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It never rains but it pours: Modelling the persistence of spikes in electricity prices

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Author Info
T M Christensen () (QUT)
A S Hurn () (QUT)
K A Lindsay (Glasgow)

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Abstract

During periods of market stress, electricity prices can rise dramatically. This paper treats these abnormal episodes or price spikes as count events and attempts to build a model of the spiking process. In contrast to the existing literature, which either ignores temporal dependence in the spiking process or attempts to model the dependence solely in terms of deterministic variables (like seasonal and day of the week effects), this paper argues that persistence in the spiking process is an important factor in building an effective model. A Poisson autoregressive framework is proposed in which price spikes occur as a result of the latent arrival and survival of system stresses. This formulation captures the salient features of the process adequately, and yields forecasts of price spikes that are superior to those obtained from na¨ıve models which do not account for persistence in the spiking process.

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Paper provided by National Centre for Econometric Research in its series NCER Working Paper Series with number 25.

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Length: 27 pages
Date of creation: 12 Jun 2008
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Handle: RePEc:qut:auncer:2008-5

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Related research
Keywords: Electricity Prices Extreme Events Poisson Regressions Poisson Autoregressive Model

Find related papers by JEL classification:
C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods
C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation and Testing

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  1. Bystrom, Hans N. E., 2005. "Extreme value theory and extremely large electricity price changes," International Review of Economics & Finance, Elsevier, vol. 14(1), pages 41-55. [Downloadable!] (restricted)
  2. Freeland, R. K. & McCabe, B. P. M., 2004. "Forecasting discrete valued low count time series," International Journal of Forecasting, Elsevier, vol. 20(3), pages 427-434. [Downloadable!] (restricted)
  3. Taylor, James W. & Buizza, Roberto, 2003. "Using weather ensemble predictions in electricity demand forecasting," International Journal of Forecasting, Elsevier, vol. 19(1), pages 57-70. [Downloadable!] (restricted)
  4. 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. [Downloadable!] (restricted)
  5. R. K. Freeland & B. P. M. McCabe, 2004. "Analysis of low count time series data by poisson autoregression," Journal of Time Series Analysis, Blackwell Publishing, vol. 25(5), pages 701-722, 09. [Downloadable!] (restricted)
  6. Adam Misiorek & Stefan Trueck & Rafal Weron, 2006. "Point and Interval Forecasting of Spot Electricity Prices: Linear vs. Non-Linear Time Series Models," Studies in Nonlinear Dynamics & Econometrics, Berkeley Electronic Press, vol. 10(3), pages 1362-1362. [Downloadable!] (restricted)
  7. William H. Greene, 1994. "Accounting for Excess Zeros and Sample Selection in Poisson and Negative Binomial Regression Models," Working Papers 94-10, New York University, Leonard N. Stern School of Business, Department of Economics.
  8. Alvaro Cartea & Marcelo Gustavo Figueroa, 2005. "Pricing in Electricity Markets: a Mean Reverting Jump Diffusion Model with Seasonality," Birkbeck Working Papers in Economics and Finance 0507, Birkbeck, School of Economics, Mathematics & Statistics. [Downloadable!]
    Other versions:
  9. Bierbrauer, Michael & Menn, Christian & Rachev, Svetlozar T. & Truck, Stefan, 2007. "Spot and derivative pricing in the EEX power market," Journal of Banking & Finance, Elsevier, vol. 31(11), pages 3462-3485, November. [Downloadable!] (restricted)
  10. Knittel, Christopher R. & Roberts, Michael R., 2005. "An empirical examination of restructured electricity prices," Energy Economics, Elsevier, vol. 27(5), pages 791-817, September. [Downloadable!] (restricted)
  11. Ralf Becker & Stan Hurn & Vlad Pavlov, 2007. "Modelling Spikes in Electricity Prices," NCER Working Paper Series 10, National Centre for Econometric Research. [Downloadable!]
    Other versions:
  12. Don Harding & Adrian Pagan, 2006. "The Econometric Analysis of Constructed Binary Time Series," Department of Economics - Working Papers Series 963, The University of Melbourne. [Downloadable!]
  13. Huisman, Ronald & Mahieu, Ronald, 2003. "Regime jumps in electricity prices," Energy Economics, Elsevier, vol. 25(5), pages 425-434, September. [Downloadable!] (restricted)
    Other versions:
    • Huisman, R. & Mahieu, R.J., 2001. "Regime Jumps in Electricity Prices," Research Paper ERS-2001-48-F&A Revision_, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus Uni. [Downloadable!]
  14. Robert Breunig & Serinah Najarian & Adrian Pagan, 2003. "Specification Testing of Markov Switching Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 65(s1), pages 703-725, December. [Downloadable!] (restricted)
  15. Hélyette Geman & Andrea Roncoroni, 2006. "Understanding the Fine Structure of Electricity Prices," Journal of Business, University of Chicago Press, vol. 79(3), pages 1225-1262, May. [Downloadable!]
  16. McCabe, B.P.M. & Martin, G.M., 2005. "Bayesian predictions of low count time series," International Journal of Forecasting, Elsevier, vol. 21(2), pages 315-330. [Downloadable!] (restricted)
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