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Short-term electricity price forecasting with time series models: A review and evaluation


Author Info

  • Rafal Weron
  • Adam Misiorek


We investigate the forecasting power of different time series models for electricity spot prices. The models include different specifications of linear autoregressive time series with heteroscedastic noise and/or additional fundamental variables and non-linear regime-switching TAR-type models. The models are tested on a time series of hourly system prices and loads from the California power market. Data from the period July 5, 1999 - April 2, 2000 are used for calibration and from the period April 3 - December 3, 2000 for out-of-sample testing.

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Bibliographic Info

Paper provided by Hugo Steinhaus Center, Wroclaw University of Technology in its series HSC Research Reports with number HSC/06/01.

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Length: 22 pages
Date of creation: 2006
Date of revision:
Publication status: Published in "Complex Electricity Markets", ed. W. Mielczarski, Chapter 10, 231-254 (2006).
Handle: RePEc:wuu:wpaper:hsc0601

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Related research

Keywords: Electricity price forecasting; Autoregression (AR) model; Threshold Autoregression (TAR) model; Electricity load;

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Cited by:
  1. Krzysztof Burnecki & Rafal Weron, 2006. "Visualization tools for insurance risk processes," HSC Research Reports HSC/06/06, Hugo Steinhaus Center, Wroclaw University of Technology.
  2. Weron, Rafal & Misiorek, Adam, 2007. "Heavy tails and electricity prices: Do time series models with non-Gaussian noise forecast better than their Gaussian counterparts?," MPRA Paper 2292, University Library of Munich, Germany, revised Oct 2007.
  3. Weron, Rafal & Misiorek, Adam, 2006. "Point and interval forecasting of wholesale electricity prices: Evidence from the Nord Pool market," MPRA Paper 1363, University Library of Munich, Germany.


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