Livan, Giacomo, Alfarano, Simone and Scalas, Enrico (2011) Fine structure of spectral properties for random correlation matrices: an application to financial markets. Physical Review E, 84. 016113. ISSN 1539-3755

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Abstract

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 and we compare empirical spectra to those predicted by Random Matrix Theory for such models.

Item Type:	Article
Schools and Departments:	School of Mathematical and Physical Sciences > Mathematics
Subjects:	Q Science > QA Mathematics > QA0276 Mathematical statistics
Depositing User:	Enrico Scalas
Date Deposited:	24 Sep 2014 06:28
Last Modified:	02 Jul 2019 21:32
URI:	http://sro.sussex.ac.uk/id/eprint/50246

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