The Anomaly of Main Inflow and the Information Game of Investors
KANG Qi, GAO Feng, LIU Shuo, WANG Qian, YE Ziwen
Research Bureau of the People's Bank of China; School of Economics and Management, Tsinghua University; School of Economics, Beijing Technology and Business University
Summary:
China's capital markets are characterized by a dominant presence of retail investors, whose trading behavior is frequently blamed for various market anomalies. Contrary to conventional wisdom, this paper examines how the rational decision-making of retail investors actually contributes to the observed main fund anomaly. The paper demonstrates that this phenomenon stems from a rational information game between institutional and retail investors. Our analysis reveals that institutional investors employ large-order trades as informative signals, which retail investors choose to follow to minimize their information acquisition costs. This interaction explains why main fund indicators-derived from large trade data-possess significant predictive power for future returns and can generate substantial alpha when incorporated into investment strategies. The study identifies a novel mechanism behind the main fund anomaly, challenging the prevailing view that such anomalies necessarily result from retail investor irrationality. Our findings offer valuable implications for enhancing market efficiency and anomaly mitigation strategies. Central to our framework is the recognition of information asymmetry in Chinese market, where retail investors face comparatively higher costs in obtaining reliable stock performance information. This environment creates a mutually beneficial “trading surplus” that incentivizes strategic interaction to enhance expected utility: institutions initiate positions through large orders, while retail investors optimally respond by following these signals and buy stocks from institutions. This sequential trading equilibrium generates superior outcomes for both parties compared to scenarios without large-order trading, ultimately producing the observed pattern where large trades systematically precede price increases. The potency of this mechanism varies with “trading surplus” levels. When retail participation is high, institutions can confidently expect sufficient follow-on demand to support their positions, while retail investors benefit from reduced information costs. The trading surplus-comprising expected institutional gains from large-order trading and retail savings from signal following-becomes particularly substantial when large orders convey stronger information content, thereby intensifying the anomaly. Our empirical investigation employs comprehensive A-share market data from 2010-2023, applying careful data filters to ensure robustness. We exclude ST/*ST stocks and the smallest decile by market capitalization to mitigate shell company effects, while implementing standard winsorization procedures (at 1%) to mitigate the effect of extreme values. This study proposes and empirically tests the following hypotheses. First, we verify the existence of significant main fund anomalies in China's stock market (H1): Stocks with higher weekly net main fund inflows demonstrate significantly higher returns in the subsequent holding period. Empirical results confirm the positive predictive power of main fund flows at weekly frequency-a 1% difference in main fund exposure between two stocks predicts an average annualized return spread of 0.63% in the following week. Second, to validate the information game mechanism between institutional and retail investors, we further examine how the main fund anomaly becomes more pronounced in stocks with “greater retail participation” and “stronger large-order signaling effects.” Regarding retail participation, we test through high-low main fund long-short portfolios: H2a posits that the positive correlation between weekly main fund inflows and subsequent returns strengthens during high-market-sentiment periods; H2b suggests this relationship intensifies for stocks with higher Baidu search indices. These hypotheses fundamentally reflect that stocks attracting greater retail attention (evidenced by elevated market sentiment or search frequency) exhibit higher relative retail investor participation. Concerning the signaling role of large orders, we establish: H3a shows the main fund-return relationship strengthens for large-cap stocks, where informed traders more strategically employ large orders; H3b demonstrates this effect amplifies in stocks with higher institutional ownership. The underlying logic is that for large-cap, institutionally-dominated stocks, information holders preferentially use large orders to convey signals, thereby enhancing the informational content of these trades. The study identifies high retail participation and information asymmetry as key drivers of the main fund anomaly—a manifestation of market inefficiency—and proposes several measures to enhance market efficiency. First, reducing information asymmetry through stricter disclosure requirements for listed firms and improved trading data transparency would help narrow the informational gap between retail and institutional investors. Second, encouraging retail investors to channel their investments through institutional intermediaries (e.g., mutual funds) could mitigate the inefficiencies arising from their inherent informational disadvantages, even though their trading behavior remains rational. Additionally, given that existing research faces challenges in linking large trades and main fund flows to institutional activity due to limited disclosure, our novel factor construction method provides a clearer connection, aiding both academic research and regulatory oversight. Beyond advancing the understanding of market anomalies, this work offers actionable policy insights to promote a more efficient and transparent stock market.
康琦, 高峰, 刘硕, 王倩, 叶子文. 主力资金异象和投资者信息博弈[J]. 金融研究, 2025, 535(1): 189-206.
KANG Qi, GAO Feng, LIU Shuo, WANG Qian, YE Ziwen. The Anomaly of Main Inflow and the Information Game of Investors. Journal of Financial Research, 2025, 535(1): 189-206.
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