English

A tool for filtering information in complex systems

Disordered Systems and Neural Networks 2007-05-23 v2 Statistical Mechanics Physics and Society

Abstract

We introduce a technique to filter out complex data-sets by extracting a subgraph of representative links. Such a filtering can be tuned up to any desired level by controlling the genus of the resulting graph. We show that this technique is especially suitable for correlation based graphs giving filtered graphs which preserve the hierarchical organization of the minimum spanning tree but containing a larger amount of information in their internal structure. In particular in the case of planar filtered graphs (genus equal to 0) triangular loops and 4 element cliques are formed. The application of this filtering procedure to 100 stocks in the USA equity markets shows that such loops and cliques have important and significant relations with the market structure and properties.

Keywords

Cite

@article{arxiv.cond-mat/0501335,
  title  = {A tool for filtering information in complex systems},
  author = {M. Tumminello and T. Aste and T. Di Matteo and R. N. Mantegna},
  journal= {arXiv preprint arXiv:cond-mat/0501335},
  year   = {2007}
}

Comments

8 pages, 3 figures, 4 tables