Robust return efficiency and herding behavior of fund managers

Lu, Shuai; Li, Shouwei; Chen, Ning

doi:10.1016/j.frl.2021.102267

Cited by 5 publications

(3 citation statements)

References 15 publications

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“…Institutional herding and Information Lin et al (2013) found that institutional investors show herding rationally based on superior information. Herding and robust return efficiency (RRE) Lu et al (2022) empirically tested the relationship between herding behavior and robust return efficiency (RRE) and found that fund managers' herding behavior benefits the RRE of their funds.…”

Section: Effect Of Institutional Herding On the Stock Pricementioning

confidence: 99%

Behavioral Biases and their Influence on Investment Decision-Making: A Systematic Literature Review and Future Research Agenda

Paúl¹,

Natarajan²

2023

J. of Law and Sust. Develop.

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Objective: This study aims to systematically review the existing literature published over the past 42 years on behavioral biases in investment decision-making. Therefore, the current study concentrates on two biases: overconfidence and herding bias of individual and institutional investors. Theoretical framework: Kahneman and Tversky (1979) formulated prospect theory and concluded that investors make decisions based on possible gains and losses, rather than on final outcomes. Therefore, this study used this theory to understand the influence of behavioral biases on investment decisions. Methods: This study used a systematic literature review (SLR) and 109 selected articles for review published between 1980 and 2022. Most importantly, this study conducted a content analysis of behavioral biases in investment decision-making. Result and Conclusion: The volume of research on behavioral bias has increased over the past two decades. The existing literature shows limited research on institutional investors’ overconfidence bias, limited studies on individual herding behavior, ineffective direct measures of overconfidence, the majority of research showed that institutional investors are more inclined to herd than individual investors, and the maximum number of studies showed that individual investors are more susceptible to overconfidence bias than institutional investors. Implications of the research: This study highlights the influence of behavioral biases in investment decision-making and suggests a future research agenda for future researchers, as well as helpful to investment advisors enabling them to manage biases and select purposeful stocks for their clientele. Originality/value: This study delineates the behavioral biases of individual and institutional investors. This first study encompasses relevant studies conducted between 1980 and 2022 and lucidly summarizes the behavioral biases, including the ‘overconfidence’ and ‘herding’ tendencies of these different kinds of investors.

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Section: Effect Of Institutional Herding On the Stock Pricementioning

confidence: 99%

Behavioral Biases and their Influence on Investment Decision-Making: A Systematic Literature Review and Future Research Agenda

Paúl¹,

Natarajan²

2023

J. of Law and Sust. Develop.

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“…Market timing entails entering and exiting the market strategically to capitalize on market cycles [17]. Some managers tactically invest in stocks observed to be favored by peers, leveraging mutual funds' capacity for large investments and agility in reacting to market dynamics [18]. Herding behavior not only impacts mutual fund profitability but also influences market volatility, potentially destabilizing markets [19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Does Herding and Anti-Herding Reflect Portfolio Managers’ Abilities in Emerging Markets?

Sheng,

Montgomery

2024

Mathematics

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This study investigates the relationship between herding behaviors and the abilities of Chinese mutual fund managers. Adapting existing methodologies to suit the low information disclosure environment of the Chinese market, we measure herding behaviors and managers’ abilities. Our analysis goes beyond traditional approaches by examining the contribution of herding outcomes to picking and timing abilities linked with mutual fund flows. Moreover, we extend this investigation to incorporate manager replacements and different market conditions. Our findings reveal that moderate herding is associated with enhanced picking abilities, particularly in bull markets. However, this effect is partly counteracted by positive mutual fund flows, suggesting that managers adjust their strategies in response to fund inflows. Excessive herding in bull markets is linked to reduced timing abilities, although this negative impact is mitigated by high turnover. Conversely, managers with anti-herding skills exhibit lower picking abilities. We observe that managerial replacements are driven by poor performance rather than considerations of current abilities. Nonetheless, under a new manager, herding behavior reflects improved picking abilities, indicating a potential shift in managerial strategies. Overall, our study provides valuable insights into the relationship between herding behaviors and managerial competencies in the Chinese mutual fund industry, highlighting the nuances of decision making in different market contexts.

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“…Data from the Wind database shows that, in the first quarter of 2020, the number of single-shareholding funds in the top 20 stocks heavily held by Chinese SIFs both reached 138, with the number of funds holding the top3 Kweichow Moutai (SH600519), Wuliangye (SZ000858), and CATL (SZ300750) being higher than 95. Typically, high returns and low risk are always the goals pursued by fund managers, and thus they may make similar trading decisions based on reputation, compensation, and other considerations, which in turn trigger herding behavior (Lim et al, 2016;Yin, 2016;Lu et al, 2021).…”

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confidence: 99%

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

Wang

2023

Humanit Soc Sci Commun

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This paper explores the influence of fund managers’ social networks on the herding behavior of securities investment funds (SIFs) in China. Using the data of Chinese SIFs in recent years as a sample, it adopts the CSAD model to measure SIFs’ herding behavior. Combining indicators such as social network centrality, constraint, and size, it constructs a regression model of the influence of fund managers’ social networks on the herding behavior of SIFs and conducts an empirical study. The heterogeneity of this influence is investigated in four dimensions, degree of herding behavior, gender, diploma, and region. The results show that: (i) The larger the social network size of fund managers, the lower the degree of herding behavior of fund managers, but the effect of the network constraint on the degree of herding behavior is not significant. (ii) When the degree of herding behavior of SIFs is high, the effect of network size on herding behavior is heterogeneous. (iii) The relationship between the social network of male fund managers and the degree of herding behavior is more significant than that of female fund managers, as network size is significant for male fund managers, while the regression results of social network centrality, network constraint, network size, and the degree of herding behavior of female fund managers are all not significant. (iv) The social network of the fund manager with a master’s degree has a significant impact on the herding behavior of SIFs, which is not significant in fund managers with Ph.D.

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Robust return efficiency and herding behavior of fund managers

Cited by 5 publications

References 15 publications

Behavioral Biases and their Influence on Investment Decision-Making: A Systematic Literature Review and Future Research Agenda

Behavioral Biases and their Influence on Investment Decision-Making: A Systematic Literature Review and Future Research Agenda

Does Herding and Anti-Herding Reflect Portfolio Managers’ Abilities in Emerging Markets?

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

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