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

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  • Liebl, Dominik
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    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.

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    Bibliographic Info

    Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 25017.

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    Date of creation: Sep 2010
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    Handle: RePEc:pra:mprapa:25017

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

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    1. Rafal Weron & Adam Misiorek, 2005. "Modeling and forecasting electricity loads: A comparison," Econometrics, EconWPA 0502004, EconWPA.
    2. Kosater, Peter & Mosler, Karl, 2005. "Can Markov-regime switching models improve power price forecasts? Evidence for German daily power prices," Discussion Papers in Statistics and Econometrics 1/05, University of Cologne, Department for Economic and Social Statistics.
    3. Wolfgang Karl Härdle & Stefan Trück, 2010. "The dynamics of hourly electricity prices," SFB 649 Discussion Papers SFB649DP2010-013, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Willems, Bert & Rumiantseva, I. & Weigt, H., 2007. "Cournot Versus Supply Functions: What does the Data Tell us?," Discussion Paper, Tilburg University, Center for Economic Research 2007-63, Tilburg University, Center for Economic Research.
    5. 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.
    6. Huisman, Ronald & Huurman, Christian & Mahieu, Ronald, 2007. "Hourly electricity prices in day-ahead markets," Energy Economics, Elsevier, vol. 29(2), pages 240-248, March.
    7. 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, American Statistical Association, vol. 104(485), pages 284-298.
    8. Rafal Weron, 2006. "Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach," HSC Books, Hugo Steinhaus Center, Wroclaw University of Technology, Hugo Steinhaus Center, Wroclaw University of Technology, number hsbook0601.
    9. Yao, Fang & Muller, Hans-Georg & Wang, Jane-Ling, 2005. "Functional Data Analysis for Sparse Longitudinal Data," Journal of the American Statistical Association, American Statistical Association, American Statistical Association, vol. 100, pages 577-590, June.
    10. Green, Richard J & Newbery, David M, 1992. "Competition in the British Electricity Spot Market," Journal of Political Economy, University of Chicago Press, University of Chicago Press, vol. 100(5), pages 929-53, October.
    11. 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.
    12. Klemperer, Paul D & Meyer, Margaret A, 1989. "Supply Function Equilibria in Oligopoly under Uncertainty," Econometrica, Econometric Society, Econometric Society, vol. 57(6), pages 1243-77, November.
    13. Daniel Gervini, 2008. "Robust functional estimation using the median and spherical principal components," Biometrika, Biometrika Trust, Biometrika Trust, vol. 95(3), pages 587-600.
    14. Mount, Timothy D. & Ning, Yumei & Cai, Xiaobin, 2006. "Predicting price spikes in electricity markets using a regime-switching model with time-varying parameters," Energy Economics, Elsevier, vol. 28(1), pages 62-80, January.
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