Clustering stock market companies via chaotic map synchronization

Details Clustering stock market companies via chaotic map synchronization Clustering stock market companies via chaotic map synchronization

2004-04-21

arxiv.org/abs/cond-mat/0404497v1

Physica A 345 (2005) 196

Physics

Condensed Matter

Disordered Systems and Neural Networks

12 pages, 3 figures

Scientific paper

10.1016/j.physa.2004.07.034

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 are associated 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.

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