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A GARCH Model to Understand the Volatility of the Electricity Spot Price in Brazil

Author

Listed:
  • André Luis da Silva Leite

    (Federal University of Santa Catarina, Brazil.)

  • Marcus Vinicius Andrade de Lima

    (Federal University of Santa Catarina, Brazil.)

Abstract

Electricity is sensitive to extreme price events and spot price volatility is an inherent characteristic of competitive electricity markets. The purpose of this article it to model the realized volatility of electricity spot price in Brazil. The Brazilian electricity industry presents unique characteristics and because of this price varies a lot in a short period. So, we developed a GARCH model using 862 weekly observations to understand the realized volatility in the four different market. We conclude that the spot price in Brazil presents high volatility that presents risk to agents. This high volatility is associated with institutional factors and the increase in the share of renewable energy in the electricity mix.

Suggested Citation

  • André Luis da Silva Leite & Marcus Vinicius Andrade de Lima, 2023. "A GARCH Model to Understand the Volatility of the Electricity Spot Price in Brazil," International Journal of Energy Economics and Policy, Econjournals, vol. 13(5), pages 332-338, September.
  • Handle: RePEc:eco:journ2:2023-05-38
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    References listed on IDEAS

    as
    1. Crespo Cuaresma, Jesús & Hlouskova, Jaroslava & Kossmeier, Stephan & Obersteiner, Michael, 2004. "Forecasting electricity spot-prices using linear univariate time-series models," Applied Energy, Elsevier, vol. 77(1), pages 87-106, January.
    2. Vahl, Fabrício Peter & Rüther, Ricardo & Casarotto Filho, Nelson, 2013. "The influence of distributed generation penetration levels on energy markets," Energy Policy, Elsevier, vol. 62(C), pages 226-235.
    3. repec:aen:journl:1995v16-03-a02 is not listed on IDEAS
    4. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    5. Worthington, Andrew & Kay-Spratley, Adam & Higgs, Helen, 2005. "Transmission of prices and price volatility in Australian electricity spot markets: a multivariate GARCH analysis," Energy Economics, Elsevier, vol. 27(2), pages 337-350, March.
    6. Tashpulatov, Sherzod N., 2013. "Estimating the volatility of electricity prices: The case of the England and Wales wholesale electricity market," Energy Policy, Elsevier, vol. 60(C), pages 81-90.
    7. Zareipour, Hamidreza & Bhattacharya, Kankar & Canizares, Claudio A., 2007. "Electricity market price volatility: The case of Ontario," Energy Policy, Elsevier, vol. 35(9), pages 4739-4748, September.
    8. Helen Higgs, 2009. "Modelling price and volatility inter-relationships in the Australian wholesale spot electricity markets," Discussion Papers in Economics economics:200904, Griffith University, Department of Accounting, Finance and Economics.
    9. Sadorsky, Perry, 2012. "Correlations and volatility spillovers between oil prices and the stock prices of clean energy and technology companies," Energy Economics, Elsevier, vol. 34(1), pages 248-255.
    10. repec:aen:journl:2004v25-04-a02 is not listed on IDEAS
    11. Li, Ying & Flynn, Peter C., 2004. "Deregulated power prices: comparison of diurnal patterns," Energy Policy, Elsevier, vol. 32(5), pages 657-672, March.
    12. Qu, Hui & Duan, Qingling & Niu, Mengyi, 2018. "Modeling the volatility of realized volatility to improve volatility forecasts in electricity markets," Energy Economics, Elsevier, vol. 74(C), pages 767-776.
    13. Ferreira, Pedro Guilherme Costa & Oliveira, Fernando Luiz Cyrino & Souza, Reinaldo Castro, 2015. "The stochastic effects on the Brazilian Electrical Sector," Energy Economics, Elsevier, vol. 49(C), pages 328-335.
    14. Higgs, Helen, 2009. "Modelling price and volatility inter-relationships in the Australian wholesale spot electricity markets," Energy Economics, Elsevier, vol. 31(5), pages 748-756, September.
    15. Robert Engle, 2001. "GARCH 101: The Use of ARCH/GARCH Models in Applied Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 157-168, Fall.
    16. Dalbem, Marta Corrêa & Brandão, Luiz Eduardo Teixeira & Gomes, Leonardo Lima, 2014. "Can the regulated market help foster a free market for wind energy in Brazil?," Energy Policy, Elsevier, vol. 66(C), pages 303-311.
    17. 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.
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    Keywords

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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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