IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v144y2025ics0140988325001653.html
   My bibliography  Save this article

Comparison of indicator saturation and Markov regime-switching models for Brazilian electricity prices

Author

Listed:
  • de Castro Matias, Marcos
  • Tabak, Benjamin Miranda

Abstract

In this study, we compared the results obtained from the application of two different approaches to model Brazilian electricity prices. One of them is the Indicator Saturation model, which consider simultaneously impulse, step, trend events and autocorrelation. The other one is the Markov regime-switching model. We considered the marginal operating cost as the Brazilian electricity spot price, and the study was applied in the four different Brazilian submarkets. We concluded that the Indicator Saturation approach outperforms the regime-switching model in terms of outlier detection. We discussed the relevance of this study as a response to the increase in electricity price volatility caused by the energy transition, as well as to enrich the debate related to the possible change in the methodology for calculating the Brazilian electricity spot price within the framework of the electricity sector reform underway in Brazil.

Suggested Citation

  • de Castro Matias, Marcos & Tabak, Benjamin Miranda, 2025. "Comparison of indicator saturation and Markov regime-switching models for Brazilian electricity prices," Energy Economics, Elsevier, vol. 144(C).
  • Handle: RePEc:eee:eneeco:v:144:y:2025:i:c:s0140988325001653
    DOI: 10.1016/j.eneco.2025.108341
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988325001653
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.eneco.2025.108341?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Marczak, Martyna & Proietti, Tommaso, 2016. "Outlier detection in structural time series models: The indicator saturation approach," International Journal of Forecasting, Elsevier, vol. 32(1), pages 180-202.
    2. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry & Felix Pretis, 2015. "Detecting Location Shifts during Model Selection by Step-Indicator Saturation," Econometrics, MDPI, vol. 3(2), pages 1-25, April.
    3. Huisman, Ronald & Mahieu, Ronald, 2003. "Regime jumps in electricity prices," Energy Economics, Elsevier, vol. 25(5), pages 425-434, September.
    4. Paulo Cesar Coutinho & Andre Rossi de Oliveira, 2013. "Trading Forward in the Brazilian Electricity Market," International Journal of Energy Economics and Policy, Econjournals, vol. 3(3), pages 272-287.
    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. Apergis, Nicholas & Pan, Wei-Fong & Reade, James & Wang, Shixuan, 2023. "Modelling Australian electricity prices using indicator saturation," Energy Economics, Elsevier, vol. 120(C).
    2. Daglish, Toby & de Bragança, Gabriel Godofredo Fiuza & Owen, Sally & Romano, Teresa, 2021. "Pricing effects of the electricity market reform in Brazil," Energy Economics, Elsevier, vol. 97(C).
    3. Ericsson, Neil R., 2017. "How biased are U.S. government forecasts of the federal debt?," International Journal of Forecasting, Elsevier, vol. 33(2), pages 543-559.
    4. Ericsson, Neil R., 2017. "Interpreting estimates of forecast bias," International Journal of Forecasting, Elsevier, vol. 33(2), pages 563-568.
    5. Kaufmann, Robert K., 2023. "Energy price volatility affects decisions to purchase energy using capital: Motor vehicles," Energy Economics, Elsevier, vol. 126(C).
    6. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    7. Andrew B. Martinez & Neil R. Ericsson, 2025. "Improving empirical models and forecasts with saturation-based machine learning," Annals of Operations Research, Springer, vol. 346(1), pages 447-487, March.
    8. Ericsson Neil R., 2016. "Testing for and estimating structural breaks and other nonlinearities in a dynamic monetary sector," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(4), pages 377-398, September.
    9. Neil R. Ericsson & Mohammed H. I. Dore & Hassan Butt, 2022. "Detecting and Quantifying Structural Breaks in Climate," Econometrics, MDPI, vol. 10(4), pages 1-27, November.
    10. Kaufmann, Robert K. & Schroer, Colter, 2023. "Social and environmental events disrupt the relation between motor gasoline prices and market fundamentals," Energy Economics, Elsevier, vol. 126(C).
    11. Alain Monfort & Olivier Féron, 2012. "Joint econometric modeling of spot electricity prices, forwards and options," Review of Derivatives Research, Springer, vol. 15(3), pages 217-256, October.
    12. Ericsson, Neil R., 2016. "Eliciting GDP forecasts from the FOMC’s minutes around the financial crisis," International Journal of Forecasting, Elsevier, vol. 32(2), pages 571-583.
    13. Rafał Weron, 2009. "Heavy-tails and regime-switching in electricity prices," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 69(3), pages 457-473, July.
    14. Jun Maekawa & Koji Shimada, 2019. "A Speculative Trading Model for the Electricity Market: Based on Japan Electric Power Exchange," Energies, MDPI, vol. 12(15), pages 1-15, July.
    15. Dima, Bogdan & Dima, Ştefana Maria & Ioan, Roxana, 2025. "The short-run impact of investor expectations’ past volatility on current predictions: The case of VIX," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 98(C).
    16. Marczak, Martyna & Proietti, Tommaso, 2016. "Outlier detection in structural time series models: The indicator saturation approach," International Journal of Forecasting, Elsevier, vol. 32(1), pages 180-202.
    17. Felix Pretis & Michael Mann & Robert Kaufmann, 2015. "Testing competing models of the temperature hiatus: assessing the effects of conditioning variables and temporal uncertainties through sample-wide break detection," Climatic Change, Springer, vol. 131(4), pages 705-718, August.
    18. Higgs, Helen & Worthington, Andrew, 2008. "Stochastic price modeling of high volatility, mean-reverting, spike-prone commodities: The Australian wholesale spot electricity market," Energy Economics, Elsevier, vol. 30(6), pages 3172-3185, November.
    19. Michel Culot & Valérie Goffin & Steve Lawford & Sébastien de Menten and Yves Smeers, . "Practical stochastic modeling of electricity prices," Journal of Energy Markets, Journal of Energy Markets.
    20. Karsten Kohler & Engelbert Stockhammer, 2023. "Flexible exchange rates in emerging markets: shock absorbers or drivers of endogenous cycles?," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 32(2), pages 551-572.

    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:eee:eneeco:v:144:y:2025:i:c:s0140988325001653. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    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.