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Simple measure of similarity for the market graph construction

Author

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  • Grigory Bautin
  • Valery Kalyagin
  • Alexander Koldanov
  • Petr Koldanov
  • Panos Pardalos

Abstract

A simple measure of similarity for the construction of the market graph is proposed. The measure is based on the probability of the coincidence of the signs of the stock returns. This measure is robust, has a simple interpretation, is easy to calculate and can be used as measure of similarity between any number of random variables. For the case of pairwise similarity the connection of this measure with the sign correlation of Fechner is noted. The properties of the proposed measure of pairwise similarity in comparison with the classic Pearson correlation are studied. The simple measure of pairwise similarity is applied (in parallel with the classic correlation) for the study of Russian and Swedish market graphs. The new measure of similarity for more than two random variables is introduced and applied to the additional deeper analysis of Russian and Swedish markets. Some interesting phenomena for the cliques and independent sets of the obtained market graphs are observed. Copyright Springer-Verlag Berlin Heidelberg 2013

Suggested Citation

  • Grigory Bautin & Valery Kalyagin & Alexander Koldanov & Petr Koldanov & Panos Pardalos, 2013. "Simple measure of similarity for the market graph construction," Computational Management Science, Springer, vol. 10(2), pages 105-124, June.
    • Handle: RePEc:spr:comgts:v:10:y:2013:i:2:p:105-124
    DOI: 10.1007/s10287-013-0169-3
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Kalyagin, V.A. & Koldanov, A.P. & Koldanov, P.A., 2022. "Reliability of maximum spanning tree identification in correlation-based market networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 599(C).
    2. V. A. Kalyagin & A. P. Koldanov & P. A. Koldanov & P. M. Pardalos, 2018. "Optimal decision for the market graph identification problem in a sign similarity network," Annals of Operations Research, Springer, vol. 266(1), pages 313-327, July.
    3. Carlo Drago & Andrea Scozzari, 2022. "Evaluating conditional covariance estimates via a new targeting approach and a networks-based analysis," Papers 2202.02197, arXiv.org.
    4. Výrost, Tomáš & Lyócsa, Štefan & Baumöhl, Eduard, 2015. "Granger causality stock market networks: Temporal proximity and preferential attachment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 427(C), pages 262-276.
    5. V. A. Kalyagin & P. A. Koldanov & P. M. Pardalos, 2015. "Optimal decision for the market graph identification problem in sign similarity network," Papers 1512.06449, arXiv.org.
    6. 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.
    7. Halkos, George & Tsilika, Kyriaki, 2016. "Measures of correlation and computer algebra," MPRA Paper 70200, University Library of Munich, Germany.
    8. 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.
    9. Seo Woo Hong & Pierre Miasnikof & Roy Kwon & Yuri Lawryshyn, 2021. "Market Graph Clustering via QUBO and Digital Annealing," JRFM, MDPI, vol. 14(1), pages 1-13, January.
    10. V. A. Kalyagin & A. P. Koldanov & P. A. Koldanov & P. M. Pardalos & V. A. Zamaraev, 2013. "Measures of uncertainty in market network analysis," Papers 1311.2273, arXiv.org.
    11. 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.
    12. 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.

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