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Short- and mid-term forecasting of baseload electricity prices in the UK: The impact of intra-day price relationships and market fundamentals

Listed author(s):
  • Katarzyna Maciejowska
  • Rafal Weron

In this paper we investigate whether considering the fine structure of half-hourly electricity prices, the market closing prices of fundamentals (natural gas, coal and CO2) and the system-wide demand can lead to significantly more accurate short- and mid-term forecasts of APX UK baseload prices. We evaluate the predictive accuracy of a number of univariate and multivariate time series models over a three-year out-of-sample forecasting period and compare it against that of a benchmark autoregressive model. We find that in the short-term, up to a few business days ahead, a disaggregated model which independently predicts the intra-day prices and then takes their average to yield baseload price forecasts is the best performer. However, in the mid-term, factor models which explore the correlation structure of intra-day prices lead to significantly (as measured by the Diebold-Mariano test) better baseload price forecasts. At the same time, we observe that the inclusion of fundamental variables - especially natural gas prices (in the short-term) and coal prices (in the mid-term) - provides significant gains. The CO2 prices, on the other hand, generally do not improve the price forecasts at all, at least in the time period considered in this study (Apr. 2009 - Dec. 2013).

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File URL: http://www.im.pwr.wroc.pl/~hugo/RePEc/wuu/wpaper/HSC_15_04.pdf
File Function: Final version, 2015
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Paper provided by Hugo Steinhaus Center, Wroclaw University of Technology in its series HSC Research Reports with number HSC/15/04.

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Length: 15 pages
Date of creation: 2015
Publication status: Published as K. Maciejowska, R. Weron (2016) Short- and mid-term forecasting of baseload electricity prices in the UK: The impact of intra-day price relationships and market fundamentals, IEEE Transactions on Power Systems 31(2), 994-1005 (doi: 10.1109/TPWRS.2015.2416433).
Handle: RePEc:wuu:wpaper:hsc1504
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  1. Bessec Marie & Bouabdallah Othman, 2005. "What Causes The Forecasting Failure of Markov-Switching Models? A Monte Carlo Study," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(2), pages 1-24, June.
  2. Tao Hong, 2014. "Energy Forecasting: Past, Present, and Future," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 32, pages 43-48, Winter.
  3. Misiorek Adam & Trueck Stefan & Weron Rafal, 2006. "Point and Interval Forecasting of Spot Electricity Prices: Linear vs. Non-Linear Time Series Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(3), pages 1-36, September.
  4. Weron, Rafal & Misiorek, Adam, 2008. "Forecasting spot electricity prices: A comparison of parametric and semiparametric time series models," International Journal of Forecasting, Elsevier, vol. 24(4), pages 744-763.
  5. Fong Chan, Kam & Gray, Philip, 2006. "Using extreme value theory to measure value-at-risk for daily electricity spot prices," International Journal of Forecasting, Elsevier, vol. 22(2), pages 283-300.
  6. Schlueter, Stephan, 2010. "A long-term/short-term model for daily electricity prices with dynamic volatility," Energy Economics, Elsevier, vol. 32(5), pages 1074-1081, September.
  7. Liebl, Dominik, 2013. "Modeling and Forecasting Electricity Spot Prices: A Functional Data Perspective," MPRA Paper 50881, University Library of Munich, Germany.
  8. Katarzyna Maciejowska & Rafal Weron, 2013. "Forecasting of daily electricity spot prices by incorporating intra-day relationships: Evidence form the UK power market," HSC Research Reports HSC/13/01, Hugo Steinhaus Center, Wroclaw University of Technology, revised 15 Apr 2013.
  9. Clements,Michael & Hendry,David, 1998. "Forecasting Economic Time Series," Cambridge Books, Cambridge University Press, number 9780521634809, September.
  10. Rafal Weron, 2006. "Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach," HSC Books, Hugo Steinhaus Center, Wroclaw University of Technology, number hsbook0601.
  11. Weron, RafaƂ, 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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