Clustering stock market companies via chaotic map synchronization

N. Basalto, R. Bellotti, F. De Carlo, P. Facchi and S. Pascazio

Physica A: Statistical Mechanics and its Applications, 2005, vol. 345, issue 1, 196-206

Abstract: A pairwise clustering approach is applied to the analysis of the Dow Jones index companies, in order to identify similar temporal behavior of the traded stock prices. To this end, the chaotic map clustering algorithm is used, where a map is associated to each company and the correlation coefficients of the financial time series to the coupling strengths between maps. The simulation of a chaotic map dynamics gives rise to a natural partition of the data, as companies belonging to the same industrial branch are often grouped together. The identification of clusters of companies of a given stock market index can be exploited in the portfolio optimization strategies.

Keywords: Stock index; Clustering algorithms; Chaotic maps (search for similar items in EconPapers)
Date: 2005
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Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:345:y:2005:i:1:p:196-206

DOI: 10.1016/j.physa.2004.07.034

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