publication . Preprint . 2006

Random Correlation Matrix and De-Noising

Ken-ichi Mitsui; Yoshio Tabata;
Open Access
  • Published: 01 Sep 2006
In Finance, the modeling of a correlation matrix is one of the important problems. In particular, the correlation matrix obtained from market data has the noise. Here we apply the de-noising processing based on the wavelet analysis to the noisy correlation matrix, which is generated by a parametric function with random parameters. First of all, we show that two properties, i.e. symmetry and ones of all diagonal elements, of the correlation matrix preserve via the de-noising processing and the efficiency of the de-nosing processing by numerical experiments. We propose that the de-noising processing is one of the effective methods in order to reduce the noise in t...
free text keywords: correlation matrix, calibration, rank reduction, de-noising, wavelet analysis, jel:C51, jel:C61, jel:C63, jel:G32

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