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Proceedings Article

Correlation filtering in financial time series (Invited Paper)

[+] Author Affiliations
T. Aste, Tiziana Di Matteo

The Australian National Univ. (Australia)

M. Tumminello, R. N. Mantegna

INFM (Italy) and Univ. di Palermo (Italy)

Proc. SPIE 5848, Noise and Fluctuations in Econophysics and Finance, 100 (June 01, 2005); doi:10.1117/12.619185
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From Conference Volume 5848

  • Noise and Fluctuations in Econophysics and Finance
  • Derek Abbott; Jean-Philippe Bouchaud; Xavier Gabaix; Joseph L. McCauley
  • Austin, TX | May 23, 2005

abstract

We apply a method to filter relevant information from the correlation coefficient matrix by extracting a network of relevant interactions. This method succeeds to generate networks with the same hierarchical structure of the Minimum Spanning Tree but containing a larger amount of links resulting in a richer network topology allowing loops and cliques. In Tumminello et al.,1 we have shown that this method, applied to a financial portfolio of 100 stocks in the USA equity markets, is pretty efficient in filtering relevant information about the clustering of the system and its hierarchical structure both on the whole system and within each cluster. In particular, we have found that triangular loops and 4 element cliques have important and significant relations with the market structure and properties. Here we apply this filtering procedure to the analysis of correlation in two different kind of interest rate time series (16 Eurodollars and 34 US interest rates).

© (2005) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Topics

Matrices ; Networks
Citation

T. Aste ; Tiziana Di Matteo ; M. Tumminello and R. N. Mantegna
"Correlation filtering in financial time series (Invited Paper)", Proc. SPIE 5848, Noise and Fluctuations in Econophysics and Finance, 100 (June 01, 2005); doi:10.1117/12.619185; http://dx.doi.org/10.1117/12.619185


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