IDEAS home Printed from https://ideas.repec.org/a/wsi/acsxxx/v11y2008i06ns0219525908002021.html
   My bibliography  Save this article

Centrality And Peripherality In Filtered Graphs From Dynamical Financial Correlations

Author

Listed:
  • F. POZZI

    (Department of Applied Mathematics, The Australian National University, 0200 Canberra, ACT, Australia)

  • T. DI MATTEO

    (Department of Applied Mathematics, The Australian National University, 0200 Canberra, ACT, Australia)

  • T. ASTE

    (Department of Applied Mathematics, The Australian National University, 0200 Canberra, ACT, Australia)

Abstract

Minimum spanning trees and planar maximally filtered graphs are generated from correlations between the 300 most-capitalized NYSE stocks' daily returns, computed dynamically over moving windows of sizes between 1 and 12 months, in the period from 2001 to 2003. We study how different economic sectors differently populate the various regions of these graphs. We find that the financial sector is always at the center whereas the periphery is shared among different sectors. Four extremes are observed: stocks well-connected and central; stocks well-connected but at the same time peripheral; stocks poorly-connected but central; stocks poorly-connected and peripheral. Two principal components of centrality measures are individuated. The economic meaning of this hierarchical disposition is discussed.

Suggested Citation

  • F. Pozzi & T. Di Matteo & T. Aste, 2008. "Centrality And Peripherality In Filtered Graphs From Dynamical Financial Correlations," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 11(06), pages 927-950.
    • Handle: RePEc:wsi:acsxxx:v:11:y:2008:i:06:n:s0219525908002021
    DOI: 10.1142/S0219525908002021
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0219525908002021
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1142/S0219525908002021?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. Dorogovtsev, S.N. & Mendes, J.F.F., 2003. "Evolution of Networks: From Biological Nets to the Internet and WWW," OUP Catalogue, Oxford University Press, number 9780198515906.
    2. Caldarelli, Guido, 2007. "Scale-Free Networks: Complex Webs in Nature and Technology," OUP Catalogue, Oxford University Press, number 9780199211517.
    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. Tomaso Aste, 2019. "Cryptocurrency market structure: connecting emotions and economics," Digital Finance, Springer, vol. 1(1), pages 5-21, November.
    2. Li, Yan & Jiang, Xiong-Fei & Tian, Yue & Li, Sai-Ping & Zheng, Bo, 2019. "Portfolio optimization based on network topology," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 671-681.
    3. Kazemilari, Mansooreh & Mardani, Abbas & Streimikiene, Dalia & Zavadskas, Edmundas Kazimieras, 2017. "An overview of renewable energy companies in stock exchange: Evidence from minimal spanning tree approach," Renewable Energy, Elsevier, vol. 102(PA), pages 107-117.
    4. Dariusz Siudak, 2021. "Sectoral Analysis of the US Stock Market through Complex Networks," European Research Studies Journal, European Research Studies Journal, vol. 0(3B), pages 951-966.
    5. Tomaso Aste, 2019. "Cryptocurrency market structure: connecting emotions and economics," Papers 1903.00472, arXiv.org.
    6. Wiliński, M. & Sienkiewicz, A. & Gubiec, T. & Kutner, R. & Struzik, Z.R., 2013. "Structural and topological phase transitions on the German Stock Exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(23), pages 5963-5973.
    7. 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.
    8. Stefan, F.M. & Atman, A.P.F., 2023. "Asymmetric rate of returns and wealth distribution influenced by the introduction of technical analysis into a behavioral agent-based model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    9. Cho, Younghwan & Song, Jae Wook, 2023. "Hierarchical risk parity using security selection based on peripheral assets of correlation-based minimum spanning trees," Finance Research Letters, Elsevier, vol. 53(C).
    10. Zhang, Yiting & Lee, Gladys Hui Ting & Wong, Jian Cheng & Kok, Jun Liang & Prusty, Manamohan & Cheong, Siew Ann, 2011. "Will the US economy recover in 2010? A minimal spanning tree study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(11), pages 2020-2050.
    11. Kazemilari, Mansooreh & Djauhari, Maman Abdurachman, 2015. "Correlation network analysis for multi-dimensional data in stocks market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 429(C), pages 62-75.

