Using Random Matrix Theory one can derive exact relations between the eigenvalue spectrum of the covariance matrix and the eigenvalue spectrum of its estimator (experimentally measured correlation matrix). These relations will be used to analyze a particular case of the correlations in financial ser
Signal and noise in correlation matrix
✍ Scribed by Z. Burda; A. Görlich; A. Jarosz; J. Jurkiewicz
- Publisher
- Elsevier Science
- Year
- 2004
- Tongue
- English
- Weight
- 402 KB
- Volume
- 343
- Category
- Article
- ISSN
- 0378-4371
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✦ Synopsis
Using random matrix technique we determine an exact relation between the eigenvalue spectrum of the covariance matrix and of its estimator. This relation can be used in practice to compute eigenvalue invariants of the covariance (correlation) matrix. Results can be applied in various problems where one experimentally estimates correlations in a system with many degrees of freedom, like for instance those in statistical physics, lattice measurements of ÿeld theory, genetics, quantitative ÿnance and other applications of multivariate statistics.
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