IDEAS home Printed from https://ideas.repec.org/a/eee/finana/v20y2011i1p1-5.html
   My bibliography  Save this article

Characteristics of the Polish Stock Market correlations

Author

Listed:
  • Galazka, Marek

Abstract

In this paper a network structure of the Polish Stock Market (PSM), one of the emerging markets, is studied. The conceptions: Minimum Spanning Tree (MST) and Weighted Random Graph (WRG), constructed among companies listed on this stock exchange, are compared. In these models denote each vertex a stock and the weight assigned to each edge in WRG is the cross-correlation coefficients. The Influence-Strength (IS) is at each vertex in both models defined: in WRG as the sum of the weights on the edges upon that vertex, in MST as the vertex degree. The IS distribution follows a power law with exponent r = 1.8 in WRG and [delta] = 2.2 in MST. Both results show that there must be a few stocks whose price fluctuations can powerfully influence the price dynamics of other stocks in the same market. In both cases these are the same companies.

Suggested Citation

  • Galazka, Marek, 2011. "Characteristics of the Polish Stock Market correlations," International Review of Financial Analysis, Elsevier, vol. 20(1), pages 1-5, January.
    • Handle: RePEc:eee:finana:v:20:y:2011:i:1:p:1-5
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1057-5219(10)00082-7
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. G. Bonanno & F. Lillo & R. N. Mantegna, 2001. "High-frequency cross-correlation in a set of stocks," Quantitative Finance, Taylor & Francis Journals, vol. 1(1), pages 96-104.
    2. R. Mantegna, 1999. "Hierarchical structure in financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 11(1), pages 193-197, September.
    3. Gebka, Bartosz, 2008. "Volume- and size-related lead-lag effects in stock returns and volatility: An empirical investigation of the Warsaw Stock Exchange," International Review of Financial Analysis, Elsevier, vol. 17(1), pages 134-155.
    4. Laurent Laloux & Pierre Cizeau & Jean-Philippe Bouchaud & Marc Potters, 1999. "Random matrix theory and financial correlations," Science & Finance (CFM) working paper archive 500053, Science & Finance, Capital Fund Management.
    5. Onnela, J.-P. & Chakraborti, A. & Kaski, K. & Kertész, J., 2003. "Dynamic asset trees and Black Monday," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 324(1), pages 247-252.
    6. Vasiliki Plerou & Parameswaran Gopikrishnan & Bernd Rosenow & Luis A. Nunes Amaral & H. Eugene Stanley, 1999. "Universal and non-universal properties of cross-correlations in financial time series," Papers cond-mat/9902283, arXiv.org.
    7. G. Bonanno & G. Caldarelli & F. Lillo & S. Micciché & N. Vandewalle & R. Mantegna, 2004. "Networks of equities in financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 38(2), pages 363-371, March.
    8. Laurent Laloux & Pierre Cizeau & Jean-Philippe Bouchaud & Marc Potters, 1999. "Random matrix theory," Science & Finance (CFM) working paper archive 500052, Science & Finance, Capital Fund Management.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Liu, Xueyong & Chen, Zhihua & Chen, Zhensong & Yao, Yinhong, 2022. "The time-varying spillover effect of China’s stock market during the COVID-19 pandemic," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    2. Djauhari, Maman Abdurachman & Gan, Siew Lee, 2015. "Optimality problem of network topology in stocks market analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 108-114.
    3. Polovnikov, Kirill & Kazakov, Vlad & Syntulsky, Sergey, 2020. "Core–periphery organization of the cryptocurrency market inferred by the modularity operator," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    4. V. A. Kalyagin & A. P. Koldanov & P. A. Koldanov & P. M. Pardalos & V. A. Zamaraev, 2013. "Measures of uncertainty in market network analysis," Papers 1311.2273, arXiv.org.
    5. Kalyagin, V.A. & Koldanov, A.P. & Koldanov, P.A. & Pardalos, P.M. & Zamaraev, V.A., 2014. "Measures of uncertainty in market network analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 59-70.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Leonidas Sandoval Junior & Italo De Paula Franca, 2011. "Correlation of financial markets in times of crisis," Papers 1102.1339, arXiv.org, revised Mar 2011.
    2. Sandoval, Leonidas & Franca, Italo De Paula, 2012. "Correlation of financial markets in times of crisis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(1), pages 187-208.
    3. Sandoval, Leonidas, 2014. "To lag or not to lag? How to compare indices of stock markets that operate on different times," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 403(C), pages 227-243.
    4. Teh, Boon Kin & Goo, Yik Wen & Lian, Tong Wei & Ong, Wei Guang & Choi, Wen Ting & Damodaran, Mridula & Cheong, Siew Ann, 2015. "The Chinese Correction of February 2007: How financial hierarchies change in a market crash," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 225-241.
    5. Anirban Chakraborti & Ioane Muni Toke & Marco Patriarca & Frederic Abergel, 2011. "Econophysics review: I. Empirical facts," Quantitative Finance, Taylor & Francis Journals, vol. 11(7), pages 991-1012.
    6. Sensoy, Ahmet & Tabak, Benjamin M., 2014. "Dynamic spanning trees in stock market networks: The case of Asia-Pacific," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 387-402.
    7. Aoki, Masanao & Hawkins, Raymond, 2009. "Macroeconomic Relaxation: Adjustment Processes of Hierarchical Economic Structures," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 3, pages 1-21.
    8. Tanya Araujo & Francisco Louca, 2007. "The geometry of crashes. A measure of the dynamics of stock market crises," Quantitative Finance, Taylor & Francis Journals, vol. 7(1), pages 63-74.
    9. Leonidas Sandoval Junior, 2011. "A Map of the Brazilian Stock Market," Papers 1107.4146, arXiv.org, revised Mar 2013.
    10. 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.
    11. Naylor, Michael J. & Rose, Lawrence C. & Moyle, Brendan J., 2007. "Topology of foreign exchange markets using hierarchical structure methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(1), pages 199-208.
    12. Kim, Min Jae & Kim, Sehyun & Jo, Yong Hwan & Kim, Soo Yong, 2011. "Dependence structure of the commodity and stock markets, and relevant multi-spread strategy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(21), pages 3842-3854.
    13. Sandoval, Leonidas, 2012. "Pruning a minimum spanning tree," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(8), pages 2678-2711.
    14. Anirban Chakraborti & Ioane Muni Toke & Marco Patriarca & Frederic Abergel, 2011. "Econophysics review: II. Agent-based models," Quantitative Finance, Taylor & Francis Journals, vol. 11(7), pages 1013-1041.
    15. Wilcox, Diane & Gebbie, Tim, 2007. "An analysis of cross-correlations in an emerging market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 375(2), pages 584-598.
    16. Gang-Jin Wang & Chi Xie & Shou Chen, 2017. "Multiscale correlation networks analysis of the US stock market: a wavelet analysis," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(3), pages 561-594, October.
    17. Peng Yue & Qing Cai & Wanfeng Yan & Wei-Xing Zhou, 2020. "Information flow networks of Chinese stock market sectors," Papers 2004.08759, arXiv.org.
    18. Artur F. Tomeczek & Tomasz M. Napiórkowski, 2024. "PageRank and Regression as a Two-Step Approach to Analysing a Network of Nasdaq Firms During a Recession: Insights from Minimum Spanning Tree Topology," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 3, pages 56-69.
    19. Výrost, Tomáš, 2012. "Country effects in CEE3 stock market networks: a preliminary study," MPRA Paper 43481, University Library of Munich, Germany.
    20. 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.

    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:eee:finana:v:20:y:2011:i:1:p:1-5. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620166 .

    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.