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机构地区:[1]西南交通大学经济管理学院,四川成都610031
出 处:《管理工程学报》2013年第3期20-26,共7页Journal of Industrial Engineering and Engineering Management
基 金:国家自然科学基金重大资助项目(71090402);国家自然科学基金资助项目(71171170);中央高校基本科研业务费专项资金资助乡(SWJTU11CX088);教育部人文社科资助项目(09YJA790169;09YJCZH103;09XJC630013)
摘 要:本文从信息扩散和关联交易的角度,实证研究股东联结网络对股价联动关系的影响。本文发现:股东联结网络对股价联动关系有显著正向影响,股票间的股东联结越强,则股票间的相关系数越大,股东联结网络反映了股票间关联交易联结和信息扩散路径而影响股价联动关系,同时行业、公司规模和市盈率特征也是股价联动关系的影响因素,同行业、公司规模和市盈率特征越相似的公司,其股价联动越紧密。进一步研究表明:越处于股东联结网络中心位置、价格越低和每股收益越高的股票,其股价走势对其他股票股价走势的影响更大。实证结果意味着投资者组合配置内生性的影响股票市场的联动关系结构。The degree of correlation between securities goes far beyond the influence of economic fundamentals. This excessive co- movement may have issues because of its significant effect on financial theory and practice. Existing studies suggest that the market segmentation in institutional investors is an important factor to lead the excessive co-movement, but there is still lack of adequate knowledge about how the market segmentation can lead to the excessive co-movement. This paper discusses the effect of investors in the stock price co-movement from the perspectives of information diffusion and correlation trade, and considers that information diffusion and correlation trade are internal factors of the excessive co-movement phenomenon in stock price. Different stocks with the same major shareholders make the stocks interconnected and finally form the stock network. This stock network reflects the information diffusion path of major shareholders on one side, and reflects the correlated trade relation of major shareholders configuration stocks in portfolio investment on the other side. This specific information diffusion path and correlation trade that caused by the investors relations will lead to the excessive co-movement in stocks. This paper has an empirical analysis of the relevant data about 300 samples shares of Shanghai and Shenzhen in 2008. This paper expresses the stocks co-movement by stock correlation matrix and extends the direct relationship between individuals to the relationship of group network path in the co-movement relationship research. This study builds an interpretation model of the co-movement relationship matrix of stock groups to understand the effect of shareholders correlation matrix on the stocks' co-movement. This model uses the stock correlation matrix as the dependent variable, and uses the stock industry relationship matrix, difference of scale matrix, price matrix differences, similarity of PE ratio matrix, and others as the explanatory variable. In order to further study the effec
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