IDEAS home Printed from https://ideas.repec.org/h/spr/spochp/978-3-319-09683-4_3.html
   My bibliography  Save this book chapter

Robustness of Sign Correlation in Market Network Analysis

In: Network Models in Economics and Finance

Author

Listed:
  • Grigory A. Bautin

    (National Research University Higher School of Economics, Laboratory LATNA)

  • Alexander P. Koldanov

    (National Research University Higher School of Economics, Laboratory LATNA)

  • Panos M. Pardalos

    (National Research University Higher School of Economics, Laboratory LATNA)

Abstract

Financial market can be modeled as network represented by a complete weighted graph. Different characteristics of this graph (minimum spanning tree, market graph, and others) give an important information on the network. In the present paper it is studied how the choice of measure of similarity between stocks influences the statistical errors in the calculation of network characteristics. It is shown that sign correlation is a robust measure of similarity in contrast with Pearson correlation widely used in market network analysis. This gives a possibility to get more precise information on stock market from observations.

Suggested Citation

  • Grigory A. Bautin & Alexander P. Koldanov & Panos M. Pardalos, 2014. "Robustness of Sign Correlation in Market Network Analysis," Springer Optimization and Its Applications, in: Valery A. Kalyagin & Panos M. Pardalos & Themistocles M. Rassias (ed.), Network Models in Economics and Finance, edition 127, pages 25-33, Springer.
    • Handle: RePEc:spr:spochp:978-3-319-09683-4_3
    DOI: 10.1007/978-3-319-09683-4_3
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

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


    Cited by:

    1. Kalyagin, V. & Koldanov, A. & Koldanov, P. & Pardalos, P., 2017. "Statistical Procedures for Stock Markets Network Structures Identification," Journal of the New Economic Association, New Economic Association, vol. 35(3), pages 33-52.

    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:spr:spochp:978-3-319-09683-4_3. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.