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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
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    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.

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