首页> 外文期刊>Fluctuation and Noise Letters: FNL: An Interdisciplinary Scientific Journal on Random Processes in Physical, Biological and Technological Systems >Market Correlation Structure Changes Around the Great Crash: A Random Matrix Theory Analysis of the Chinese Stock Market
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Market Correlation Structure Changes Around the Great Crash: A Random Matrix Theory Analysis of the Chinese Stock Market

机译:大崩盘前后的市场关联结构变化——基于中国股市的随机矩阵理论分析

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摘要

The correlation structure of a stock market contains important financial contents, which may change remarkably due to the occurrence of financial crisis. 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 Chinese stocks. 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.
机译:股票市场的关联结构包含重要的金融内容,这些内容可能会因金融危机的发生而发生显着变化。我们基于对1228只中国股票的高频股票回报的随机矩阵分析,对2008年危机发生前后的中国股市进行了比较分析。研究了一年两个时间段内与市场指数相关的原始相关矩阵和偏相关矩阵。我们发现,2008年中国股票的平均相关性和偏相关性比2007年更强,平均偏相关性明显弱于各时期的平均相关性。因此,在每个周期内,相关矩阵的最大特征值都显著大于偏相关矩阵的特征值。此外,每个最大的特征值及其特征向量都反映了明显的市场效应,而其他偏离的特征值则没有。我们没有发现任何证据表明偏离特征值包含工业部门信息。令人惊讶的是,2007年第二大特征值和2008年第三大特征值的特征向量能够将股票与两个交易所区分开来。我们还发现,一些最大的特征向量的分量大小与股票的资本化成正比。

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