1999/02/20 by Vasiliki Plerou, Parameswaran Gopikrishnan, Bernd Rosenow +2 · 5 citations
Physics and Astronomy · Economics, Econometrics and Finance · #cond-mat.stat-mech #cond-mat.dis-nn #q-fin.ST
paper · pdf · doi:10.1103/physrevlett.83.1471
published as Phys. Rev. Lett., 83 (1999) 1471 · 14 pages, 3 figures, Revtex
arxiv created 1999/02/20 · arxiv updated 2009/11/30
We use methods of random matrix theory to analyze the cross-correlation matrix C of price changes of the largest 1000 US stocks for the 2-year period 1994-95. We find that the statistics of most of the eigenvalues in the spectrum of C agree with the predictions of random matrix theory, but there are deviations for a few of the largest eigenvalues. We find that C has the universal properties of the Gaussian orthogonal ensemble of random matrices. Furthermore, we analyze the eigenvectors of C through their inverse participation ratio and find eigenvectors with large inverse participation ratios at both edges of the eigenvalue spectrum--a situation reminiscent of results in localization theory.