    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. Ya-Chun Gao & Zong-Wen Wei & Bing-Hong Wang, 2013. "Dynamic Evolution Of Financial Network And Its Relation To Economic Crises," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 24(02), pages 1-10.
    2. Vitor H. P. Louzada & Fabio Daolio & Hans J. Herrmann & Marco Tomassini, "undated". "Smart rewiring for network robustness," Working Papers ETH-RC-14-004, ETH Zurich, Chair of Systems Design.
    3. Yao, Yiyang & Zhou, Yinzuo, 2017. "Epidemic spreading on dual-structure networks with mobile agents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 467(C), pages 218-225.
    4. Jukka-Pekka Onnela & Samuel Arbesman & Marta C González & Albert-László Barabási & Nicholas A Christakis, 2011. "Geographic Constraints on Social Network Groups," PLOS ONE, Public Library of Science, vol. 6(4), pages 1-7, April.
    5. T. Di Matteo & F. Pozzi & T. Aste, 2010. "The use of dynamical networks to detect the hierarchical organization of financial market sectors," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 73(1), pages 3-11, January.
    6. James B. Glattfelder & Thomas Bisig & Richard B. Olsen, 2014. "R&D Strategy Document," Papers 1405.6027, arXiv.org.
    7. Pietro Gravino & Vito D. P. Servedio & Alain Barrat & Vittorio Loreto, 2012. "Complex Structures And Semantics In Free Word Association," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 15(03n04), pages 1-22.
    8. Diego Garlaschelli & Maria I. Loffredo, 2007. "Effects of network topology on wealth distributions," Papers 0711.4710, arXiv.org, revised Jan 2008.
    9. Zhou, Wei-Xing & Jiang, Zhi-Qiang & Sornette, Didier, 2007. "Exploring self-similarity of complex cellular networks: The edge-covering method with simulated annealing and log-periodic sampling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 375(2), pages 741-752.
    10. Guido Caldarelli & Matthieu Cristelli & Andrea Gabrielli & Luciano Pietronero & Antonio Scala & Andrea Tacchella, 2012. "A Network Analysis of Countries’ Export Flows: Firm Grounds for the Building Blocks of the Economy," PLOS ONE, Public Library of Science, vol. 7(10), pages 1-11, October.
    11. Bezsudnov, I.V. & Snarskii, A.A., 2014. "From the time series to the complex networks: The parametric natural visibility graph," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 53-60.
    12. Mark S. Handcock & Adrian E. Raftery & Jeremy M. Tantrum, 2007. "Model‐based clustering for social networks," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 170(2), pages 301-354, March.
    13. Wang, Qingyun & Duan, Zhisheng & Chen, Guanrong & Feng, Zhaosheng, 2008. "Synchronization in a class of weighted complex networks with coupling delays," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(22), pages 5616-5622.
    14. Hutzler, S. & Sommer, C. & Richmond, P., 2016. "On the relationship between income, fertility rates and the state of democracy in society," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 452(C), pages 9-18.
    15. F. W. S. Lima, 2015. "Evolution of egoism on semi-directed and undirected Barabási-Albert networks," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 26(12), pages 1-9.
    16. G. Ghoshal & M. E.J. Newman, 2007. "Growing distributed networks with arbitrary degree distributions," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 58(2), pages 175-184, July.
    17. Andreas Koulouris & Ioannis Katerelos & Theodore Tsekeris, 2013. "Multi-Equilibria Regulation Agent-Based Model of Opinion Dynamics in Social Networks," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, vol. 11(1), pages 51-70.
    18. Chang, Y.F. & Han, S.K. & Wang, X.D., 2018. "The way to uncover community structure with core and diversity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 501(C), pages 111-119.
    19. Chakrabarti, Anindya S., 2015. "Stochastic Lotka-Volterra equations: A model of lagged diffusion of technology in an interconnected world," IIMA Working Papers WP2015-08-05, Indian Institute of Management Ahmedabad, Research and Publication Department.
    20. Roth, Camille, 2007. "Empiricism for descriptive social network models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 378(1), pages 53-58.

    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:wsi:acsxxx:v:11:y:2008:i:06:n:s0219525908002021. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/acs/acs.shtml .

    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.