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Algorithmic complexity theory and the relative efficiency of financial markets - Updated

Author

Listed:
  • Giglio, Ricardo
  • Matsushita, Raul
  • Figueiredo, Annibal
  • Gleria, Iram
  • Da Silva, Sergio

Abstract

Financial economists usually assess market efficiency in absolute terms. This is to be viewed as a shortcoming. One way of dealing with the relative efficiency of markets is to resort to the efficiency interpretation provided by algorithmic complexity theory. We employ such an approach in order to rank 36 stock exchanges and 20 US dollar exchange rates in terms of their relative efficiency.

Suggested Citation

  • Giglio, Ricardo & Matsushita, Raul & Figueiredo, Annibal & Gleria, Iram & Da Silva, Sergio, 2008. "Algorithmic complexity theory and the relative efficiency of financial markets - Updated," MPRA Paper 11150, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:11150
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    File URL: https://mpra.ub.uni-muenchen.de/11150/1/MPRA_paper_11150.pdf
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    References listed on IDEAS

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    1. repec:hrv:faseco:33077889 is not listed on IDEAS
    2. Ronaldo Seroa da Motta & Ajax R.B. Moreira, 2004. "Efficiency and Regulation in the Sanitation Sector in Brazil," Discussion Papers 1059, Instituto de Pesquisa Econômica Aplicada - IPEA.
    3. Andrei Shleifer, 1998. "State versus Private Ownership," Journal of Economic Perspectives, American Economic Association, vol. 12(4), pages 133-150, Fall.
    4. Sebastian Galiani & Paul Gertler & Ernesto Schargrodsky, 2005. "Water for Life: The Impact of the Privatization of Water Services on Child Mortality," Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 83-120, February.
    5. Seroa da Motta, Ronaldo & Moreira, Ajax, 2006. "Efficiency and regulation in the sanitation sector in Brazil," Utilities Policy, Elsevier, vol. 14(3), pages 185-195, September.
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    Cited by:

    1. Cristescu, C.P. & Stan, C. & Scarlat, E.I., 2009. "The dynamics of exchange rate time series and the chaos game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(23), pages 4845-4855.
    2. Alvarez-Ramirez, J. & Rodriguez, E. & Espinosa-Paredes, G., 2012. "A partisan effect in the efficiency of the US stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(20), pages 4923-4932.
    3. Da Silva, Sergio, 2015. "Financial Market Efficiency Should be Gauged in Relative Rather than Absolute Terms," MPRA Paper 64497, University Library of Munich, Germany.
    4. Lucio Maria Calcagnile & Fulvio Corsi & Stefano Marmi, 2016. "Entropy and efficiency of the ETF market," Papers 1609.04199, arXiv.org.
    5. Zunino, Luciano & Zanin, Massimiliano & Tabak, Benjamin M. & Pérez, Darío G. & Rosso, Osvaldo A., 2010. "Complexity-entropy causality plane: A useful approach to quantify the stock market inefficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(9), pages 1891-1901.

    More about this item

    Keywords

    financial market efficiency; algorithmic complexity theory;

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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