Joint Ownership and Investment Behaviors of Mutual Funds and Stock Crash Risk
ZENG Wei, XU Zhong, LI Shangchen, SHEN Ji, WANG Chong
China Investment Corporation National;
Association of Financial Market Institutional Investors;
Center for Financial Innovation and Development;
The University of Hong Kong Guanghua School of Management, and Key Laboratory of Mathematical
Economics and Quantitative Finance (Peking University);
Peking UniversityGuanghua School of Management, Peking University
Summary:
China's stock market is facing a severe problem of excessive stock price volatility. The mutual fund industry in China has experienced remarkable growth over the past two decades. In April 2022, the China Securities Regulatory Commission (CSRC) issued opinions promoting the high-quality development of the mutual fund industry and emphasized the importance of mutual funds in serving the capital market. However, anecdotal reports of panic selling by mutual funds raise concerns about the potential impact of public mutual funds on the stock price crash risk. Research primarily focuses on the role of information asymmetry in explaining stock price crash risks, suggesting that institutional investors influence this risk through mechanisms such as corporate governance, collusion, or information mining, which affect the transparency of the information environment and the release of negative news (Chen et al., 2001; Jin and Myers, 2006; Callen and Fang, 2013). However, another direct mechanism, namely competitive trading behavior in response to negative news, may be at play. To illustrate this new perspective, the paper first constructs a continuous-time trading model with multiple institutional investors. The real-time asset price is set to consist of three important components. The first component represents the trading needs of uninformed noise traders and is modeled as white noise with no drift term. The second component captures the permanent price impact, which is related to inventory in the hands of institutional investors. The third component captures the transitory price pressure from instantaneous trading. Each institutional investor with a mean-variance utility function determines their individual trading speed to maximize the expected payoff in a given period of time. The optimal dynamic trading trajectory for each participant is derived, and the asset price dynamics are characterized as a result of aggregation. Given the total position adjustment for the group of institutional investors, the asset price skewness is then easily obtained as an equilibrium outcome. Using the model, we then study a case wherein the optimal liquidation position for each participant can be endogenized and explore whether the stock holdings distributed among institutional investors may affect the stock price crash risk. We empirically test hypotheses derived from the theoretical model using quarterly data on reported holdings of stock mutual funds in China from 2010 to 2022. The results show a significant positive correlation between the proportion of fund ownership and the stock price crash risk. When negative signals such as downgrades of stock ratings or earnings forecasts by sell-side analysts occur, funds tend to reduce their holdings. Moreover, a higher proportion of joint ownership among funds leads to a stronger negative market reaction and greater stock price crash risk. To further illustrate the competitive selling mechanism among mutual funds, we analyze the impact of the number of funds holding stock and the concentration of their ownership on stock divestments. Our findings reveal that a higher number of funds holding a stock indicates a stronger willingness to sell in response to negative news, while a higher concentration among holding funds is associated with a lower propensity for competitive selling. Consistent with the predictions of the theoretical model, we examine how fund characteristics and stock features influence the relationship between fund holdings and the stock price crash risk. The results indicate that the impact of fund holdings on stock price crash risk is stronger when a larger number of funds hold the stock and their shares are more evenly distributed. Additionally, a long investment horizon and reduced short-term performance pressure among holding funds help mitigate the impact of fund holdings on the stock price crash risk. Furthermore, we find that stock return volatility dampens the influence of fund holdings on the stock price collapse risk. This paper contributes to the literature in several ways. First, it provides a new perspective on how the competitive selling behavior of mutual funds in response to negative information increases the stock price crash risk, thereby contributing to the academic debate on the role of institutional investors. Second, it develops a competitive selling model for investors to assess the impacts of fund holding concentration and stock volatility on the stock price crash risk. Third, it finds that the investment horizon and short-term performance pressure are important factors influencing the relationship between fund holdings and the stock price crash risk. These findings not only enrich the empirical discussion on whether mutual funds exacerbate or mitigate the stock price crash risk but also provide valuable insights into the regulation of the mutual fund industry.
