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Measuring capital market efficiency: Global and local correlations structure

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  • Kristoufek, Ladislav
  • Vosvrda, Miloslav

Abstract

We introduce a new measure for capital market efficiency. The measure takes into consideration the correlation structure of the returns (long-term and short-term memory) and local herding behavior (fractal dimension). The efficiency measure is taken as a distance from an ideal efficient market situation. The proposed methodology is applied to a portfolio of 41 stock indices. We find that the Japanese NIKKEI is the most efficient market. From a geographical point of view, the more efficient markets are dominated by the European stock indices and the less efficient markets cover mainly Latin America, Asia and Oceania. The inefficiency is mainly driven by a local herding, i.e. a low fractal dimension.

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Bibliographic Info

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

Volume (Year): 392 (2013)
Issue (Month): 1 ()
Pages: 184-193

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Handle: RePEc:eee:phsmap:v:392:y:2013:i:1:p:184-193

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

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Keywords: Capital market efficiency; Long-range dependence; Short-range dependence; Fractal dimension;

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References

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Citations

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Cited by:
  1. Ladislav Kristoufek & Miloslav Vosvrda, 2013. "Measuring capital market efficiency: Long-term memory, fractal dimension and approximate entropy," Papers 1307.3060, arXiv.org, revised May 2014.
  2. Todea, Alexandru & Pleşoianu, Anita, 2013. "The influence of foreign portfolio investment on informational efficiency: Empirical evidence from Central and Eastern European stock markets," Economic Modelling, Elsevier, vol. 33(C), pages 34-41.
  3. Ladislav Kristoufek & Miloslav Vosvrda, 2013. "Commodity futures and market efficiency," Papers 1309.1492, arXiv.org.
  4. Rui Pascoal & Ana Margarida Monteiro, 2013. "Market Efficiency, Roughness and Long Memory in the PSI20 Index Returns: Wavelet and Entropy Analysis," GEMF Working Papers 2013-27, GEMF - Faculdade de Economia, Universidade de Coimbra.

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