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The influence of the social networks of fund managers on the herding behavior of SIFs in China

Economics

The influence of the social networks of fund managers on the herding behavior of SIFs in China

L. Wang, Y. Wang, et al.

This intriguing study by Liang Wang, Yuanfei Wang, and Bixiao Li delves into how fund managers' social networks influence the herding behavior of Securities Investment Funds in China. Discover how the size and dynamics of these networks can change investment behavior, shedding light on critical differences related to gender and education levels.

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~3 min • Beginner • English
Abstract
This paper explores the influence of fund managers' social networks on the herding behavior of securities investment funds (SIFs) in China. Using recent data on Chinese SIFs, it adopts the CSAD model to measure herding behavior. Combining indicators such as social network centrality, constraint, and size, the authors construct a regression model to test the influence of fund managers' social networks on SIFs' herding behavior and conduct an empirical study. Heterogeneity is examined by degree of herding behavior, gender, diploma, and region. The results show that: (i) larger social network size of fund managers is associated with a lower degree of herding behavior, while network constraint has no significant effect; (ii) when the overall degree of herding is high, the effect of network size on herding is heterogeneous; (iii) the relationship between male fund managers' social networks and herding is more significant than for female managers (network size significant only for male managers; centrality, constraint and size are not significant for female managers); (iv) the social networks of managers with master’s degrees significantly affect herding behavior, while effects are not significant for those with Ph.D. degrees.
Publisher
Humanities and Social Sciences Communications
Published On
Apr 27, 2023
Authors
Liang Wang, Yuanfei Wang, Bixiao Li
Tags
fund managers
social networks
herding behavior
Securities Investment Funds
China
network influence
heterogeneity
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