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Dynamics of Stock Market Correlations

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  • Dror Y. Kenett

    (Tel-Aviv University, School of Physics and Astronomy, The Raymond and Beverly Sackler Faculty of Exact Sciences, Tel-Aviv, Israel)

  • Yoash Shapira

    (Tel-Aviv University, School of Physics and Astronomy, The Raymond and Beverly Sackler Faculty of Exact Sciences, Tel-Aviv, Israel)

  • Asaf Madi

    (Tel Aviv University, Faculty of Medicine, Tel Aviv, Israel)

  • Sharron Bransburg-Zabary

    (Tel Aviv University, Faculty of Medicine, Tel Aviv, Israel)

  • Gitit Gur-Gershgoren

    (Israel Securities Authority, Jerusalem, Israel
    Ben Gurion University, School of Business and Management, Beer Sheva, Israel)

  • Eshel Ben-Jacob

    ()
    (Tel-Aviv University, School of Physics and Astronomy, The Raymond and Beverly Sackler Faculty of Exact Sciences, Tel-Aviv, Israel)

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    Abstract

    We present a novel approach to the study the dynamics of stock market correlations. This is achieved through an innovative visualization tool that allows an investigation of the structure and dynamics of the market, through the study of correlations. This is based on the Stock Market Holography (SMH) method recently introduced. This qualitative measure is complemented by the use of the eigenvalue entropy measure, to quantify how the information in the market changes in time. Using this innovative approach, we analyzed data from the New York Stock Exchange (NYSE), and the Tel Aviv Stock Exchange (TASE), for daily trading data for the time period of 2000–2009. This paper covers these new concepts for the study of financial markets in terms of structure and information as reflected by the changes in correlations over time.

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    Bibliographic Info

    Article provided by Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies in its journal AUCO Czech Economic Review.

    Volume (Year): 4 (2010)
    Issue (Month): 3 (November)
    Pages: 330-340

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    Handle: RePEc:fau:aucocz:au2010_330

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    Related research

    Keywords: Correlation; Stock Market Holography; eigenvalue entropy; sliding window;

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    Cited by:
    1. Sandoval, Leonidas, 2012. "Pruning a minimum spanning tree," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(8), pages 2678-2711.
    2. Leonidas Sandoval Junior, 2011. "Cluster formation and evolution in networks of financial market indices," Papers 1111.5069, arXiv.org.
    3. Leonidas Sandoval Junior, 2011. "Pruning a Minimum Spanning Tree," Papers 1109.0642, arXiv.org.
    4. Dror Y. Kenett & Matthias Raddant & Thomas Lux & Eshel Ben-Jacob, 2011. "Evolvement of uniformity and volatility in the stressed global financial village," Kiel Working Papers 1739, Kiel Institute for the World Economy.
    5. Caraiani, Petre, 2014. "The predictive power of singular value decomposition entropy for stock market dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 393(C), pages 571-578.

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