scholarly journals Random Matrix Theory of Dynamical Cross Correlations in Financial Data

2009 ◽  
Vol 179 ◽  
pp. 60-70 ◽  
Author(s):  
Yasuhiro Nakayama ◽  
Hiroshi Iyetomi
2000 ◽  
Vol 03 (03) ◽  
pp. 399-403 ◽  
Author(s):  
BERND ROSENOW ◽  
VASILIKI PLEROU ◽  
PARAMESWARAN GOPIKRISHNAN ◽  
LUÍS A. NUNES AMARAL ◽  
H. EUGENE STANLEY

We address the question of how to precisely identify correlated behavior between different firms in the economy by applying methods of random matrix theory (RMT). Specifically, we use methods of random matrix theory to analyze the cross-correlation matrix [Formula: see text] of price changes of the largest 1000 US stocks for the 2-year period 1994–1995. We find that the statistics of most of the eigenvalues in the spectrum of [Formula: see text] agree with the predictions of random matrix theory, but there are deviations for a few of the largest eigenvalues. To prove that the rest of the eigenvalues are genuinely random, we test for universal properties such as eigenvalue spacings and eigenvalue correlations. We demonstrate that [Formula: see text] shares universal properties with the Gaussian orthogonal ensemble of random matrices. In addition, we quantify the number of significant participants, that is companies, of the eigenvectors using the 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.


Author(s):  
Thomas Chinwe Urama ◽  
◽  
Patrick Oseloka Ezepue ◽  
Peters Chimezie ◽  
◽  
...  

2000 ◽  
Vol 287 (3-4) ◽  
pp. 374-382 ◽  
Author(s):  
V Plerou ◽  
P Gopikrishnan ◽  
B Rosenow ◽  
L.A.N Amaral ◽  
H.E Stanley

2017 ◽  
Vol 07 (02) ◽  
pp. 291-307 ◽  
Author(s):  
Thomas Chinwe Urama ◽  
Patrick Oseloka Ezepue ◽  
Chimezie Peters Nnanwa

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