[1] 曹丰、鲁冰、李争光和徐凯,2015,《机构投资者降低了股价崩盘风险吗？》,《会计研究》第11期,第55～61+97页。 [2] 陈新春、刘阳和罗荣华,2017,《机构投资者信息共享会引来黑天鹅吗？——基金信息网络与极端市场风险》,《金融研究》第7期,第140～155页。 [3] 董纪昌、庞嘉琦、李秀婷和董志,2020,《机构投资者持股与股价崩盘风险的关系——基于市场变量的检验》,《管理科学学报》第3期,第73～88页。 [4] 高昊宇、杨晓光和叶彦艺,2017,《机构投资者对暴涨暴跌的抑制作用:基于中国市场的实证》,《金融研究》第2期,第163～178页。 [5] 孔东民、刘莎莎和谭伟强,2019,《分析师评级与投资者交易行为》,《管理世界》第1期,第167～178+228页。 [6] 孔东民和王江元,2016,《机构投资者信息竞争与股价崩盘风险》,《南开管理评论》第5期,第127～138页。 [7] 彭俞超、倪骁然和沈吉,2018,《企业“脱实向虚”与金融市场稳定——基于股价崩盘风险的视角》,《经济研究》第10期,第50～66页。 [8] 祁斌、黄明和陈卓思,2006,《机构投资者与股市波动性》,《金融研究》第9期,第54~64页。 [9] 史永东和王谨乐,2014,《中国机构投资者真的稳定市场了吗？》,《经济研究》第12期,第100～112页。 [10] 吴晓晖、郭晓冬和乔政,2019,《机构投资者抱团与股价崩盘风险》,《中国工业经济》第2期,第117～135页。 [11] 许年行、于上尧和伊志宏,2013,《机构投资者羊群行为与股价崩盘风险》,《管理世界》第7期,第31～43页。 [12] 尹海员和朱旭,2022,《机构投资者信息挖掘、羊群行为与股价崩盘风险》,《管理科学学报》第2期,第69～88页。 [13] 朱菲菲、吴偎立和杨云红,2023,《ETF、股票流动性与股价崩盘风险》,《金融研究》第6期,第169～186页。 [14] Alexander, G.J., G. Cici and S. Gibson, 2007, “Does motivation matter when assessing trade performance？ An analysis of mutual funds”, The Review of Financial Studies, 20(1), pp.125～150. [15] Almgren, R. and N. Chriss, 2001, “Optimal execution of portfolio transactions”, Journal of Risk, 3(2), pp.5～40. [16] Bertsimas, D. and A.W. Lo, 1998, “Optimal control of execution costs”, Journal of Financial Markets, 1(1), pp.1～50. [17] Boguth, O. and M. Simutin, 2018, “Leverage Constraints and Asset Prices: Insights from Mutual Fund Risk Taking”, Journal of Financial Economics, 127(2), pp. 325～341. [18] Brown, G.W., P. Howard and C.T. Lundblad, 2022, “Crowded trades and tail risk”, The Review of Financial Studies, 35(7), pp.3231～3271. [19] Callen, J. L. and X. Fang, 2013, “Institutional Investor Stability and Crash Risk: Monitoring Versus Short-termism？”, Journal of Banking＆Finance, 37(8), pp. 3047～3063. [20] Carlin, B.I., M. S. Lobo and S. Viswanathan, 2007, “Episodic Liquidity Crises: Cooperative and Predatory Trading”, Journal of Finance, 62, pp. 2235～2274. [21] Chen, J., H. Hong and J. C. Stein, 2001, “Forecasting Crashes: Trading Volume, Past Returns, and Conditional Skewness in Stock Prices”, Journal of Financial Economics, 61(3), pp. 345～381. [22] Coval, J. and E. Stafford, 2007, “Asset fire sales (and purchases) in equity markets”, Journal of Financial Economics, 86(2), pp.479～512. [23] DeMarzo, P.M. and B. Uroševic, 2006, “Ownership dynamics and asset pricing with a large shareholder”, Journal of Political Economy, 114(4), pp.774～815. [24] Gabaix, X., P. Gopikrishnan, V. Plerou and H. E. Stanley, 2006, “Institutional Investors and Stock Market Volatility”, Quarterly Journal of Economics, 121(2), pp. 461～504. [25] Jin, L. and S. C. Myers, 2006, “R2 Around the World: New Theory and New Tests”, Journal of Financial Economics, 79(2), pp. 257～292. [26] Liu, J., R. F. Stambaugh and Y. Yuan, 2019, “Size and Value in China”, Journal of Financial Economics, 134(1), pp. 48～69. [27] Oehmke, M., 2014, “Liquidating Illiquid Collateral”, Journal of Economic Theory, 149, pp. 183～210. [28] Stickel, S. E., 1989, “The Timing of and Incentives for Annual Earnings Forecasts Near Interim Earnings Announcements”, Journal of Accounting and Economics, 11(2-3), pp. 275～292. [29] Vayanos, D., 1998, “Transaction Costs and Asset Prices: A Dynamic Equilibrium Model”, Review of Financial Studies, 11, pp.1～58.
