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Forecasting Spot Electricity Prices With Time Series Models

Author

Listed:
  • Rafal Weron

    (Hugo Steinhaus Center)

  • Adam Misiorek

    (Institute of Power Systems Automation)

Abstract

In this paper we study simple time series models and assess their forecasting performance. In particular we calibrate ARMA and ARMAX (where the exogenous variable is the system load) processes. Models are tested on a time series of California power market system prices and loads from the period proceeding and including the market crash.

Suggested Citation

  • Rafal Weron & Adam Misiorek, 2005. "Forecasting Spot Electricity Prices With Time Series Models," Econometrics 0504001, University Library of Munich, Germany.
  • Handle: RePEc:wpa:wuwpem:0504001
    Note: Type of Document - pdf; pages: 8. To appear in ”The European Electricity Market EEM-05”, Proceedings Volume
    as

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    File URL: https://econwpa.ub.uni-muenchen.de/econ-wp/em/papers/0504/0504001.pdf
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    References listed on IDEAS

    as
    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 & Adam Misiorek, 2005. "Modeling and forecasting electricity loads: A comparison," Econometrics 0502004, University Library of Munich, Germany.
    3. Vasicek, Oldrich, 1977. "An equilibrium characterization of the term structure," Journal of Financial Economics, Elsevier, vol. 5(2), pages 177-188, November.
    4. Conejo, Antonio J. & Contreras, Javier & Espinola, Rosa & Plazas, Miguel A., 2005. "Forecasting electricity prices for a day-ahead pool-based electric energy market," International Journal of Forecasting, Elsevier, vol. 21(3), pages 435-462.
    5. Merton, Robert C., 1976. "Option pricing when underlying stock returns are discontinuous," Journal of Financial Economics, Elsevier, vol. 3(1-2), pages 125-144.
    6. Huisman, Ronald & Mahieu, Ronald, 2003. "Regime jumps in electricity prices," Energy Economics, Elsevier, vol. 25(5), pages 425-434, September.
    7. Alvaro Escribano & J. Ignacio Peña & Pablo Villaplana, 2011. "Modelling Electricity Prices: International Evidence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 73(5), pages 622-650, October.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Electricity; price forecasting; ARMA model; seasonal component;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

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