Fund Network Centrality and Stock Price Informativeness: A Mechanism Study Based on Information Transmission and Governance Effects

Abstract

Using Chinese A-share listed companies from 2014 to 2024 as the sample, this paper constructs a mutual shareholding network of public mutual funds based on complex network theory. It employs social network analysis to measure fund network centrality and empirically examines its impact on stock price informativeness as well as the underlying mechanisms. The results show that fund network centrality significantly reduces stock price informativeness: higher network centrality is associated with stronger stock price synchronicity and lower efficiency in incorporating firm-specific information into prices. This conclusion remains robust after a series of robustness checks, including lagging the explanatory variable by one period, propensity score matching, and excluding special years. Heterogeneity analysis reveals that the negative effect is more pronounced in small-scale firms and in regions with lower levels of marketization, indicating that weaker information environments amplify homogeneous trading behavior among networked institutions. Mechanism analysis explores two potential channels of influence: first, the “information crowding-out” channel, whereby fund network centrality may weaken analysts’ incentives for information discovery and firm monitoring; second, the “agency cost” channel, whereby network centrality may increase the likelihood of collusion between management and institutional investors, thereby raising agency costs and suppressing the release of firm-specific information. This study extends the research framework on capital market pricing efficiency from a micro-network perspective and provides policy implications for regulators to identify and mitigate market risks arising from coordinated institutional behavior.