built on sinusoidal long-term seasonal components.

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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 42563.

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Date of creation: 11 Nov 2012
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Handle: RePEc:pra:mprapa:42563

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

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Cited by:
  1. Kriechbaumer, Thomas & Angus, Andrew & Parsons, David & Rivas Casado, Monica, 2014. "An improved wavelet–ARIMA approach for forecasting metal prices," Resources Policy, Elsevier, Elsevier, vol. 39(C), pages 32-41.
  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, Hugo Steinhaus Center, Wroclaw University of Technology HSC/13/07, Hugo Steinhaus Center, Wroclaw University of Technology.
  4. 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.
  5. Pawel Maryniak & Rafal Weron, 2014. "Forecasting the occurrence of electricity price spikes in the UK power market," HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Technology HSC/14/11, Hugo Steinhaus Center, Wroclaw University of Technology.
  6. Rafal Weron & Michal Zator, 2014. "A note on using the Hodrick-Prescott filter in electricity markets," HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Technology HSC/14/04, Hugo Steinhaus Center, Wroclaw University of Technology.

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