The Information Content of the Financial Cross Correlation Matrix: Evidence from Shanghai Stock Exchange

We use methods of random matrix theory (RMT) to investigate the information content of the cross correlation matrix C of Shanghai stock exchange (SSE) for the period Jan 2, 2001 to May 30, 2008. We find that, the statistics of most of the eigenvalues in the spectrum of C agree with the predictions of random matrix theory, 92.6% of the eigenvalues fall within the RMT bounds, and the eigenvalues within the bounds agree with the universal properties of random matrix, implying a large degree of noise in the empirically measured cross correlation coefficients. We also find a characteristic difference between properties of SSE and other exchange, SSE has a particularly high value of the largest eigenvalues of 209.26, which is about 89 times larger than the theorical upper bound. The high value of the largest eigenvalue of C may be attributed to the fact that, the stocks in China are often influenced by some common factors that affects the ldquoentire marketrdquo.