Shrinkage and spectral filtering of correlation matrices: a comparison via the Kullback-Leibler distance

Rosario Nunzio Mantegna, Michele Tumminello, Fabrizio Lillo, Fabrizio Lillo, Rosario N. Mantegna, Michele Tumminello

Risultato della ricerca: Article

12 Citazioni (Scopus)

Abstract

The problem of filtering information from large correlation matrices is of great importance in many applications. We have recently proposed the use of the Kullback-Leibler distance to measure the performance of filtering algorithms in recovering the underlying correlation matrix when the variables are described by a multivariate Gaussian distribution. Here we use the Kullback-Leibler distance to investigate the performance of filtering methods based on Random Matrix Theory and on the shrinkage technique. We also present some results on the application of the Kullback-Leibler distance to multivariate data which are non Gaussian distributed
Lingua originaleEnglish
pagine (da-a)4079-4088
Numero di pagine10
RivistaActa Physica Polonica B
Volume38
Stato di pubblicazionePublished - 2007

All Science Journal Classification (ASJC) codes

  • Physics and Astronomy(all)

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