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Robustness of Sign Correlation in Market Network Analysis

  • Grigory A. BautinEmail author
  • Alexander P. Koldanov
  • Panos M. Pardalos
Chapter
Part of the Springer Optimization and Its Applications book series (SOIA, volume 100)

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.

Keywords

Pearson Correlation Minimum Span Tree Sample Sign Heavy Tail Mixture Distribution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

This work is partly supported by RF government grant, ag. 11.G34.31.0057 and RFFI grant 14-01-00807.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Grigory A. Bautin
    • 1
    Email author
  • Alexander P. Koldanov
    • 1
  • Panos M. Pardalos
    • 1
  1. 1.National Research University Higher School of Economics, Laboratory LATNAMoscowRussia

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