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Quantifying multiscale inefficiency in electricity markets

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  • Uritskaya, Olga Y.
  • Serletis, Apostolos

Abstract

One of the basic features of efficient markets is the absence of correlations between price increments over any time scale leading to random walk-type behavior of prices. In this paper, we propose a new approach for measuring deviations from the efficient market state based on an analysis of scale-dependent fractal exponent characterizing correlations at different time scales. The approach is applied to two electricity markets, Alberta and Mid Columbia (Mid-C), as well as to the AECO Alberta natural gas market (for purposes of providing a comparison between storable and non-storable commodities). We show that price fluctuations in all studied markets are not efficient, with electricity prices exhibiting complex multiscale correlated behavior not captured by monofractal methods used in previous studies.

Suggested Citation

  • Uritskaya, Olga Y. & Serletis, Apostolos, 2008. "Quantifying multiscale inefficiency in electricity markets," Energy Economics, Elsevier, vol. 30(6), pages 3109-3117, November.
    • Handle: RePEc:eee:eneeco:v:30:y:2008:i:6:p:3109-3117
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    References listed on IDEAS

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    1. Stanley, H.E. & Amaral, L.A.N. & Goldberger, A.L. & Havlin, S. & Ivanov, P.Ch. & Peng, C.-K., 1999. "Statistical physics and physiology: Monofractal and multifractal approaches," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 270(1), pages 309-324.
    2. Apostolos Serletis & Ricardo Rangel-Ruiz, 2007. "Testing for Common Features in North American Energy Markets," World Scientific Book Chapters, in: Quantitative And Empirical Analysis Of Energy Markets, chapter 14, pages 172-187, World Scientific Publishing Co. Pte. Ltd..
    3. Serletis, Apostolos & Rosenberg, Aryeh Adam, 2007. "The Hurst exponent in energy futures prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 380(C), pages 325-332.
    4. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    5. repec:clg:wpaper:2007-02 is not listed on IDEAS
    6. Apostolos Serletis, 2007. "Quantitative and Empirical Analysis of Energy Markets," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 6352, August.
    7. Apostolos Serletis & Mattia Bianchi, 2007. "Informational Efficiency and Interchange Transactions in Alberta's Electricity Market," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 121-144.
    8. Costa, Rogério L. & Vasconcelos, G.L., 2003. "Long-range correlations and nonstationarity in the Brazilian stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 329(1), pages 231-248.
    9. R. L. Costa & G. L. Vasconcelos, 2003. "Long-range correlations and nonstationarity in the Brazilian stock market," Papers cond-mat/0302342, arXiv.org.
    10. Moulton, Jonathan S., 2005. "California electricity futures: the NYMEX experience," Energy Economics, Elsevier, vol. 27(1), pages 181-194, January.
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    4. Afanasyev, D. & Fedorova, E., 2018. "External and Internal Determinants on the Electricity Market: A Multi-Scale Adaptive Causal Analysis," Journal of the New Economic Association, New Economic Association, vol. 39(3), pages 33-54.
    5. Aurelio F. Bariviera & Luciano Zunino & M. Belen Guercio & Lisana B. Martinez & Osvaldo A. Rosso, 2015. "Efficiency and credit ratings: a permutation-information-theory analysis," Papers 1509.01839, arXiv.org.
    6. Olga Y. Uritskaya & Vadim M. Uritsky, 2015. "Predictability of price movements in deregulated electricity markets," Papers 1505.08117, arXiv.org.
    7. Wang, Yudong & Wei, Yu & Wu, Chongfeng, 2010. "Auto-correlated behavior of WTI crude oil volatilities: A multiscale perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(24), pages 5759-5768.
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    9. 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.
    10. Alvarez-Ramirez, Jose & Escarela-Perez, Rafael, 2010. "Time-dependent correlations in electricity markets," Energy Economics, Elsevier, vol. 32(2), pages 269-277, March.
    11. Uritskaya, Olga Y. & Uritsky, Vadim M., 2015. "Predictability of price movements in deregulated electricity markets," Energy Economics, Elsevier, vol. 49(C), pages 72-81.
    12. George P. Papaioannou & Christos Dikaiakos & Akylas C. Stratigakos & Panos C. Papageorgiou & Konstantinos F. Krommydas, 2019. "Testing the Efficiency of Electricity Markets Using a New Composite Measure Based on Nonlinear TS Tools," Energies, MDPI, vol. 12(4), pages 1-30, February.
    13. Dmitriy O. Afanasyev & Elena A. Fedorova & Evgeniy V. Gilenko, 2021. "The fundamental drivers of electricity price: a multi-scale adaptive regression analysis," Empirical Economics, Springer, vol. 60(4), pages 1913-1938, April.
    14. Wang, Yudong & Liu, Li, 2010. "Is WTI crude oil market becoming weakly efficient over time?: New evidence from multiscale analysis based on detrended fluctuation analysis," Energy Economics, Elsevier, vol. 32(5), pages 987-992, September.
    15. Wang, Fang & Liao, Gui-ping & Li, Jian-hui & Li, Xiao-chun & Zhou, Tie-jun, 2013. "Multifractal detrended fluctuation analysis for clustering structures of electricity price periods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(22), pages 5723-5734.
    16. Engelen, Steve & Norouzzadeh, Payam & Dullaert, Wout & Rahmani, Bahareh, 2011. "Multifractal features of spot rates in the Liquid Petroleum Gas shipping market," Energy Economics, Elsevier, vol. 33(1), pages 88-98, January.
    17. Avci-Surucu, Ezgi & Aydogan, A. Kursat & Akgul, Doganbey, 2016. "Bidding structure, market efficiency and persistence in a multi-time tariff setting," Energy Economics, Elsevier, vol. 54(C), pages 77-87.
    18. Serinaldi, Francesco, 2010. "Use and misuse of some Hurst parameter estimators applied to stationary and non-stationary financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(14), pages 2770-2781.
    19. Alvarez-Ramirez, J. & Escarela-Perez, R. & Espinosa-Perez, G. & Urrea, R., 2009. "Dynamics of electricity market correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(11), pages 2173-2188.
    20. Liu, Li & Wang, Yudong & Wan, Jieqiu, 2010. "Analysis of efficiency for Shenzhen stock market: Evidence from the source of multifractality," International Review of Financial Analysis, Elsevier, vol. 19(4), pages 237-241, September.

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