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Proceedings Article

Economic sector identification in a set of stocks traded at the New York Stock Exchange: a comparative analysis

[+] Author Affiliations
C. Coronnello, M. Tumminello, F. Lillo, S. Miccichè, R. N. Mantegna

Univ. degli Studi di Palermo (Italy)

Proc. SPIE 6601, Noise and Stochastics in Complex Systems and Finance, 66010T (June 12, 2007); doi:10.1117/12.729619
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From Conference Volume 6601

  • Noise and Stochastics in Complex Systems and Finance
  • János Kertész; Stefan Bornholdt; Rosario N. Mantegna
  • Florence, Italy | May 20, 2007

abstract

We review some methods recently used in the literature to detect the existence of a certain degree of common behavior of stock returns belonging to the same economic sector. Specifically, we discuss methods based on random matrix theory and hierarchical clustering techniques. We apply these methods to a set of stocks traded at the New York Stock Exchange. The investigated time series are recorded at a daily time horizon. All the considered methods are able to detect economic information and the presence of clusters characterized by the economic sector of stocks. However, different methodologies provide different information about the considered set. Our comparative analysis suggests that the application of just a single method could not be able to extract all the economic information present in the correlation coefficient matrix of a set of stocks.

© (2007) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Topics

Matrices
Citation

C. Coronnello ; M. Tumminello ; F. Lillo ; S. Miccichè and R. N. Mantegna
"Economic sector identification in a set of stocks traded at the New York Stock Exchange: a comparative analysis", Proc. SPIE 6601, Noise and Stochastics in Complex Systems and Finance, 66010T (June 12, 2007); doi:10.1117/12.729619; http://dx.doi.org/10.1117/12.729619


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