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On transition probabilities of regime switching in electricity prices

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  • Kanamura, Takashi
  • O[combining macron]hashi, Kazuhiko
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    Abstract

    We analyze the transition probabilities of regime switching in electricity prices by explicitly incorporating the underlying demand/supply structure. We show that the transition probabilities of electricity prices cannot be constant, and depend on both the current demand level relative to the supply capacity and the trends of demand fluctuation. These results not only contrast with the assumption of constant transition probabilities on which many regime-switching models are built, but also provide new insights on the determinants of the state-dependent transition probabilities of regime switching.

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    File URL: http://www.sciencedirect.com/science/article/B6V7G-4P8B0T9-2/1/3eb42f7d0cde66453818df71a267ffcb
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    Bibliographic Info

    Article provided by Elsevier in its journal Energy Economics.

    Volume (Year): 30 (2008)
    Issue (Month): 3 (May)
    Pages: 1158-1172

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    Handle: RePEc:eee:eneeco:v:30:y:2008:i:3:p:1158-1172

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

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    References

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    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.:
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    1. de Jong, C.M. & Huisman, R., 2002. "Option Formulas for Mean-Reverting Power Prices with Spikes," ERIM Report Series Research in Management ERS-2002-96-F&A, 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.
    2. M. T. Barlow, 2002. "A Diffusion Model For Electricity Prices," Mathematical Finance, Wiley Blackwell, vol. 12(4), pages 287-298.
    3. Kanamura, Takashi & Ohashi, Kazuhiko, 2007. "A structural model for electricity prices with spikes: Measurement of spike risk and optimal policies for hydropower plant operation," Energy Economics, Elsevier, vol. 29(5), pages 1010-1032, September.
    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.
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    Cited by:
    1. Janczura, Joanna & Trueck, Stefan & Weron, Rafal & Wolff, Rodney, 2012. "Identifying spikes and seasonal components in electricity spot price data: A guide to robust modeling," MPRA Paper 39277, University Library of Munich, Germany.
    2. repec:dgr:umamet:2012029 is not listed on IDEAS
    3. Joanna Janczura & Rafał Weron, 2012. "Efficient estimation of Markov regime-switching models: An application to electricity spot prices," AStA Advances in Statistical Analysis, Springer, vol. 96(3), pages 385-407, July.
    4. Janczura, Joanna & Weron, Rafal, 2010. "An empirical comparison of alternate regime-switching models or electricity spot prices," MPRA Paper 20546, University Library of Munich, Germany.
    5. Carlo Lucheroni, 2012. "A hybrid SETARX model for spikes in tight electricity markets," Operations Research and Decisions, Wroclaw University of Technology, Institute of Organization and Management, vol. 1, pages 13-49.
    6. Weron, Rafal & Janczura, Joanna, 2010. "Efficient estimation of Markov regime-switching models: An application to electricity wholesale market prices," MPRA Paper 26628, University Library of Munich, Germany.
    7. Redl, Christian & Haas, Reinhard & Huber, Claus & Böhm, Bernhard, 2009. "Price formation in electricity forward markets and the relevance of systematic forecast errors," Energy Economics, Elsevier, vol. 31(3), pages 356-364, May.
    8. Nowotarski, Jakub & Tomczyk, Jakub & Weron, Rafał, 2013. "Robust estimation and forecasting of the long-term seasonal component of electricity spot prices," Energy Economics, Elsevier, vol. 39(C), pages 13-27.
    9. Joanna Janczura, 2012. "Pricing electricity derivatives within a Markov regime-switching model," Papers 1203.5442, arXiv.org.

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