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Comparison of extended mean-reversion and time series models for electricity spot price simulation considering negative prices

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  • Keles, Dogan
  • Genoese, Massimo
  • Möst, Dominik
  • Fichtner, Wolf
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    Abstract

    This paper evaluates different financial price and time series models, such as mean reversion, autoregressive moving average (ARMA), integrated ARMA (ARIMA) and general autoregressive conditional heteroscedasticity (GARCH) process, usually applied for electricity price simulations. However, as these models are developed to describe the stochastic behaviour of electricity prices, they are extended by a separate data treatment for the deterministic components (trend, daily, weekly and annual cycles) of electricity spot prices. Furthermore price jumps are considered and implemented within a regime-switching model. Since 2008 market design allows for negative prices at the European Energy Exchange, which also occurred for several hours in the last years. Up to now, only a few financial and time series approaches exist, which are able to capture negative prices. This paper presents a new approach incorporating negative prices.

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    Bibliographic Info

    Article provided by Elsevier in its journal Energy Economics.

    Volume (Year): 34 (2012)
    Issue (Month): 4 ()
    Pages: 1012-1032

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    Handle: RePEc:eee:eneeco:v:34:y:2012:i:4:p:1012-1032

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    Web page: http://www.elsevier.com/locate/eneco

    Related research

    Keywords: Electricity prices; Time-series models; Mean-reversion process; Negative prices;

    References

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    1. Weron, R & Bierbrauer, M & Trück, S, 2004. "Modeling electricity prices: jump diffusion and regime switching," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 336(1), pages 39-48.
    2. Rafal Weron, 2006. "Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach," HSC Books, Hugo Steinhaus Center, Wroclaw University of Technology, number hsbook0601.
    3. Lise, Wietze & Linderhof, Vincent & Kuik, Onno & Kemfert, Claudia & Ostling, Robert & Heinzow, Thomas, 2006. "A game theoretic model of the Northwestern European electricity market--market power and the environment," Energy Policy, Elsevier, vol. 34(15), pages 2123-2136, October.
    4. Ventosa, Mariano & Baillo, Alvaro & Ramos, Andres & Rivier, Michel, 2005. "Electricity market modeling trends," Energy Policy, Elsevier, vol. 33(7), pages 897-913, May.
    5. Schneider, Stefan & Schneider, Stefan, 2010. "Power Spot Price Models with negative Prices," MPRA Paper 29958, University Library of Munich, Germany.
    6. Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
    7. Jan Seifert & Marliese Uhrig-Homburg, 2007. "Modelling jumps in electricity prices: theory and empirical evidence," Review of Derivatives Research, Springer, vol. 10(1), pages 59-85, January.
    8. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    9. Gibson, Rajna & Schwartz, Eduardo S, 1990. " Stochastic Convenience Yield and the Pricing of Oil Contingent Claims," Journal of Finance, American Finance Association, vol. 45(3), pages 959-76, July.
    10. Möst, Dominik & Keles, Dogan, 2010. "A survey of stochastic modelling approaches for liberalised electricity markets," European Journal of Operational Research, Elsevier, vol. 207(2), pages 543-556, December.
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    Citations

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    Cited by:
    1. Keles, Dogan & Genoese, Massimo & Möst, Dominik & Ortlieb, Sebastian & Fichtner, Wolf, 2013. "A combined modeling approach for wind power feed-in and electricity spot prices," Energy Policy, Elsevier, vol. 59(C), pages 213-225.
    2. Kovacevic, Raimund M. & Paraschiv, Florentina, 2012. "Medium-term Planning for Thermal Electricity Production," Working Papers on Finance 1220, University of St. Gallen, School of Finance.
    3. Nowotarski, Jakub & Tomczyk, Jakub & Weron, Rafal, 2012. "Robust estimation and forecasting of the long-term seasonal component of electricity spot prices," MPRA Paper 42563, University Library of Munich, Germany.
    4. Sergey Voronin & Jarmo Partanen, 2013. "Price Forecasting in the Day-Ahead Energy Market by an Iterative Method with Separate Normal Price and Price Spike Frameworks," Energies, MDPI, Open Access Journal, vol. 6(11), pages 5897-5920, November.
    5. Florian Ziel & Rick Steinert, 2014. "Efficient Modeling and Forecasting of the Electricity Spot Price," Papers 1402.7027, arXiv.org.
    6. Paraschiv, Florentina, 2013. "Price Dynamics in Electricity Markets," Working Papers on Finance 1314, University of St. Gallen, School of Finance.
    7. Simon Hagemann, 2013. "Price Determinants in the German Intraday Market for Electricity: An Empirical Analysis," EWL Working Papers 1318, University of Duisburg-Essen, Chair for Management Science and Energy Economics, revised Oct 2013.

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