Comparison between the eigenvalues of empirical correlation matrix and surrogate random correlation matrix.

<p>The black circled line is the 99th percentile of the eigenvalues of the shuffled return series. The return series in each moving window is randomized by shuffling for 10 times. The red squared line is the number of the empirical eigenvalues significantly larger than those of the shuffled data, which are the eigenvalues larger than the 99th percentile of the eigenvalues of the shuffled data. The blue solid line shows the A-share Index of Shanghai Stock Exchange, scaled by a factor 0.005.</p

Dynamics of eigenvalue distribution.

<p>Probability density function (PDF) of the eigenvalues obtained from the correlation matrix of the return series of 367 A-Share stocks evolved with the time .</p

Dynamics of correlation coefficient distribution.

<p>Probability density function (PDF) of the correlation coefficients calculated from the return series of 367 A-Share stocks evolved with the time .</p

Figure 9

<p>(a). Contribution of conventional industries. for obtained from the correlation matrix of the return series of 367 A-Share stocks evolved with time . (b). Contribution of conventional industries. for obtained from the correlation matrix of the return series of 367 A-Share stocks evolved with time . (c). Contribution of conventional industries. for obtained from the correlation matrix of the return series of 367 A-Share stocks evolved with time . (d). Contribution of conventional industries. for obtained from the correlation matrix of the return series of 367 A-Share stocks evolved with time .</p

Dynamics of Cumulative Risk Fraction (CRF).

<p>CRF is measured by the eigenvalues obtained from the correlation matrix of the return series of 367 A-Share stocks within a moving window of length 400 days. Different lines correspond to the proportions of total variance explained by PC 1, PC 1-10, PC 1-50, and PC 1-367. PC 1 denotes the principal component corresponding to the largest eigenvalue .</p

Enlarged eigenvalue distribution.

<p>Partial enlarged drawing of eigenvalue distribution for .</p

Largest ten components of deviating eigenvectors in period from 06/09/2000 to 02/04/2003.

<p>Largest ten components of , , , and by the average ranks of the eigenvector components taken over the moving windows with ending dates from 06/09/2000 to 02/04/2003. The eigenvectors are obtained from the correlation matrices of the return series in these moving windows. The stock codes corresponding to the largest ten components, the industries they belonging to, and the industry codes are listed.</p

Largest ten components of deviating eigenvectors in period from 25/12/2006 to 13/01/2009.

<p>Largest ten components of , , , and by the average ranks of the eigenvector components taken over the moving windows with ending dates from 25/12/2006 to 13/01/2009. The eigenvectors are obtained from the correlation matrices of the return series in these moving windows. The stock codes corresponding to the largest ten components, the industries they belonging to, and the industry codes are listed.</p

Projection of the 367 stock returns on the largest eigenvector .

<p> obtained from the correlation matrices of the return series in the moving windows ended on 06/09/2000, 02/04/2003, 25/12/2006, 13/01/2009, 11/05/2010, and 30/12/2011, as a function of the return of the A-share Index of Shanghai Stock Exchange. The A-share Index is composed of all the A-share stocks listed on the Shanghai Stock Exchange. Curves are removed for clarity. A linear regression between the two normalized axes for different moving windows yields slopes: 0.99, 0.99, 0.88, 0.88, 0.90, and 0.91.</p

Contribution of conventional industries.

<p> for obtained from the correlation matrix of the return series of 367 A-Share stocks evolved with time .</p