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Measuring long-range dependence in electricity prices

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  • Rafal Weron

Abstract

The price of electricity is far more volatile than that of other commodities normally noted for extreme volatility. The possibility of extreme price movements increases the risk of trading in electricity markets. However, underlying the process of price returns is a strong mean-reverting mechanism. We study this feature of electricity returns by means of Hurst R/S analysis, Detrended Fluctuation Analysis and periodogram regression.

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File URL: http://arxiv.org/pdf/cond-mat/0103621
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Bibliographic Info

Paper provided by arXiv.org in its series Papers with number cond-mat/0103621.

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Date of creation: Mar 2001
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Publication status: Published in in H. Takayasu ed., "Empirical Science of Financial Fluctuations" (Springer-Verlag Tokyo, 2002), pp. 110-119
Handle: RePEc:arx:papers:cond-mat/0103621

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References

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  1. Lobato, Ignacio N & Savin, N E, 1998. "Real and Spurious Long-Memory Properties of Stock-Market Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(3), pages 261-68, July.
  2. Rafal Weron & Beata Przybylowicz, 2000. "Hurst analysis of electricity price dynamics," HSC Research Reports HSC/00/01, Hugo Steinhaus Center, Wroclaw University of Technology.
  3. Richard B. Olsen & Ulrich A. Müller & Michel M. Dacorogna & Olivier V. Pictet & Rakhal R. Davé & Dominique M. Guillaume, 1997. "From the bird's eye to the microscope: A survey of new stylized facts of the intra-daily foreign exchange markets (*)," Finance and Stochastics, Springer, vol. 1(2), pages 95-129.
  4. Rafal Weron, 2000. "Energy price risk management," HSC Research Reports HSC/00/02, Hugo Steinhaus Center, Wroclaw University of Technology.
  5. Thomas Lux, 1996. "Long-term stochastic dependence in financial prices: evidence from the German stock market," Applied Economics Letters, Taylor & Francis Journals, vol. 3(11), pages 701-706.
  6. Rafal Weron, 2001. "Estimating long range dependence: finite sample properties and confidence intervals," HSC Research Reports HSC/01/03, Hugo Steinhaus Center, Wroclaw University of Technology.
  7. Weron, R. & Kozłowska, B. & Nowicka-Zagrajek, J., 2001. "Modeling electricity loads in California: a continuous-time approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(1), pages 344-350.
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Citations

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Cited by:
  1. Josep Perello & Miquel Montero & Luigi Palatella & Ingve Simonsen & Jaume Masoliver, 2006. "Entropy of the Nordic electricity market: anomalous scaling, spikes, and mean-reversion," Papers physics/0609066, arXiv.org.
  2. Trinidad Segovia, J.E. & Fernández-Martínez, M. & Sánchez-Granero, M.A., 2012. "A note on geometric method-based procedures to calculate the Hurst exponent," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(6), pages 2209-2214.
  3. Rafal Weron, 2005. "Market price of risk implied by Asian-style electricity options," Econometrics 0502003, EconWPA.
  4. Ladislav KRISTOUFEK & Petra LUNACKOVA, 2013. "Long-term Memory in Electricity Prices: Czech Market Evidence," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(5), pages 407-424, November.
  5. Ladislav Krištoufek, 2010. "Long-Term Memory and Its Evolution in Returns of Stock Index PX Between 1997 and 2009," Politická ekonomie, University of Economics, Prague, vol. 2010(4), pages 471-487.
  6. Majumder, Debasish, 2012. "When the market becomes inefficient: Comparing BRIC markets with markets in the USA," International Review of Financial Analysis, Elsevier, vol. 24(C), pages 84-92.
  7. Sánchez Granero, M.A. & Trinidad Segovia, J.E. & García Pérez, J., 2008. "Some comments on Hurst exponent and the long memory processes on capital markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(22), pages 5543-5551.

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