IDEAS home Printed from https://ideas.repec.org/a/fau/aucocz/au2010_330.html
   My bibliography  Save this article

Dynamics of Stock Market Correlations

Author

Listed:
  • 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)

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.

Suggested Citation

  • Dror Y. Kenett & Yoash Shapira & Asaf Madi & Sharron Bransburg-Zabary & Gitit Gur-Gershgoren & Eshel Ben-Jacob, 2010. "Dynamics of Stock Market Correlations," Czech Economic Review, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, vol. 4(3), pages 330-340, November.
    • Handle: RePEc:fau:aucocz:au2010_330
    as

    Download full text from publisher

    File URL: http://auco.cuni.cz/mag/article/download/id/97/type/attachment
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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. 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.
    4. Champagne, Claudia, 2014. "The international syndicated loan market network: An “unholy trinity”?," Global Finance Journal, Elsevier, vol. 25(2), pages 148-168.
    5. Jiang, Jiaqi & Gu, Rongbao, 2016. "Using Rényi parameter to improve the predictive power of singular value decomposition entropy on stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 448(C), pages 254-264.
    6. Gautier Marti & Frank Nielsen & Miko{l}aj Bi'nkowski & Philippe Donnat, 2017. "A review of two decades of correlations, hierarchies, networks and clustering in financial markets," Papers 1703.00485, arXiv.org, revised Nov 2020.
    7. Dror Y Kenett & Matthias Raddant & Thomas Lux & Eshel Ben-Jacob, 2012. "Evolvement of Uniformity and Volatility in the Stressed Global Financial Village," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-8, February.
    8. Lei Tan & Bo Zheng & Jun-Jie Chen & Xiong-Fei Jiang, 2015. "How Volatilities Nonlocal in Time Affect the Price Dynamics in Complex Financial Systems," PLOS ONE, Public Library of Science, vol. 10(2), pages 1-16, February.
    9. Andrey Kudryavtsev & Gil Cohen & Julia Pavlodsky, 2012. "Incorporating Weekend Information in Stock Prices: Evidence from Israeli Stock Market," Journal of Finance and Investment Analysis, SCIENPRESS Ltd, vol. 1(4), pages 1-1.
    10. Irena Vodenska & Alexander P. Becker & Di Zhou & Dror Y. Kenett & H. Eugene Stanley & Shlomo Havlin, 2016. "Community Analysis of Global Financial Markets," Risks, MDPI, vol. 4(2), pages 1-15, May.
    11. Jianrong Wei & Jiping Huang, 2012. "An Exotic Long-Term Pattern in Stock Price Dynamics," PLOS ONE, Public Library of Science, vol. 7(12), pages 1-5, December.
    12. Kocheturov, A. & Batsyn, M. & Pardalos, P., 2015. "Dynamics of Cluster Structures in Stock Market Networks," Journal of the New Economic Association, New Economic Association, vol. 28(4), pages 12-30.
    13. Leonidas Sandoval Junior, 2011. "Pruning a Minimum Spanning Tree," Papers 1109.0642, arXiv.org.
    14. Vishwas Kukreti & Hirdesh K. Pharasi & Priya Gupta & Sunil Kumar, 2020. "A perspective on correlation-based financial networks and entropy measures," Papers 2004.09448, arXiv.org.
    15. Stosic, Darko & Stosic, Dusan & Ludermir, Teresa & Stosic, Tatijana, 2016. "Correlations of multiscale entropy in the FX market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 52-61.
    16. Dror Y Kenett & Yoash Shapira & Asaf Madi & Sharron Bransburg-Zabary & Gitit Gur-Gershgoren & Eshel Ben-Jacob, 2011. "Index Cohesive Force Analysis Reveals That the US Market Became Prone to Systemic Collapses Since 2002," PLOS ONE, Public Library of Science, vol. 6(4), pages 1-8, April.

    More about this item

    Keywords

    Correlation; Stock Market Holography; eigenvalue entropy; sliding window;
    All these keywords.

    JEL classification:

    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:fau:aucocz:au2010_330. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Lenka Stastna (email available below). General contact details of provider: https://edirc.repec.org/data/icunicz.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.