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Analysis of data clusters obtained by self-organizing methods

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  • Gafiychuk, V.V
  • Datsko, B.Yo
  • Izmaylova, J

Abstract

The self-organizing methods were used for the investigation of financial market. As an example we consider data time-series of Dow Jones index for the years 2002–2003 (R. Mantegna, cond-mat/9802256). In order to reveal new structures in stock market behavior of the companies drawing up Dow Jones index we apply self-organizing maps (SOM) and group method of data handling (GMDH) algorithms. Using SOM techniques we obtain SOM-maps that establish a new relationship in market structure. Analysis of the obtained clusters was made by GMDH.

Suggested Citation

  • Gafiychuk, V.V & Datsko, B.Yo & Izmaylova, J, 2004. "Analysis of data clusters obtained by self-organizing methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 341(C), pages 547-555.
    • Handle: RePEc:eee:phsmap:v:341:y:2004:i:c:p:547-555
    DOI: 10.1016/j.physa.2004.04.115
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    References listed on IDEAS

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    1. R. Mantegna, 1999. "Hierarchical structure in financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 11(1), pages 193-197, September.
    2. Fabrizio Lillo & Rosario N. Mantegna, 2000. "Variety and Volatility in Financial Markets," Papers cond-mat/0006065, arXiv.org.
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    2. Juan Brida & Wiston Risso, 2010. "Dynamics and Structure of the 30 Largest North American Companies," Computational Economics, Springer;Society for Computational Economics, vol. 35(1), pages 85-99, January.

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