IDEAS home Printed from https://ideas.repec.org/a/bla/ecorec/v83y2007i263p371-382.html
   My bibliography  Save this article

Modelling Spikes in Electricity Prices

Author

Listed:
  • RALF BECKER
  • STAN HURN
  • VLAD PAVLOV

Abstract

During periods of market stress, electricity prices can rise dramatically. Electricity retailers cannot pass these extreme prices on to customers because of retail price regulation. Improved prediction of these price spikes therefore is important for risk management. This paper builds a time‐varying‐probability Markov‐switching model of Queensland electricity prices, aimed particularly at forecasting price spikes. Variables capturing demand and weather patterns are used to drive the transition probabilities. Unlike traditional Markov‐switching models that assume normality of the prices in each state, the model presented here uses a generalised beta distribution to allow for the skewness in the distribution of electricity prices during high‐price episodes.

Suggested Citation

  • Ralf Becker & Stan Hurn & Vlad Pavlov, 2007. "Modelling Spikes in Electricity Prices," The Economic Record, The Economic Society of Australia, vol. 83(263), pages 371-382, December.
    • Handle: RePEc:bla:ecorec:v:83:y:2007:i:263:p:371-382
    DOI: 10.1111/j.1475-4932.2007.00427.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1475-4932.2007.00427.x
    Download Restriction: no
    File URL: https://libkey.io/10.1111/j.1475-4932.2007.00427.x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Filardo, Andrew J, 1994. "Business-Cycle Phases and Their Transitional Dynamics," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 299-308, July.
    2. Robert F. Engle & Jeffrey R. Russell, 1998. "Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data," Econometrica, Econometric Society, vol. 66(5), pages 1127-1162, September.
    3. Hamilton, James D., 1990. "Analysis of time series subject to changes in regime," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 39-70.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Li, Zhicheng & Chen, Xinyun & Xing, Haipeng, 2023. "A multifactor regime-switching model for inter-trade durations in the high-frequency limit order market," Economic Modelling, Elsevier, vol. 118(C).
    2. Lahiri, Kajal & Yang, Liu, 2013. "Forecasting Binary Outcomes," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1025-1106, Elsevier.
    3. Masaru Chiba, 2023. "Robust and efficient specification tests in Markov-switching autoregressive models," Statistical Inference for Stochastic Processes, Springer, vol. 26(1), pages 99-137, April.
    4. L. Bauwens & E. Otranto, 2013. "Modeling the Dependence of Conditional Correlations on Volatility," Working Paper CRENoS 201304, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    5. Nan Li & Simon S. Kwok, 2021. "Jointly determining the state dimension and lag order for Markov‐switching vector autoregressive models," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(4), pages 471-491, July.
    6. Ibrahim L. Awad, 2019. "Revisiting the Exchange Rate Pass-Through to Domestic Inflation in Egypt: Why Is the Statistical Association Weak in the Short Run?," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 18(1), pages 59-77, June.
    7. Franses, Philip Hans & Paap, Richard & Vroomen, Bjorn, 2004. "Forecasting unemployment using an autoregression with censored latent effects parameters," International Journal of Forecasting, Elsevier, vol. 20(2), pages 255-271.
    8. Diebold, Francis X & Rudebusch, Glenn D, 1996. "Measuring Business Cycles: A Modern Perspective," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 67-77, February.
    9. Mehmet Balcilar & Rangan Gupta & Anandamayee Majumdar & Stephen M. Miller, 2012. "Was the Recent Downturn in US GDP Predictable?," Working Papers 1210, University of Nevada, Las Vegas , Department of Economics.
    10. repec:diw:diwwpp:dp1519 is not listed on IDEAS
    11. Maddalena Cavicchioli, 2021. "OLS Estimation of Markov switching VAR models: asymptotics and application to energy use," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 105(3), pages 431-449, September.
    12. Chen, Bin & Hong, Yongmiao, 2014. "A unified approach to validating univariate and multivariate conditional distribution models in time series," Journal of Econometrics, Elsevier, vol. 178(P1), pages 22-44.
    13. Balcilar, Mehmet & Gupta, Rangan & Miller, Stephen M., 2015. "Regime switching model of US crude oil and stock market prices: 1859 to 2013," Energy Economics, Elsevier, vol. 49(C), pages 317-327.
    14. repec:dau:papers:123456789/11721 is not listed on IDEAS
    15. Matteo Manera & Alessandro Cologni, 2006. "The Asymmetric Effects of Oil Shocks on Output Growth: A Markov-Switching Analysis for the G-7 Countries," Working Papers 2006.29, Fondazione Eni Enrico Mattei.
    16. Gilles Dufrénot & Aurélia Jambois & Laurine Jambois & Guillaume Khayat, 2016. "Regime-Dependent Fiscal Multipliers in the United States," Open Economies Review, Springer, vol. 27(5), pages 923-944, November.
    17. Marco Rubilar-González & Gabriel Pino, 2018. "Are Euro-Area expectations about recession phases effective to anticipate consequences of economic crises?," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 9(2), pages 141-161, June.
    18. Oscar Jorda & Massimiliano Marcellino, "undated". "Stochastic Processes Subject To Time Scale Transformations: An Application To High-Frequency Fx Data," Department of Economics 00-02, California Davis - Department of Economics.
    19. Jiang, George J. & Lo, Ingrid, 2014. "Private information flow and price discovery in the U.S. treasury market," Journal of Banking & Finance, Elsevier, vol. 47(C), pages 118-133.
    20. Mehmet Balcilar & Reneé van Eyden & Josine Uwilingiye & Rangan Gupta, 2017. "The Impact of Oil Price on South African GDP Growth: A Bayesian Markov Switching-VAR Analysis," African Development Review, African Development Bank, vol. 29(2), pages 319-336, June.
    21. Kuhanathan Ano Sujithan & Sanvi Avouyi-Dovi, 2013. "The links between some European financial factors and the BRICS credit default swap spreads," Post-Print hal-01511898, HAL.
    22. Höppner, Florian & Wesche, Katrin, 2000. "Non-linear Effects of Fiscal Policy in Germany: A Markov-Switching Approach," Bonn Econ Discussion Papers 9/2000, University of Bonn, Bonn Graduate School of Economics (BGSE).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:ecorec:v:83:y:2007:i:263:p:371-382. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/esausea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.