Summary:
Institutional investors often share information with and learn from others in the market. This information interaction promotes the dissemination of private information among investors, and can directly affect their decision-making and asset pricing. Thus, research on the impact and mechanism of the information interaction among investors can help explain the behavior of institutional investors and some of the anomalies in asset pricing. Based on social network theory, this paper empirically analyzes how the information interaction between funds influences their decision-making and stock pricing. First, this paper uses Pareek’s (2009) method to establish the fund information networks. Specifically, if two funds are heavy holders of the same shares, they are deemed to be “connected.” In this way, all of the funds connected to a fund constitute its information network. An information network is a typical social network based on the exchange of information, which can be regarded as the scope and medium of the information interaction. Second, we examine the relationship between the position decision-making of funds and that of the members of their information networks. This relationship can be considered to reflect the influence of the information interaction in controlling public information. We further consider whether the effects of the information interaction under different decision-making scenarios and market situations are significant and different. We then divide the effects of the information interaction into the effects in the same city and different cities, and test whether there are any significant differences. Finally, we test whether the effects of the information interaction vary in terms gender, length of service of fund managers, and size of the information networks. In addition, we build a stock information network based on the fund information network to study how the information interaction affects the stock pricing. A stock’s information network is composed of all of the funds that are heavy holders of this stock and their information network members. The structural characteristics of the network determine the efficiency of the information sharing among the funds. We verify the impact of the information sharing on stock prices and its mechanism by examining the relationships between the structural characteristics, pricing efficiency, and stock prices. Our sample comprises all of the A-share listed companies on the Shanghai and Shenzhen Stock Exchanges from the first quarter of 2005 to the fourth quarter of 2018 and the equity and mixed open-ended funds. The data on the positions of the funds are from the Wind database. The financial data on the listed companies, the stock transaction data, and the basic information about the funds are all from the CSMAR database. The results show that information interaction has a significant impact on the funds’ position decision-making, and the impact is significantly different under different decision-making scenarios and market situations. In addition, the subjective factors (fund managers’ gender and length of service) and objective factors (size of the information networks) influence the effect of the information interaction. In Beijing, Guangzhou, and Shenzhen, the effects of other cities are significantly greater than those of the same city, while the case is the opposite in Shanghai.Moreover, information sharing reduces the long-term idiosyncratic volatility of the stock prices, and the pricing efficiency of the stock market plays a mediating role. This paper extends the application of social network theory to research on financial markets by exploring the relationship between decision-making on individual investments and the corresponding market performance. Our findings contribute to our understanding of the decision-making of institutional investors and means of controlling the market risk caused by herding behavior. Our quantitative findings regarding the information interaction among institutional investors can help regulators identify the “head sheep” of funds in the market and avoid irrational and excessive behavioral synergies. We also discuss the factors that influence the information interaction of funds, which can help the regulators to track the transmission of public and private information among institutional investors, prevent and monitor insider trading and stock price operations, and establish fair competition in the market.
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