机构投资者信息共享与股价崩盘风险——基于社会关系网络的分析

Institutional Investors Information-Sharing and Stock Crash Risk

机构投资者之间除了信息竞争,在很多情况下还会选择共享信息。信息共享提高了市场定价效率,从而对于股价崩盘风险具有重要影响。本文采用社会关系网络结构变量来衡量信息共享效率,基于2004—2017年我国A股市场与公募证券投资基金数据对于机构投资者之间的信息共享对于股价崩盘风险的影响进行了实证检验。研究表明:机构投资者信息共享降低了股价崩盘风险,市场定价效率的提升是其中重要的作用路径;随着机构投资期限的延长,信息共享降低股价崩盘风险的作用将得到增强;机构投资者之间的信息共享提高了股价的短期特质波动,降低了股价的长期特质波动。本文从社会关系网络的视角探讨了私有信息及其传播对于机构投资者决策以及股价的影响,为股价崩盘风险影响因素研究提供了新的视角。

There is not only information competition among institutional investors,but also cooperation,which is particularly common for transactional institutional investors,such as public securities investment funds.Information sharing can improve the pricing efficiency for the market,which could eliminate information asymmetry between managements and investors to a certain extent.So it could reduce the crash risk for individual stock.The social network between the investors is the main way to obtain private information for them.Investors usually actively acquire information through social relations when making decisions.Much survey and empirical research show that the institutional investors who hold the same shares massively would like share information.So we assume that there are private information exchanges between the funds holding the same shares in heavy positions.This paper measures the efficiency for information sharing by the structural characteristic variables of social network,such as degree centrality,density,and cluster.Based on the data of China A-share market and public securities investment funds from 2004 to 2017,it makes an empirical analysis on the relationship between information sharing and the crash risk for individual stock.The main conclusions are as follows:Firstly,there is a significant positive correlation between information sharing and pricing efficiency for the market,which implies information sharing between institutional investors maybe promote the pricing efficiency.Meanwhile there is a significant negative correlation between information sharing and crash risk,that is,information sharing may reduce the crash risk.Moreover,market pricing efficiency is an important intermediary variable between them.This may be because the information sharing improves the comprehensiveness,accuracy and instantaneity of information for the market.Secondly,with the extension of investment term,the role of information sharing in reducing the crash risk will be strengthened.This may be due to the fact that institutional investors with longer term are more dependent on private information,so information sharing has a greater impact on their behavior.Thirdly,information sharing improves the short-term volatility of stock prices and reduces the long-term volatility of stock prices.This may be because information sharing among institutional investors improves the consistency of their trading operations,which has a short-term impact on stock prices.However,in the long run,information sharing can improve the effectiveness of the market and inhibit the volatility of stock price.In this paper,the social network is introduced into the research on behavior of institutional investors,and the relationship between information sharing and the crash risk.It expands the research on the impact of institutional investors on the crash risk and the stability of stock market.From the perspective of social network,this paper explores the impact of private information and its dissemination on institutional investors decision-making and stock prices,which also provides a new perspective for the study of factors affecting the crash risk.In addition,based on the research methods and conclusions of this paper,it can help regulators identify institutional investors who have important impact on market stability and take targeted measures to stabilize the market.They can identify institutional investors who play an important role in information transmission and supervise them pertinently.Information sharing can improve market pricing efficiency,but the regulators should pay close attention to whether institutional investors who are more closely connected in the information network are suspected of collusion and manipulation.