IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2102.00070.html
   My bibliography  Save this paper

Network-centric indicators for fragility in global financial indices

Author

Listed:
  • Areejit Samal
  • Sunil Kumar
  • Yasharth Yadav
  • Anirban Chakraborti

Abstract

Over the last two decades, financial systems have been studied and analysed from the perspective of complex networks, where the nodes and edges in the network represent the various financial components and the strengths of correlations between them. Here, we adopt a similar network-based approach to analyse the daily closing prices of 69 global financial market indices across 65 countries over a period of 2000-2014. We study the correlations among the indices by constructing threshold networks superimposed over minimum spanning trees at different time frames. We investigate the effect of critical events in financial markets (crashes and bubbles) on the interactions among the indices by performing both static and dynamic analyses of the correlations. We compare and contrast the structures of these networks during periods of crashes and bubbles, with respect to the normal periods in the market. In addition, we study the temporal evolution of traditional market indicators, various global network measures and the recently developed edge-based curvature measures. We show that network-centric measures can be extremely useful in monitoring the fragility in the global financial market indices.

Suggested Citation

  • Areejit Samal & Sunil Kumar & Yasharth Yadav & Anirban Chakraborti, 2021. "Network-centric indicators for fragility in global financial indices," Papers 2102.00070, arXiv.org.
    • Handle: RePEc:arx:papers:2102.00070
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2102.00070
    File Function: Latest version
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Kulkarni, Saumitra & Pharasi, Hirdesh K. & Vijayaraghavan, Sudharsan & Kumar, Sunil & Chakraborti, Anirban & Samal, Areejit, 2024. "Investigation of Indian stock markets using topological data analysis and geometry-inspired network measures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 643(C).
    2. Anwesha Sengupta & Shashankaditya Upadhyay & Indranil Mukherjee & Prasanta K. Panigrahi, 2024. "A study of the effect of influential spreaders on the different sectors of Indian market and a few foreign markets: a complex networks perspective," Journal of Computational Social Science, Springer, vol. 7(1), pages 45-85, April.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:arx:papers:2102.00070. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.