The fine structure of spectral properties for random correlation matrices: an application to financial markets
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comunitat-uji-handle2:10234/8643
comunitat-uji-handle3:10234/8644
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Título
The fine structure of spectral properties for random correlation matrices: an application to financial marketsFecha de publicación
2011-07-29Editor
American Physical SocietyISSN
1539-3755; 1550-2376Cita bibliográfica
Physical Review E (2011) vol. 84, no. 1Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
http://link.aps.org/doi/10.1103/PhysRevE.84.016113Versión
info:eu-repo/semantics/publishedVersionPalabras clave / Materias
Resumen
We study some properties of eigenvalue spectra of financial correlation matrices. In particular, we investigate the nature of the large eigenvalue bulks which are observed empirically, and which have often been regarded ... [+]
We study some properties of eigenvalue spectra of financial correlation matrices. In particular, we investigate the nature of the large eigenvalue bulks which are observed empirically, and which have often been regarded as a consequence of the supposedly large amount of noise contained in financial data. We challenge this common knowledge by acting on the empirical correlation matrices of two data sets with a filtering procedure which highlights some of the cluster structure they contain, and we analyze the consequences of such filtering on eigenvalue spectra. We show that empirically observed eigenvalue bulks emerge as superpositions of smaller structures, which in turn emerge as a consequence of cross correlations between stocks. We interpret and corroborate these findings in terms of factor models, and we compare empirical spectra to those predicted by random matrix theory for such models. [-]
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