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arXiv · 2104.08966

Generic Features in the Spectral Decomposition of Correlation Matrices

Yuriy Stepanov·Hendrik Herrmann·Thomas Guhr
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Abstract

We show that correlation matrices with particular average and variance of the correlation coefficients have a notably restricted spectral structure. Applying geometric methods, we derive lower bounds for the largest eigenvalue and the alignment of the corresponding eigenvector. We explain how and to which extent, a distinctly large eigenvalue and an approximately diagonal eigenvector generically occur for specific correlation matrices independently of the correlation matrix dimension.

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Yuriy Stepanov, Hendrik Herrmann, Thomas Guhr. 2021-04-18. Generic Features in the Spectral Decomposition of Correlation Matrices. https://doi.org/10.1063/5.0054438

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