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Increasing market efficiency in the stock markets

Author

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  • Jae-Suk Yang
  • Wooseop Kwak
  • Taisei Kaizoji
  • In-mook Kim

Abstract

We study the temporal evolutions of three stock markets; Standard and Poor's 500 index, Nikkei 225 Stock Average, and the Korea Composite Stock Price Index. We observe that the probability density function of the log-return has a fat tail but the tail index has been increasing continuously in recent years. We have also found that the variance of the autocorrelation function, the scaling exponent of the standard deviation, and the statistical complexity decrease, but that the entropy density increases as time goes over time. We introduce a modified microscopic spin model and simulate the model to confirm such increasing and decreasing tendencies in statistical quantities. These findings indicate that these three stock markets are becoming more efficient. Copyright EDP Sciences/Società Italiana di Fisica/Springer-Verlag 2008

Suggested Citation

  • Jae-Suk Yang & Wooseop Kwak & Taisei Kaizoji & In-mook Kim, 2008. "Increasing market efficiency in the stock markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 61(2), pages 241-246, January.
    • Handle: RePEc:spr:eurphb:v:61:y:2008:i:2:p:241-246
    DOI: 10.1140/epjb/e2008-00050-0
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    Cited by:

    1. Kantar, Ersin & Keskin, Mustafa, 2013. "The relationships between electricity consumption and GDP in Asian countries, using hierarchical structure methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(22), pages 5678-5684.
    2. Oh, Gabjin & Kim, Ho-yong & Ahn, Seok-Won & Kwak, Wooseop, 2015. "Analyzing the financial crisis using the entropy density function," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 464-469.
    3. Taisei Kaizoji, 2010. "Stock volatility in the periods of booms and stagnations," EERI Research Paper Series EERI_RP_2010_07, Economics and Econometrics Research Institute (EERI), Brussels.
    4. Campos Dias de Sousa, Ricardo Emanuel & Howden, David, 2015. "The Efficient Market Conjecture," MPRA Paper 79792, University Library of Munich, Germany.
    5. Xu, Meng & Shang, Pengjian, 2018. "Analysis of financial time series using multiscale entropy based on skewness and kurtosis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1543-1550.
    6. Minsung Kim & Minki Kim, 2014. "Group-Wise Herding Behavior in Financial Markets: An Agent-Based Modeling Approach," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-7, April.
    7. Park, Sangjin & Jang, Kwahngsoo & Yang, Jae-Suk, 2021. "Information flow between bitcoin and other financial assets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    8. Preuss, Björn, 2019. "Equity fund managements promise and action: A comparative study of Nordic and US fund’s," Journal of Behavioral and Experimental Finance, Elsevier, vol. 23(C), pages 84-89.

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