This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

Point and Interval Forecasting of Spot Electricity Prices: Linear vs. Non-Linear Time Series Models

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Adam Misiorek (Institute of Power Systems Automation)
Stefan Trueck (Queensland University of Technology)
Rafal Weron (Wroclaw University of Technology)

Additional information is available for the following registered author(s):

Abstract

In this paper we assess the short-term forecasting power of different time series models in the electricity spot market. In particular we calibrate AR/ARX (''X'' stands for exogenous/fundamental variable -- system load in our study), AR/ARX-GARCH, TAR/TARX and Markov regime-switching models to California Power Exchange (CalPX) system spot prices. We then use them for out-of-sample point and interval forecasting in normal and extremely volatile periods preceding the market crash in winter 2000/2001. We find evidence that (i) non-linear, threshold regime-switching (TAR/TARX) models outperform their linear counterparts, both in point and interval forecasting, and that (ii) an additional GARCH component generally decreases point forecasting efficiency. Interestingly, the former result challenges a number of previously published studies on the failure of non-linear regime-switching models in forecasting.

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help file. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.bepress.com/cgi/viewcontent.cgi?article=1362&context=snde
File Format: application/pdf
File Function:
Download Restriction: Subscription to the journal may be required to access full texts.

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

Publisher Info
Article provided by Berkeley Electronic Press in its journal Studies in Nonlinear Dynamics & Econometrics.

Volume (Year): 10 (2006)
Issue (Month): 3 ()
Pages: 1362-1362
Download reference. The following formats are available: HTML, plain text, BibTeX, RIS (EndNote), ReDIF
Handle: RePEc:bep:sndecm:10:2006:3:1362-1362

Note: oai:bepress:snde-1362
Contact details of provider:
Web page: http://www.bepress.com/snde/

Order Information:
Web: http://www.bepress.com/subscriptions.html

For technical questions regarding this item, or to correct its listing, contact: (Christopher F. Baum).

Related research
Keywords: power market spot price forecasting autoregressive model heteroscedasticity regime-switching model threshold autoregression

