This study explores how Chinese mutual fund managers’ degrees of disagreement (DOD) on stock market returns affect investor capital allocation decisions using a novel textbased measure of expectations in fund disclosures. In the time series, the DOD negatively predicts market returns. Cross-sectional results show that investors correctly perceive the DOD as an overpricing signal and discount fund performance accordingly. Flow-performance sensitivity (FPS) is diminished during high dispersion periods. The effect is stronger for outperforming funds and funds with substantial investments in bubble and high-beta stocks, but weaker for skilled funds. We also discuss ffnancial sophistication of investors and provide evidence that our results are not contingent upon such sophistication.

This paper finds that reported fund returns do not necessarily represent the returns of mutual fund investors, especially over long investment periods. We show that mutual fund’s reported returns are calculated using NAV and represent the mutual fund manager’s skill in extracting value from the capital market. However, the real returns earned by mutual fund investors depend not only on the mutual fund manager’s skill but also on the subscription and redemption activities. Using the inflow and outflow information reported in the mutual funds’ semi-annual reports in China, we are able to calculate mutual fund investors’ real returns. We further derive the adjusted gain coefficient (AGC) to capture the difference between the reported mutual fund returns and the mutual fund investors’ real returns. We find that the AGC is significantly lower than 1, which suggests that the real returns of mutual fund investors are significantly lower than reported mutual fund returns in China. The underperformance of mutual fund investors relative to the mutual fund managers they invest in is very persistent and is stronger in more recent years. A further investigation reveals that this underperformance is largely attributed to investors’ poor timing skills and additional fees incurred as a result of excessive subscription and redemption activities. We also identify skilled mutual fund investors using AGC and find that fund managers can benefit from investors’ timing skills. Skilled mutual fund investors flow in when the mutual fund managers have good investment opportunities and flow out when the mutual fund managers have extra cash. The synchronization of the mutual fund investors’ flow and mutual fund managers’ investment strategies can reduce the need for liquidity management and improve mutual fund performance. Using Chinese mutual funds data, we show that a 1% increase in AGC can increase fund riskadjusted return by 0.2% in the next six months.

As many ESG rating agencies have flourished to meet rising interests in ESG investing, we examine the information provider role of these rating agencies. We hypothesize that new ratings can add information useful to investors about rated firms besides any changes to the average level and dispersion in ratings. We exploited the empirical setting where the introduction of various ESG ratings in China is staggered over time and across firms. We show that an increase in the number of ratings by different agencies for a given firm will induce more mutual funds’ investments towards that firm. This is unexplained by rating inflation or rating shopping channels. We further show that such effect is more pronounced when incumbent and entrant agents provide complementary information. For different types of funds, we find different sensitivities to the arrival of new agents in accordance with their explicit requirements for ESG mandate. And interestingly ESG funds that track ESG indices are not responsive to new ratings as ESG indices are sticky in choosing the reference rating. We also provide evidence that the documented effects are not due to endogenous actions taken by incumbent agencies or the firms. Our paper provides interesting and causal evidence of the incremental information from additional ESG ratings which have important implications for the market competition and regulations of ESG rating agencies.

Using four datasets of individuals’ digital payment and mutual fund investment records from a dominating fintech platform, we observe a robust U-shaped relation between individuals’ consumption and their financial wealth shocks. Contrary to the prediction of the wealth effect, individuals increase their consumption shortly after experiencing large positive and negative wealth shocks. The unexpected increase in consumption following negative wealth shocks is particularly pronounced among consumption categories with a “hedonic” nature, such as entertainment-related items. We show that this effect, termed “financial retail therapy,” is consistent with a dynamic model of Prospect Theory and evidence from a controlled laboratory experiment.

Common institutional ownership can enhance knowledge spillovers by increasing portfolio firms’ awareness about each other’s innovation. By investigating listed electronic hardware firms in China for 2000-2016, we find that when common ownership by mutual funds is higher between a firm pair, it is more likely that these two firms cite each other’s patents. To confirm causality, we show that even the exogenous increase in firms’ common ownership following their inclusion into the stock index still positively influences the citing likelihood. We also find that such citations are taken place in a timely manner. Additionally, this positive effect is robust when the effects of overlapping board members and common ownership by other types of institutional investors are controlled for. This effect is more pronounced among nonneighboring firms, when non-neighboring firms are close to their common owners, when common owners hold shares longer, and when firms’ executives have lower incentive to communicate (i.e., SOEs). Last, we find that common ownership by mutual funds also enhances knowledge spillovers through third-party patents. This paper deepens the understanding of knowledge spillovers among firms in developing countries.

We examine the impact of political connections on the investment decisions of Chinese mutual funds. We identify a direct link between mutual funds’ political connections and stocks held from the same political network using hand-collected information on the professional backgrounds of Chinese mutual fund managers and fund management company (FMC) shareholders. While mutual funds tend to allocate more investments to stocks based on their political connections, this effect alleviates somewhat after the 2012 anti-corruption campaign. Our findings suggest that anti-corruption campaigns can help to reduce the political effects of government-related agencies on fund holdings and contribute to better market fairness.

Fund managers’ ability to evaluate risk has important implications for their portfolio management and performance. We use a state-of-the-art deep learning model to measure fund managers’ forward-looking risk assessments from their narrative discussions. We validate that managers’ negative (positive) risk assessments lead to subsequent decreases (increases) in their portfolio risk-taking. However, only managers who identify negative risk generate superior risk-adjusted returns and higher Sharpe ratios, and have better intraquarter trading skills, suggesting that cautious, skilled managers are less subject to overconfidence biases. interestingly, only sophisticated investors respond to the narrative-based risk assessment measure, consistent with limited attention by retail investors.

We uncover a signiffcant relationship between the persistence of marketing and investment skills among U.S. mutual fund companies. Using regulatory filings, we calculate the share of marketing-oriented employees to total employment and reveal alarge heterogeneity in its level and persistence. A framework based on costly signaling and learning helps explain the observed marketing decision. The model features a separating equilibrium in which fund companies’ optimal marketing employment share responds to their past performance differently, conditional on the skill level. We confirm the model prediction that the volatility of the marketing employment share negatively predicts the fund companies’ long-term performance.

Using unique data on Alipay users' investment accounts, we find that, in addition to generating better performance than investors’ self-directed portfolios, robo-advising has a positive spillover effect on its adopters in terms that it improves their investment behaviors. Investors have more diversified portfolios and exhibit fewer behavioral biases in portfolio management and fund choices in their self-directed accounts after adopting robo-advising. The spillover effect is more prominent for adopters who interact with the service more actively and who were less sophisticated before adopting the app. We also find that adopters learn from the robo-advisor by simply imitating its portfolios or strategies. Collectively, this study provides large-sample, non-laboratory evidence that robo-advising effectively plays a role in educating investors through repeated interactions with its adopters and setting investment models that are easy to follow.

As “sin” stocks and “brown” stocks generally earn higher returns than “green” stocks, fund managers face a trade-off between profitability and sustainability preferences when investing in environmental, social and governance (ESG). We explore the investment styles of ESG funds in the Chinese A-share market and analyze the behavior of ESG funds in terms of asset allocation and portfolio adjustment. We find that ESG funds prefer stocks with high return performance over stocks with high ESG performance. Textual analyses of prospectuses reveal a degree of “greenwashing” behavior by ESG funds. Overall, we show that ESG funds not purely ESG-driven.