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Modeling hourly Electricity Spot Market Prices as non stationary functional times series

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  • Liebl, Dominik

Abstract

The instantaneous nature of electricity distinguishes its spot prices from spot prices for equities and other commodities. Up to now electricity cannot be stored economically and therefore demand for electricity has an untempered effect on electricity prices. In particular, hourly electricity spot prices show a vast range of dynamics which can change rapidly. In this paper we introduce a robust version of functional principal component analysis for sparse data. The functional perspective interprets spot prices as functions of demand for electricity and allows to estimate a single price curve for each day. Variations in market fundamentals such as commodity prices are absorbed by the first principal components.

Suggested Citation

  • Liebl, Dominik, 2010. "Modeling hourly Electricity Spot Market Prices as non stationary functional times series," MPRA Paper 25017, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:25017
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    File URL: https://mpra.ub.uni-muenchen.de/25017/1/MPRA_paper_25017.pdf
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    References listed on IDEAS

    as
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    3. Willems, Bert & Rumiantseva, Ina & Weigt, Hannes, 2009. "Cournot versus Supply Functions: What does the data tell us?," Energy Economics, Elsevier, vol. 31(1), pages 38-47, January.
    4. Fang Yao & Hans-Georg Müller & Andrew J. Clifford & Steven R. Dueker & Jennifer Follett & Yumei Lin & Bruce A. Buchholz & John S. Vogel, 2003. "Shrinkage Estimation for Functional Principal Component Scores with Application to the Population Kinetics of Plasma Folate," Biometrics, The International Biometric Society, vol. 59(3), pages 676-685, September.
    5. Daniel Gervini, 2008. "Robust functional estimation using the median and spherical principal components," Biometrika, Biometrika Trust, vol. 95(3), pages 587-600.
    6. De Jong Cyriel, 2006. "The Nature of Power Spikes: A Regime-Switch Approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(3), pages 1-28, September.
    7. Rafal Weron & Adam Misiorek, 2005. "Modeling and forecasting electricity loads: A comparison," Econometrics 0502004, EconWPA.
    8. Wolfgang Karl Härdle & Stefan Trück, 2010. "The dynamics of hourly electricity prices," SFB 649 Discussion Papers SFB649DP2010-013, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
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    11. Peter Cramton, 2003. "Competitive Bidding Behavior in Uniform-Price Auction Markets," Papers of Peter Cramton 03ferc1, University of Maryland, Department of Economics - Peter Cramton, revised 2003.
    12. Klemperer, Paul D & Meyer, Margaret A, 1989. "Supply Function Equilibria in Oligopoly under Uncertainty," Econometrica, Econometric Society, vol. 57(6), pages 1243-1277, November.
    13. Rafal Weron, 2006. "Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach," HSC Books, Hugo Steinhaus Center, Wroclaw University of Technology, number hsbook0601.
    14. Kosater, Peter & Mosler, Karl, 2006. "Can Markov regime-switching models improve power-price forecasts? Evidence from German daily power prices," Applied Energy, Elsevier, vol. 83(9), pages 943-958, September.
    15. Park, Byeong U. & Mammen, Enno & Härdle, Wolfgang & Borak, Szymon, 2009. "Time Series Modelling With Semiparametric Factor Dynamics," Journal of the American Statistical Association, American Statistical Association, vol. 104(485), pages 284-298.
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    More about this item

    Keywords

    Functional principal component analysis; non stationary functional time series data; sparse data; electricity spot market prices; European Electricity Exchange (EEX).;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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