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

  1. Paul L. Joskow, 2001. "California's Electricity Crisis," NBER Working Papers 8442, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
    Other versions:
  2. Michael Bierbrauer & Stefan Trueck & Rafal Weron, 2005. "Modeling electricity prices with regime switching models," Econometrics 0502005, EconWPA. [Downloadable!]
  3. 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. [Downloadable!] (restricted)
  4. Max Stevenson, 2001. "Filtering and Forecasting Spot Electricity Prices in the Increasingly Deregulated Australian Electricity Market," Research Paper Series 63, Quantitative Finance Research Centre, University of Technology, Sydney. [Downloadable!]
  5. Jong, C. de & Huisman, R., 2002. "Option Formulas for Mean-Reverting Power Prices with Spikes," Research Paper ERS-2002-96-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!]
  6. Peter F. Christoffersen & Francis X. Diebold, 2000. "How Relevant is Volatility Forecasting for Financial Risk Management?," The Review of Economics and Statistics, MIT Press, vol. 82(1), pages 12-22, February. [Downloadable!] (restricted)
    Other versions:
  7. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-84, March. [Downloadable!] (restricted)
  8. Teräsvirta, Timo, 2005. "Forecasting economic variables with nonlinear models," Working Paper Series in Economics and Finance 598, Stockholm School of Economics, revised 29 Dec 2005. [Downloadable!]
    Other versions:
  9. Rafal Weron & Adam Misiorek, 2005. "Forecasting Spot Electricity Prices With Time Series Models," Econometrics 0504001, EconWPA. [Downloadable!]
  10. Jong, C. de, 2005. "The Nature of Power Spikes: a regime-switch approach," Research Paper ERS-2005-052-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!]
  11. Marie Bessec & Othman Bouabdallah, 2005. "What Causes The Forecasting Failure of Markov-Switching Models? A Monte Carlo Study," Studies in Nonlinear Dynamics & Econometrics, Berkeley Electronic Press, vol. 9(2), pages 1171-1171. [Downloadable!] (restricted)
    Other versions:
  12. Niels Haldrup & Morten O. Nielsen, 2004. "A Regime Switching Long Memory Model for Electricity Prices," Economics Working Papers 2004-2, School of Economics and Management, University of Aarhus. [Downloadable!]
    Other versions:
  13. Bruce Hansen, 1997. "Inference in TAR Models," Studies in Nonlinear Dynamics & Econometrics, Berkeley Electronic Press, vol. 2(1), pages 1-14. [Downloadable!] (restricted)
  14. 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)
  15. Chiang, Thomas C & Doong, Shuh-Chyi, 2001. " Empirical Analysis of Stock Returns and Volatility: Evidence from Seven Asian Stock Markets Based on TAR-GARCH Model," Review of Quantitative Finance and Accounting, Springer, vol. 17(3), pages 301-18, November. [Downloadable!] (restricted)
  16. B. Ricky Rambharat & Anthony E. Brockwell & Duane J. Seppi, 2005. "A threshold autoregressive model for wholesale electricity prices," Journal Of The Royal Statistical Society Series C, Royal Statistical Society, vol. 54(2), pages 287-299. [Downloadable!] (restricted)
  17. 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!]
  18. Hamilton, James D., 1990. "Analysis of time series subject to changes in regime," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 39-70. [Downloadable!] (restricted)
  19. Ventosa, Mariano & Baillo, Alvaro & Ramos, Andres & Rivier, Michel, 2005. "Electricity market modeling trends," Energy Policy, Elsevier, vol. 33(7), pages 897-913, May. [Downloadable!] (restricted)
  20. M. Angeles Carnero & Siem Jan Koopman & Marius Ooms, 2003. "Periodic Heteroskedastic RegARFIMA Models for Daily Electricity Spot Prices," Tinbergen Institute Discussion Papers 03-071/4, Tinbergen Institute. [Downloadable!]
    Other versions:
  21. Gordon W. Crawford & Michael C. Fratantoni, 2003. "Assessing the Forecasting Performance of Regime-Switching, ARIMA and GARCH Models of House Prices," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 31(2), pages 223-243, 06. [Downloadable!] (restricted)
  22. Vehvilainen, Iivo & Pyykkonen, Tuomas, 2005. "Stochastic factor model for electricity spot price--the case of the Nordic market," Energy Economics, Elsevier, vol. 27(2), pages 351-367, March. [Downloadable!] (restricted)
  23. 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. [Downloadable!] (restricted)
Full references

Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Massimiliano Serati & Matteo Manera & Michele Plotegher, 2008. "Modelling electricity prices: from the state of the art to a draft of a new proposal," LIUC Papers in Economics 210, Cattaneo University (LIUC). [Downloadable!]
  2. Weron, Rafal & Misiorek, Adam, 2006. "Point and interval forecasting of wholesale electricity prices: Evidence from the Nord Pool market," MPRA Paper 1363, University Library of Munich, Germany. [Downloadable!]
  3. Christian Huurman & Francesco Ravazzolo & Chen Zhou, 2007. "The Power of Weather: Some Empirical Evidence on Predicting Day-ahead Power Prices through Day-ahead Weather Forecasts," Tinbergen Institute Discussion Papers 07-036/4, Tinbergen Institute. [Downloadable!]
  4. Weron, Rafal & Misiorek, Adam, 2007. "Heavy tails and electricity prices: Do time series models with non-Gaussian noise forecast better than their Gaussian counterparts?," MPRA Paper 2292, University Library of Munich, Germany, revised Oct 2007. [Downloadable!]
  5. Alexander Boogert & Dominique Dupont, 2007. "When Supply Meets Demand: The Case of Hourly Spot Electricity Prices," Birkbeck Working Papers in Economics and Finance 0707, Birkbeck, School of Economics, Mathematics & Statistics. [Downloadable!]
Statistics
Access and download statistics

Did you know? IDEAS also indexes book chapters.

This page was last updated on 2008-11-19.

This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.