文献类型：期刊文献

英文题名：Dynamic Evolution of Cross-Correlations in the Chinese Stock Market

作者：Ren, Fei[1,2,3];Zhou, Wei-Xing[1,2,3]

机构：[1]E China Univ Sci & Technol, Sch Business, Shanghai 200237, Peoples R China;[2]E China Univ Sci & Technol, Sch Sci, Shanghai 200237, Peoples R China;[3]E China Univ Sci & Technol, Res Ctr Econophys, Shanghai 200237, Peoples R China

年份：2014

卷号：9

期号：5

外文期刊名：PLOS ONE

收录：MEDLINE(收录号：24867071);;WOS:【SSCI(收录号:WOS:000336914100022)，SCI-EXPANDED(收录号:WOS:000336914100022)】；PubMed;

基金：This work was partially supported by the National Natural Science Foundation (Nos. 10905023, 11075054 and 71131007), Humanities and Social Sciences Fund sponsored by Ministry of Education of the People's Republic of China (No. 09YJCZH042), the Shanghai (Follow-up) Rising Star Program Grant 11QH1400800, the Zhejiang Provincial Natural Science Foundation of China (Nos. Z6090130 and Y6110687), and the Fundamental Research Funds for the Central Universities. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

语种：英文

摘要：The analysis of cross-correlations is extensively applied for the understanding of interconnections in stock markets and the portfolio risk estimation. Current studies of correlations in Chinese market mainly focus on the static correlations between return series, and this calls for an urgent need to investigate their dynamic correlations. Our study aims to reveal the dynamic evolution of cross-correlations in the Chinese stock market, and offer an exact interpretation for the evolution behavior. The correlation matrices constructed from the return series of 367 A-share stocks traded on the Shanghai Stock Exchange from January 4, 1999 to December 30, 2011 are calculated over a moving window with a size of 400 days. The evolutions of the statistical properties of the correlation coefficients, eigenvalues, and eigenvectors of the correlation matrices are carefully analyzed. We find that the stock correlations are significantly increased in the periods of two market crashes in 2001 and 2008, during which only five eigenvalues significantly deviate from the random correlation matrix, and the systemic risk is higher in these volatile periods than calm periods. By investigating the significant contributors of the deviating eigenvectors in different time periods, we observe a dynamic evolution behavior in business sectors such as IT, electronics, and real estate, which lead the rise (drop) before (after) the crashes. Our results provide new perspectives for the understanding of the dynamic evolution of cross-correlations in the Chines stock markets, and the result of risk estimation is valuable for the application of risk management.