Market correlation structure changes around the Great Crash

TL;DR

This study analyzes how the correlation structure of the Chinese stock market changed around the 2008 financial crisis using high-frequency data and random matrix theory, revealing shifts in market and sector effects.

Contribution

It provides a comparative analysis of correlation and partial correlation matrices before and after the 2008 crisis, highlighting eigenvalue and eigenvector changes and their relation to market effects.

Findings

Higher average correlation and partial correlation in 2008 compared to 2007.

Largest eigenvalue reflects market-wide effects, with eigenvectors distinguishing exchanges.

Eigenvector component magnitudes relate to stocks' capitalizations.

Abstract

We perform a comparative analysis of the Chinese stock market around the occurrence of the 2008 crisis based on the random matrix analysis of high-frequency stock returns of 1228 stocks listed on the Shanghai and Shenzhen stock exchanges. Both raw correlation matrix and partial correlation matrix with respect to the market index in two time periods of one year are investigated. We find that the Chinese stocks have stronger average correlation and partial correlation in 2008 than in 2007 and the average partial correlation is significantly weaker than the average correlation in each period. Accordingly, the largest eigenvalue of the correlation matrix is remarkably greater than that of the partial correlation matrix in each period. Moreover, each largest eigenvalue and its eigenvector reflect an evident market effect, while other deviating eigenvalues do not. We find no evidence that deviating eigenvalues contain industrial sectorial information. Surprisingly, the eigenvectors of the second largest eigenvalues in 2007 and of the third largest eigenvalues in 2008 are able to distinguish the stocks from the two exchanges. We also find that the component magnitudes of the some largest eigenvectors are proportional to the stocks' capitalizations.