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.
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.
