IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v391y2012i20p5049-5057.html
   My bibliography  Save this article

A robust filter in stock networks analysis

Author

Listed:
  • Djauhari, Maman A.

Abstract

We show that the use of a minimal spanning tree (MST) to filter important information in a complex system is not robust except when the system contains a unique MST. In this paper we propose to use the forest of all MSTs as a robust filter. According to this filter, centrality measures are also robust. For that purpose an algorithm, which can also be used to detect the uniqueness of an MST, will be provided. A simple hypothetical example will clarify the construction of the proposed filter and a real problem in filtering the information contained in NYSE 100 stocks will illustrate its advantages compared to the MST-based filter.

Suggested Citation

  • Djauhari, Maman A., 2012. "A robust filter in stock networks analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(20), pages 5049-5057.
  • Handle: RePEc:eee:phsmap:v:391:y:2012:i:20:p:5049-5057
    DOI: 10.1016/j.physa.2012.05.060
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437112004323
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2012.05.060?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. 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.
    2. Miccichè, Salvatore & Bonanno, Giovanni & Lillo, Fabrizio & N. Mantegna, Rosario, 2003. "Degree stability of a minimum spanning tree of price return and volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 324(1), pages 66-73.
    3. Eom, Cheoljun & Oh, Gabjin & Jung, Woo-Sung & Jeong, Hawoong & Kim, Seunghwan, 2009. "Topological properties of stock networks based on minimal spanning tree and random matrix theory in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(6), pages 900-906.
    4. Tabak, Benjamin M. & Serra, Thiago R. & Cajueiro, Daniel O., 2010. "Topological properties of stock market networks: The case of Brazil," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(16), pages 3240-3249.
    5. Cheoljun Eom & Gabjin Oh & Seunghwan Kim, 2006. "Topological Properties of the Minimal Spanning Tree in Korean and American Stock Markets," Papers physics/0612068, arXiv.org, revised Jan 2007.
    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. 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.
    2. Cheng Juan Zhan & William Rea & Alethea Rea, 2016. "Stock Selection as a Problem in Phylogenetics—Evidence from the ASX," IJFS, MDPI, vol. 4(4), pages 1-19, September.
    3. Hannah Cheng Juan Zhan & William Rea & Alethea Rea, 2015. "A Comparison of Three Network Portfolio Selection Methods -- Evidence from the Dow Jones," Working Papers in Economics 15/02, University of Canterbury, Department of Economics and Finance.
    4. 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.
    5. Djauhari, Maman Abdurachman & Gan, Siew Lee, 2013. "Minimal spanning tree problem in stock networks analysis: An efficient algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(9), pages 2226-2234.
    6. Nguyen, Q. & Nguyen, N.K. K. & Nguyen, L.H. N., 2019. "Dynamic topology and allometric scaling behavior on the Vietnamese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 235-243.
    7. Fatin Nur Amirah Mahamood & Hafizah Bahaludin & Mimi Hafizah Abdullah, 2019. "A Network Analysis of Shariah-Compliant Stocks across Global Financial Crisis: A Case of Malaysia," Modern Applied Science, Canadian Center of Science and Education, vol. 13(7), pages 1-80, July.
    8. 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.
    9. 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. 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.
    2. Marcin Wk{a}torek & Stanis{l}aw Dro.zd.z & Jaros{l}aw Kwapie'n & Ludovico Minati & Pawe{l} O'swik{e}cimka & Marek Stanuszek, 2020. "Multiscale characteristics of the emerging global cryptocurrency market," Papers 2010.15403, arXiv.org, revised Mar 2021.
    3. Djauhari, Maman Abdurachman & Gan, Siew Lee, 2013. "Minimal spanning tree problem in stock networks analysis: An efficient algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(9), pages 2226-2234.
    4. Peng Yue & Qing Cai & Wanfeng Yan & Wei-Xing Zhou, 2020. "Information flow networks of Chinese stock market sectors," Papers 2004.08759, arXiv.org.
    5. 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.
    6. Radhakrishnan, Srinivasan & Duvvuru, Arjun & Sultornsanee, Sivarit & Kamarthi, Sagar, 2016. "Phase synchronization based minimum spanning trees for analysis of financial time series with nonlinear correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 259-270.
    7. Samitas, Aristeidis & Kampouris, Elias & Polyzos, Stathis, 2022. "Covid-19 pandemic and spillover effects in stock markets: A financial network approach," International Review of Financial Analysis, Elsevier, vol. 80(C).
    8. 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.
    9. Leonidas Sandoval Junior, 2011. "A Map of the Brazilian Stock Market," Papers 1107.4146, arXiv.org, revised Mar 2013.
    10. Kim, Kyungwon & Jung, Sean S., 2014. "Empirical analysis of structural change in Credit Default Swap volatility," Chaos, Solitons & Fractals, Elsevier, vol. 60(C), pages 56-67.
    11. Qu, Junyi & Liu, Ying & Tang, Ming & Guan, Shuguang, 2022. "Identification of the most influential stocks in financial networks," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    12. A. Q. Barbi & G. A. Prataviera, 2017. "Nonlinear dependencies on Brazilian equity network from mutual information minimum spanning trees," Papers 1711.06185, arXiv.org, revised May 2019.
    13. Linda Margarita Medina Herrera & Ernesto Armando Pacheco Velázquez, 2012. "Distances And Networks: The Case Of Mexico," Accounting & Taxation, The Institute for Business and Finance Research, vol. 4(2), pages 39-48.
    14. Eom, Cheoljun & Kwon, Okyu & Jung, Woo-Sung & Kim, Seunghwan, 2010. "The effect of a market factor on information flow between stocks using the minimal spanning tree," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(8), pages 1643-1652.
    15. Barbi, A.Q. & Prataviera, G.A., 2019. "Nonlinear dependencies on Brazilian equity network from mutual information minimum spanning trees," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 876-885.
    16. Eom, Cheoljun, 2017. "Two-faced property of a market factor in asset pricing and diversification effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 190-199.
    17. Cheong, Siew Ann & Fornia, Robert Paulo & Lee, Gladys Hui Ting & Kok, Jun Liang & Yim, Woei Shyr & Xu, Danny Yuan & Zhang, Yiting, 2011. "The Japanese economy in crises: A time series segmentation study," Economics Discussion Papers 2011-24, Kiel Institute for the World Economy (IfW Kiel).
    18. Zhu, Jia & Wei, Daijun, 2021. "Analysis of stock market based on visibility graph and structure entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 576(C).
    19. Samitas, Aristeidis & Kampouris, Elias & Kenourgios, Dimitris, 2020. "Machine learning as an early warning system to predict financial crisis," International Review of Financial Analysis, Elsevier, vol. 71(C).
    20. 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.

    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:phsmap:v:391:y:2012:i:20:p:5049-5057. 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.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.