Using “the Measures for the Administration of Bank Wealth Management (henceforth BWM) Funds Sales” as an exogenous shock in fund distribution channels in Chinese BWM industry, we investigate the impact of non-affiliated distribution on fund performance. We find that the adoption of non-affiliated distribution brokers has a positive effect on BWM fund performance. We further find that the effect is more pronounced when the non-affiliated distribution broker has more market power and when the fund issuer has better governance. We interpret our findings to indicate that non-affiliated distribution brokers alleviate the agency problems of fund managers by introducing both ex-ante and ex-post monitoring, highlighting the role of non-affiliated distribution brokers as an external governance mechanism in wealth management industry.

This paper studies the impact of AI technology on the mutual fund industry. I develop a new measure of AI adoption based on hiring practices and find that this measure can predict fund performance. The funds with high AI ratio outperform non-AI funds, after I controlling for standard factors and fund characteristics. Further empirical evidence shows that funds with a high AI ratio tilt their portfolios toward high information intensity stocks, indicating that mutual funds benefit from AI technology adoption by improving their information capacity. Consistent with this channel, I find that the outperformance of these mutual funds mainly comes from better stock picking skills. Finally, AI technology adoption has a negligible effect on fund manager turnover.

We examine the performance of actively managed Chinese mutual Funds over the period 2002-2020. Using the bootstrap-based false discovery technique, we find that 19.25% of Chinese actively managed mutual funds produce positive-alpha, which contrasts with existing studies documented by others in developed markets. Our findings survive a battery of robustness tests. Unlike in developed markets, equilibrium accounting may not hold in China as the Chinese stock market is dominated by retail investors instead of mutual funds, and thus the mutual funds in China can be more skilled at the expense of the retail investors. We find supportive evidence of the applicability of the bootstrap-based false discovery rate method by conducting simulations.

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.

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 evaluate how prior mutual fund working experience affects private fund managers' performance. Using a novel Chinese private fund database from 2012 to 2016, we document significantly lower excess returns and higher left-tail risks for private fund managers with prior mutual fund working experience. Such effect is concentrated in switched managers with lower performance ranks in mutual funds. Additionally, the underperformance is attributable to reduced research support, change in investment styles, and deteriorated market timing skills, while incentive schemes help alleviate such underperformance. Our findings demonstrate the key role of industry-specific human capital in the asset management industry.

We examine global integration in the market for asset management, as indicated by the correlation of mutual fund flows across domiciles. We observe no leading role for the US relative to flows in other domiciles. We do observe a strong global factor in MF flows, and global integration is linked to a market’s business environment, safety from conflict, and political stability. In regional analysis, Europe represents an integrated market for asset management, led by Luxembourg, where asset managers face common flow risks across domiciles. The Asia-Pacific region displays no coherent patterns of correlations across domiciles.

The adequate evaluation of mutual fund performance and of the fund managers’ ability to add value is an issue to which it has been given special attention in the recent financial literature. One of the traditional evaluation measures most commonly used is Carhart's alpha. However, one of the main problems of the evaluation methods that use the beta of the portfolios as a measure of risk and, therefore, Carhart's alpha is its sensitivity to the definition of the market portfolio. In this work we study the importance of defining the market portfolio using Carhart's alpha for a sample of UK mutual funds, and the influence of this market portfolio in the funds´ excess returns and in the performance ranking classification of the fund sample.

Fund managers usually set aside certain amount of cash to pay for possible redemptions, and it is believed that this will affect overall fund performance. This paper examines the properties of efficient portfolios in the mean-variance framework in the presence of a cash account. We show that investors will retain part of funds in cash, as long as the required return is lower than the expected rerun on the portfolio corresponding to the point of intersection of the traditional efficient frontier and the straight line that passes through the minimum-variance portfolio and the origin in the mean-variance plane (portfolio q1 ). In addition, the efficient portfolios determined by our model are proportional to portfolio q1 , and are more efficient than traditional efficient portfolios. Using a simulation, we illustrate that 6% to 9% of total funds are to be retained in the cash account if no-short-selling constraint is imposed. Based on real data, our out-of-sample empirical results confirm the theoretical findings.