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Forecasting day ahead electricity spot prices: The impact of the EXAA to other European electricity markets

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  • Florian Ziel
  • Rick Steinert
  • Sven Husmann

Abstract

In our paper we analyze the relationship between the day-ahead electricity price of the Energy Exchange Austria (EXAA) and other day-ahead electricity prices in Europe. We focus on markets, which settle their prices after the EXAA, which enables traders to include the EXAA price into their calculations. For each market we employ econometric models to incorporate the EXAA price and compare them with their counterparts without the price of the Austrian exchange. By employing a forecasting study, we find that electricity price models can be improved when EXAA prices are considered.

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  • Florian Ziel & Rick Steinert & Sven Husmann, 2015. "Forecasting day ahead electricity spot prices: The impact of the EXAA to other European electricity markets," Papers 1501.00818, arXiv.org, revised Dec 2015.
  • Handle: RePEc:arx:papers:1501.00818
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    References listed on IDEAS

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    1. Ziel, Florian & Steinert, Rick & Husmann, Sven, 2015. "Efficient modeling and forecasting of electricity spot prices," Energy Economics, Elsevier, vol. 47(C), pages 98-111.
    2. Viehmann, Johannes, 2011. "Risk premiums in the German day-ahead Electricity Market," Energy Policy, Elsevier, vol. 39(1), pages 386-394, January.
    3. Taylor, James W., 2010. "Triple seasonal methods for short-term electricity demand forecasting," European Journal of Operational Research, Elsevier, vol. 204(1), pages 139-152, July.
    4. Kristiansen, Tarjei, 2012. "Forecasting Nord Pool day-ahead prices with an autoregressive model," Energy Policy, Elsevier, vol. 49(C), pages 328-332.
    5. Karakatsani, Nektaria V. & Bunn, Derek W., 2008. "Forecasting electricity prices: The impact of fundamentals and time-varying coefficients," International Journal of Forecasting, Elsevier, vol. 24(4), pages 764-785.
    6. Davide Ciferri & Maria Chiara D’Errico & Paolo Polinori, 2020. "Integration and convergence in European electricity markets," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 37(2), pages 463-492, July.
    7. Bordignon, Silvano & Bunn, Derek W. & Lisi, Francesco & Nan, Fany, 2013. "Combining day-ahead forecasts for British electricity prices," Energy Economics, Elsevier, vol. 35(C), pages 88-103.
    8. Liebl, Dominik, 2013. "Modeling and Forecasting Electricity Spot Prices: A Functional Data Perspective," MPRA Paper 50881, University Library of Munich, Germany.
    9. 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.
    10. Liu, Heping & Shi, Jing, 2013. "Applying ARMA–GARCH approaches to forecasting short-term electricity prices," Energy Economics, Elsevier, vol. 37(C), pages 152-166.
    11. Ying-Yi Hong & Ching-Ping Wu, 2012. "Day-Ahead Electricity Price Forecasting Using a Hybrid Principal Component Analysis Network," Energies, MDPI, vol. 5(11), pages 1-15, November.
    12. Egil Ferkingstad & Anders L{o}land & Mathilde Wilhelmsen, 2011. "Causal modeling and inference for electricity markets," Papers 1110.5429, arXiv.org.
    13. Ferkingstad, Egil & Løland, Anders & Wilhelmsen, Mathilde, 2011. "Causal modeling and inference for electricity markets," Energy Economics, Elsevier, vol. 33(3), pages 404-412, May.
    14. Francis X. Diebold, 2015. "Comparing Predictive Accuracy, Twenty Years Later: A Personal Perspective on the Use and Abuse of Diebold-Mariano Tests," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(1), pages 1-1, January.
    15. Hickey, Emily & Loomis, David G. & Mohammadi, Hassan, 2012. "Forecasting hourly electricity prices using ARMAX–GARCH models: An application to MISO hubs," Energy Economics, Elsevier, vol. 34(1), pages 307-315.
    16. repec:taf:applec:45:y:2013:i:18:p:2683-2693 is not listed on IDEAS
    17. Ronald Huisman & Mehtap Kili砍, 2013. "A history of European electricity day-ahead prices," Applied Economics, Taylor & Francis Journals, vol. 45(18), pages 2683-2693, June.
    18. Serinaldi, Francesco, 2011. "Distributional modeling and short-term forecasting of electricity prices by Generalized Additive Models for Location, Scale and Shape," Energy Economics, Elsevier, vol. 33(6), pages 1216-1226.
    19. Bruno Bosco & Lucia Parisio & Matteo Pelagatti & Fabio Baldi, 2010. "Long-run relations in european electricity prices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(5), pages 805-832.
    20. Zachmann, Georg, 2008. "Electricity wholesale market prices in Europe: Convergence?," Energy Economics, Elsevier, vol. 30(4), pages 1659-1671, July.
    21. Bunn, Derek W. & Gianfreda, Angelica, 2010. "Integration and shock transmissions across European electricity forward markets," Energy Economics, Elsevier, vol. 32(2), pages 278-291, March.
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