Shrinkage and spectral filtering of correlation matrices: a comparison via the Kullback-Leibler distance
- Authors: Tumminello, M.; Lillo, F.; Mantegna, R.
- Publication year: 2007
- Type: Articolo in rivista (Articolo in rivista)
- OA Link: http://hdl.handle.net/10447/30988
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