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  • We utilize long-term memory, fractal dimension and approximate entropy as input variables for the Efficiency Index [Krištoufek&Vošvrda (2013), Physica A 392]. This way, we are able to comment on stock market efficiency after controlling for different types of inefficiencies. Applying the methodology on 38 stock market indices across the world, we find that the most efficient markets are situated in the Eurozone (the Netherlands, France and Germany) and the least efficient ones in the Latin America (Venezuela and Chile).
  • We utilize long-term memory, fractal dimension and approximate entropy as input variables for the Efficiency Index [Krištoufek&Vošvrda (2013), Physica A 392]. This way, we are able to comment on stock market efficiency after controlling for different types of inefficiencies. Applying the methodology on 38 stock market indices across the world, we find that the most efficient markets are situated in the Eurozone (the Netherlands, France and Germany) and the least efficient ones in the Latin America (Venezuela and Chile). (en)
Title
  • Measuring capital market efficiency: Long-term memory, fractal dimension and approximate entropy
  • Measuring capital market efficiency: Long-term memory, fractal dimension and approximate entropy (en)
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  • Measuring capital market efficiency: Long-term memory, fractal dimension and approximate entropy
  • Measuring capital market efficiency: Long-term memory, fractal dimension and approximate entropy (en)
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  • RIV/67985556:_____/13:00395886!RIV14-GA0-67985556
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  • I, P(GA402/09/0965)
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  • 86892
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  • RIV/67985556:_____/13:00395886
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  • capital market efficiency; long-range dependence; fractal dimension; approximate entropy (en)
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  • [9C32EEDF9F4B]
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  • Jihlava
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  • Jihlava
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  • Proceedings of the 31st International Conference Mathematical Methods in Economics 2013
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  • Vošvrda, Miloslav
  • Krištoufek, Ladislav
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  • College of Polytechnics Jihlava
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  • 978-80-87035-76-4
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