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Modelling Spikes in Electricity Prices

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  • 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. Copyright © 2007 The Economic Society of Australia.

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Bibliographic Info

Article provided by The Economic Society of Australia in its journal Economic Record.

Volume (Year): 83 (2007)
Issue (Month): 263 (December)
Pages: 371-382

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Handle: RePEc:bla:ecorec:v:83:y:2007:i:263:p:371-382

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Citations

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Cited by:
  1. A S Hurn & Annastiina Silvennoinen & Timo Terasvirta, 2014. "A Smooth Transition Logit Model of the Effects of Deregulation in the Electricity Market," NCER Working Paper Series 100, National Centre for Econometric Research.
  2. 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.
  3. 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.
  4. Timothy Christensen & Stan Hurn & Kenneth Lindsay, 2009. "It Never Rains but it Pours: Modeling the Persistence of Spikes in Electricity Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 25-48.
  5. Rangga Handika & Chi Truong & Stefan Trueck & Rafal Weron, 2014. "Modelling price spikes in electricity markets - the impact of load, weather and capacity," HSC Research Reports HSC/14/08, Hugo Steinhaus Center, Wroclaw University of Technology.
  6. 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.
  7. 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.
  8. Volodymyr Korniichuk, 2012. "Forecasting extreme electricity spot prices," Cologne Graduate School Working Paper Series 03-14, Cologne Graduate School in Management, Economics and Social Sciences.
  9. Sergey Voronin & Jarmo Partanen, 2013. "Price Forecasting in the Day-Ahead Energy Market by an Iterative Method with Separate Normal Price and Price Spike Frameworks," Energies, MDPI, Open Access Journal, vol. 6(11), pages 5897-5920, November.
  10. Joanna Janczura, 2014. "Pricing electricity derivatives within a Markov regime-switching model: a risk premium approach," Computational Statistics, Springer, vol. 79(1), pages 1-30, February.
  11. Christensen, T.M. & Hurn, A.S. & Lindsay, K.A., 2012. "Forecasting spikes in electricity prices," International Journal of Forecasting, Elsevier, vol. 28(2), pages 400-411.
  12. 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.

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