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Some statistical investigations on the nature and dynamics of electricity prices

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Author Info

  • Bottazzi, G.
  • Sapio, S.
  • Secchi, A.

Abstract

This work analyzes the log-returns of daily electricity prices from the NordPool day-ahead market. We study both the unconditional growth rates distribution and the distribution of residual shocks obtained with a non-parametric filtering procedure based on the Cholesky factor algorithm. We show that, even if the Subbotin family of distributions is able to describe the empirical observations in both cases, the Subbotin fit obtained for the unconditional growth rates and for the residual shocks reveal significant differences. Indeed, the sequence of log-returns can be described as the outcome of an aggregation of Laplace-distributed shocks with time-dependent volatility. We find that the standard deviation of shocks scales as a power law of the initial price level, with scaling exponent around -1. Moreover, the analysis of the empirical density of shocks, conditional on the price level, shows a strong relationship of the Subbotin fit with the latter. We conclude that the unconditional growth rates distribution is the superposition of shocks distributions characterized by decreasing volatility and fat-tailedness with respect to the price level.

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Bibliographic Info

Article provided by Elsevier in its journal Physica A: Statistical Mechanics and its Applications.

Volume (Year): 355 (2005)
Issue (Month): 1 ()
Pages: 54-61

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Handle: RePEc:eee:phsmap:v:355:y:2005:i:1:p:54-61

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Web page: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/

Related research

Keywords: Electricity markets; Subbotin distribution; Laplace distribution; Scaling;

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References

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Citations

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Cited by:
  1. Joachim Kaldasch, 2013. "Evolutionary Model of a Anonymous Consumer Durable Market," Papers 1306.3395, arXiv.org.
  2. Kaldasch, Joachim, 2012. "Evolutionary model of the growth and size of firms," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(14), pages 3751-3769.
  3. Joachim Kaldasch, 2012. "Evolutionäre Diffusion und der Produktlebenszyklus von Gebrauchsgütern," EconStor Preprints 59748, ZBW - German National Library of Economics.
  4. Weron, Rafal, 2009. "Forecasting wholesale electricity prices: A review of time series models," MPRA Paper 21299, University Library of Munich, Germany.
  5. Sandro Sapio, 2006. "An Empirically Based Model of the Supply Schedule in Day-Ahead Electricity Markets," LEM Papers Series 2006/12, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  6. Kaldasch, Joachim, 2011. "Evolutionary Model of Non-Durable Markets," EconStor Preprints 50531, ZBW - German National Library of Economics.
  7. Matteo Manera & Massimiliano Serati & Michele Plotegher, 2008. "Modeling Electricity Prices: From the State of the Art to a Draft of a New Proposal," Working Papers 2008.9, Fondazione Eni Enrico Mattei.
  8. Andrea Petrella & Sandro Sapio, 2010. "No PUN intended: A time series analysis of the Italian day-ahead electricity prices," RSCAS Working Papers 2010/03, European University Institute.
  9. Tomasz Kozubowski & Saralees Nadarajah, 2010. "Multitude of Laplace distributions," Statistical Papers, Springer, vol. 51(1), pages 127-148, January.
  10. Weron, Rafal & Misiorek, Adam, 2007. "Heavy tails and electricity prices: Do time series models with non-Gaussian noise forecast better than their Gaussian counterparts?," MPRA Paper 2292, University Library of Munich, Germany, revised Oct 2007.

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