Mutual Fund Shareholding Hypernetwork,Resource Effect, and Stock Price Stability
WANG Donghua, DING Jin, ZHANG Yahui, XIN Yang
School of Business, East China University of Science and Technology; School of Finance, Shanghai University of International Business and Economics; Asset Management Association of Shanghai
Summary:
In recent years, China's capital market has faced numerous risks and challenges, highlighting the urgency of preventing and mitigating financial risks. As the cornerstone of long-term capital in the market, mutual funds possess both the ability and the responsibility to enhance capital market stability. However, existing research has not yet fully uncovered the mechanisms through which they stabilize the market, largely because it neglects the network linkages formed by fund shareholding behaviors and their significant implications. Mutual funds, aiming to maximize the overall value of their investment portfolios, influence not only the enterprises in which they invest directly but also generate associative effects among different stocks through their holistic investment strategies. Social network theory suggests that network relationships shape individual behavior and performance. Therefore, examining the impact and pathways of funds' shareholding behaviors on market stability, based on the network connections they establish among enterprises, can provide deeper insights into their role in the market and contribute to enhancing overall market stability. Drawing on social network theory and the hypernetwork model, we use data on A-share listed companies and mutual fund holdings in China from 2015 to 2023 to construct mutual fund shareholding hypernetworks, in which firms serve as nodes and stock portfolios of funds serve as hyperedges. We investigate how the network established by mutual funds among firms affects market stability. The findings reveal that fund shareholding hypernetwork exhibits significant resource effect. Mutual funds promote information exchange and resource sharing along network links among firms and effectively attract market attention, thereby enhancing firms' informational advantages and market attention. The integration of these resources helps firms effectively reduce the risk of extreme stock price fluctuations. During periods of major market instability, firms can still acquire resources through the fund shareholding network, although the mitigating effect of network resources on stock price crash risk becomes weaker. Mechanism analysis shows that network resources primarily stabilize stock prices by improving firms' internal behaviors, such as enhancing information disclosure quality, strengthening corporate social responsibility, and curbing managerial short-termism. Further analysis indicates that the resources in the fund shareholding network can significantly hedge against the stock price risks induced by fund fire sales. Moreover, while mitigating extreme risks, mutual funds also play an active role in boosting market activity. This study offers important policy implications. First, mutual funds should strengthen multi-channel information exchange, continuously improve their capacity to acquire and interpret information, and promote the transmission of value information among firms. Second, mutual funds should actively identify and invest in firms with growth potential that have not yet received sufficient market attention, while also improving the disclosure of shareholding information by explicitly articulating investment rationales. This would help market participants better identify value targets and enhance external monitoring of firms. Third, regulators may leverage the hypernetwork model to monitor the concentration of fund holdings, guide funds toward diversified investment, and thereby improve the allocation efficiency of network resources. Fourth, during periods of severe market volatility, regulators should establish emergency mechanisms to promptly transmit value information to funds and firms, while adopting appropriate measures to support the sustained stabilizing role of funds in the market. Fifth, regulators should further clarify the functional positioning of mutual funds, encouraging them to reasonably foster market activity while closely monitoring excessive stock price fluctuations. This paper contributes to the literature in three ways. First, it expands research on the market impact of mutual fund shareholdings. While prior studies have primarily focused on the effects of funds on individual portfolio firms, we uncover the inter-firm linkages established through fund shareholdings and examine the mechanisms by which such network connections influence market stability. Second, it deepens the understanding of the role of mutual funds. We find that the mutual fund shareholding network exhibits resource effects, and these network resources can effectively mitigate stock price crash risks, thereby identifying a new pathway through which mutual funds contribute to market stability. Third, we innovatively apply the hypernetwork model to the study of fund shareholdings, offering a comprehensive depiction of the complex shareholding structures formed by mutual funds simultaneously holding multiple stocks, thus providing methodological support for future research in this field.
