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Systematic Features of High-Frequency Volatility in Australian Electricity Markets: Intraday Patterns, Information Arrival and Calendar Effects


  • Helen Higgs
  • Andrew C. Worthington


This paper investigates the intraday price volatility process in four Australian wholesale electricity markets; namely New South Wales, Queensland, South Australia and Victoria. The data set consists of half-hourly electricity prices and demand volumes over the period January 1, 2002 to June 1, 2003. A range of processes including GARCH, RiskMetrics, normal Asymmetric Power ARCH or APARCH, Student APARCH and skewed Student APARCH are used to model the time-varying variance in prices and the inclusion of news arrival as proxied by the contemporaneous volume of demand, time-of-day, day-of-week and month-of-year effects as exogenous explanatory variables. The skewed Student APARCH model, which takes account of right skewed and fat tailed characteristics, produces the best results in all four markets. The results indicate significant innovation (ARCH effects) and volatility (GARCH effects) spillovers in the conditional standard deviation equation, even with market and calendar effects included. Intraday prices also exhibit significant asymmetric responses of volatility to the flow of information.

Suggested Citation

  • Helen Higgs & Andrew C. Worthington, 2005. "Systematic Features of High-Frequency Volatility in Australian Electricity Markets: Intraday Patterns, Information Arrival and Calendar Effects," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 23-42.
  • Handle: RePEc:aen:journl:2005v26-04-a02

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    Cited by:

    1. Haugom, Erik & Ullrich, Carl J., 2012. "Forecasting spot price volatility using the short-term forward curve," Energy Economics, Elsevier, vol. 34(6), pages 1826-1833.
    2. Higgs, Helen & Lien, Gudbrand & Worthington, Andrew C., 2015. "Australian evidence on the role of interregional flows, production capacity, and generation mix in wholesale electricity prices and price volatility," Economic Analysis and Policy, Elsevier, vol. 48(C), pages 172-181.
    3. Wild, Phillip & Hinich, Melvin J. & Foster, John, 2010. "Are daily and weekly load and spot price dynamics in Australia's National Electricity Market governed by episodic nonlinearity?," Energy Economics, Elsevier, vol. 32(5), pages 1082-1091, September.
    4. Herrera, Rodrigo & González, Nicolás, 2014. "The modeling and forecasting of extreme events in electricity spot markets," International Journal of Forecasting, Elsevier, vol. 30(3), pages 477-490.
    5. Mawuli Segnon & Chi Keung Lau & Bernd Wilfling & Rangan Gupta, 2017. "Are multifractal processes suited to forecasting electricity price volatility? Evidence from Australian intraday data," CQE Working Papers 6117, Center for Quantitative Economics (CQE), University of Muenster.
    6. Kalantzis, Fotis G. & Milonas, Nikolaos T., 2013. "Analyzing the impact of futures trading on spot price volatility: Evidence from the spot electricity market in France and Germany," Energy Economics, Elsevier, vol. 36(C), pages 454-463.
    7. Stuart Thomas & Vikash Ramiah & Heather Mitchell & Richard Heaney, 2011. "Seasonal factors and outlier effects in rate of return on electricity spot prices in Australia's National Electricity Market," Applied Economics, Taylor & Francis Journals, vol. 43(3), pages 355-369.
    8. Ullrich, Carl J., 2012. "Realized volatility and price spikes in electricity markets: The importance of observation frequency," Energy Economics, Elsevier, vol. 34(6), pages 1809-1818.
    9. Erdogdu, Erkan, 2016. "Asymmetric volatility in European day-ahead power markets: A comparative microeconomic analysis," Energy Economics, Elsevier, vol. 56(C), pages 398-409.
    10. Sinha, Pankaj & Mathur, Kritika, 2016. "Empirical Analysis of Developments in the Day Ahead Electricity Markets in India," MPRA Paper 72969, University Library of Munich, Germany.
    11. Wang, Tao & Yang, Jian, 2010. "Nonlinearity and intraday efficiency tests on energy futures markets," Energy Economics, Elsevier, vol. 32(2), pages 496-503, March.
    12. Haugom, Erik & Westgaard, Sjur & Solibakke, Per Bjarte & Lien, Gudbrand, 2011. "Realized volatility and the influence of market measures on predictability: Analysis of Nord Pool forward electricity data," Energy Economics, Elsevier, vol. 33(6), pages 1206-1215.
    13. Hickey, Emily & Loomis, David G. & Mohammadi, Hassan, 2012. "Forecasting hourly electricity prices using ARMAX–GARCH models: An application to MISO hubs," Energy Economics, Elsevier, vol. 34(1), pages 307-315.
    14. 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.
    15. 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.
    16. Montero, José M. & García-Centeno, Maria C. & Fernández-Avilés, Gema, 2011. "Modelling the Volatility of the Spanish Wholesale Electricity Spot Market. Asymmetric GARCH Models vs. Threshold ARSV model/Modelización de la volatilidad en el mercado eléctrico español. Modelos GARC," Estudios de Economía Aplicada, Estudios de Economía Aplicada, vol. 29, pages 597-616, Agosto.
    17. Lilian de Menezes & Melanie A. Houllier, 2013. "Modelling Germany´s Energy Transition and its Potential Effect on European Electricity Spot Markets," EcoMod2013 5395, EcoMod.
    18. Hadsell, Lester, 2007. "The impact of virtual bidding on price volatility in New York's wholesale electricity market," Economics Letters, Elsevier, vol. 95(1), pages 66-72, April.
    19. Frömmel, Michael & Han, Xing & Kratochvil, Stepan, 2014. "Modeling the daily electricity price volatility with realized measures," Energy Economics, Elsevier, vol. 44(C), pages 492-502.

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    JEL classification:

    • F0 - International Economics - - General


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