Abstract
We use methods of random matrix theory to analyze the cross-correlation matrix of stock price changes of the largest 1000 U.S. companies for the 2-year period 1994–1995. We find that the statistics of most of the eigenvalues in the spectrum of agree with the predictions of random matrix theory, but there are deviations for a few of the largest eigenvalues. We find that has the universal properties of the Gaussian orthogonal ensemble of random matrices. Furthermore, we analyze the eigenvectors of through their inverse participation ratio and find eigenvectors with large ratios at both edges of the eigenvalue spectrum—a situation reminiscent of localization theory results.
- Received 22 February 1999
DOI:https://doi.org/10.1103/PhysRevLett.83.1471
©1999 American Physical Society