[1]陈名芹、刘星和辛清泉,2017,《上市公司现金股利不平稳影响投资者行为偏好吗？》,《经济研究》第6期,第90～104页。 [2]陈运森,2015,《社会网络与企业效率:基于结构洞位置的证据》,《会计研究》第1期,第48～55+97页。 [3]杜勇、孙帆和邓旭,2021,《共同机构所有权与企业盈余管理》,《中国工业经济》第6期,第155～173页。 [4]冯晓晴和文雯,2022,《国有机构投资者持股能提升企业投资效率吗？》,《经济管理》第1期,第65～84页。 [5]何瑛、陈丽丽和杜亚光,2024,《数据资产化能否缓解“专精特新”中小企业融资约束》,《中国工业经济》第8期,第154～173页。 [6]黄灿和李善民,2019,《股东关系网络、信息优势与企业绩效》,《南开管理评论》第2期,第75～88+127页。 [7]孔东民、刘莎莎、陈小林和邢精平,2015,《个体沟通、交易行为与信息优势:基于共同基金访问的证据》,《经济研究》第11期,第106～119+182页。 [8]寇宗来和千茜倩,2021,《私有信息、评级偏差和中国评级机构的市场声誉》,《金融研究》第6期,第114～132页。 [9]李善民、黄灿和史欣向,2015,《信息优势对企业并购的影响——基于社会网络的视角》,《中国工业经济》第11期,第141～155页。 [10]刘军,2004,《社会网络分析导论》,北京:社会科学文献出版社。 [11]马云飙、武艳萍和石贝贝,2021,《卖空机制能够约束内部人减持吗？——基于融资融券制度的经验证据》,《金融研究》第2期,第171～187页。 [12]潘越、戴亦一和林超群,2011,《信息不透明、分析师关注与个股暴跌风险》,《金融研究》第9期,第138～151页。 [13]邱穆青和白云霞,2019,《官员访问与企业投融资期限错配》,《财经研究》第10期,第138～152页。 [14]孙晓华、郭旭和范世龙,2023,《社会网络、技能提升与就业地选择》,《经济研究》第5期,第116～134页。 [15]索琪和郭进利,2017,《基于超图的超网络:结构及演化机制》,《系统工程理论与实践》第3期,第720～734页。 [16]万良勇和胡璟,2014,《网络位置、独立董事治理与公司并购——来自中国上市公司的经验证据》,《南开管理评论》第2期,第64～73页。 [17]王健、易尚昆、蒋忠中和秦绪伟,2024,《市场情绪与基金投资策略:迎合还是修正？》,《管理科学学报》第3期,第112～132页。 [18]肖欣荣、刘健和赵海健,2012,《机构投资者行为的传染——基于投资者网络视角》,《管理世界》第12期,第35～45页。 [19]杨子晖、王姝黛和梁方,2023,《产业链结构新视角下的尾部风险跨行业传染》,《经济学(季刊)》第1期,第212～227页。 [20]姚颐、刘志远和相二卫,2011,《中国基金在投资中是否追求了价值？》,《经济研究》第12期,第45～58页。 [21]余明桂、夏新平和邹振松,2006,《管理者过度自信与企业激进负债行为》,《管理世界》,第8期,第104～112+125+172页。 [22]于明洋、吕可夫和阮永平,2022,《供应链网络位置与企业竞争地位》,《系统工程理论与实践》第7期,第1796～1810页。 [23]俞庆进和张兵,2012,《投资者有限关注与股票收益——以百度指数作为关注度的一项实证研究》,《金融研究》第8期,第152~165页。 [24]甄红线和王谨乐,2016,《机构投资者能够缓解融资约束吗？——基于现金价值的视角》,《会计研究》第12期,第51～57+96页。 [25]周丽娜、李发旭、巩云超和胡枫,2021,《基于K-shell的超网络关键节点识别方法》,《复杂系统与复杂性科学》第3期,第15～22页。 [26]Aksoy, S.G., C. Joslyn, C. Ortiz Marrero, B. Praggastis and E. Purvine, 2020, “Hypernetwork Science Via High-order Hypergraph Walks”. EPJ Data Science, 9(16), pp.1～34. [27]Barber, B.M. and T. Odean, 2008, “All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors”, The Review of Financial Studies, 21(2), pp.785～818. [28]Berge, C., 1973, Graphs and Hypergraphs, New York: Elsevier. [29]Chuluun, T., A. Prevost and A. Upadhyay, 2017, “Firm Network Structure and Innovation”, Journal of Corporate Finance, 44, pp.193～214. [30]Coval, J. D., and E. Stafford, 2007, “Asset Fire Sales (and Purchases) in Equity Markets”, Journal of Financial Economics, 86(2), pp.479～512. [31]Fang, L. and J. Peress, 2009, “Media Coverage and the Cross-section of Stock Returns”, Journal of Finance, 64(5), pp.2023～2052. [32]Granovetter, M., 1985, “Economic Action and Social Structure: The Problem of Embeddedness”, American Journal of Sociology, 91(3), pp.481～510. [33]He, J., and J. Huang, 2017, “Product Market Competition in a World of Cross-ownership: Evidence from Institutional Blockholdings”, The Review of Financial Studies, 30(8), pp.2674～2718. [34]He, J., J. Huang and S. Zhao, 2019, “Internalizing Governance Externalities: The Role of Institutional Cross-ownership”, Journal of Financial Economics, 134(2), pp.400～418. [35]Hutton, A.P., A.J. Marcus and H. Tehranian, 2009, “Opaque Financial Reports, R2, and Crash Risk”, Journal of Financial Economics, 94(1), pp.67～86. [36]Kang, J.K., L. Luo and H.S. Na, 2018, “Are Institutional Investors with Multiple Blockholdings Effective Monitors”, Journal of Financial Economics, 128(3), pp.576～602. [37]Lee, C.M., S.T. Sun, R. Wang and R. Zhang, 2019, “Technological Links and Predictable Returns”, Journal of Financial Economics, 132(3), pp.76～96. [38]Malmendier, U., and G. Tate, 2008, “Who Makes Acquisitions？ CEO Overconfidence and the Market's Reaction”, Journal of Financial Economics, 89(1), pp.20～43.
