We investigate the role of extreme positive payoffs in the distribution of monthly fund returns in investors’ mutual fund preferences. We document a positive and significant relationship between the maximum style-adjusted monthly return (MAX) and future fund flows. The relationship is robust to controlling for average performance, volatility, skewness, and various other fund characteristics. Our findings are consistent with the notion that fund investors overweight the probability of high payoff states in the past return distribution. We further show that MAX is not a useful predictor of future performance and that an increase in a fund’s visibility does not explain our findings.

ABSTRACT This study shows that the recent trajectory of a firm's profits predicts future profitability and stock returns. The predictive information contained in the trend of profitability is not subsumed by the level of profitability, earnings momentum, or other well-known determinants of stock returns. The profit trend also predicts the earnings surprise one quarter later, and analyst forecast errors over the following 12 months, suggesting that sophisticated investors underreact to the information in the profit trend. On the other hand, we find no evidence of investor overreaction, and our results cannot be explained by well-known risk factors. JEL Classifications: G12; G14.

A higher frequency of positive overnight returns followed by negative trading day reversals during a month suggests a more intense daily tug of war between opposing investor clienteles, who are likely composed of noise traders overnight and arbitrageurs during the day. We show that a more intense daily tug of war predicts higher future returns in the cross section. Additional tests support the conclusion that, in a more intense tug of war, daytime arbitrageurs are more likely to discount the possibility that positive news arrives overnight and thus overcorrect the persistent upward overnight price pressure.

ABSTRACT We examine the relation between insiders’ investment horizon and the information content of their trades with respect to future stock returns. We conjecture that an insider's investment horizon establishes a benchmark for expected patterns of continued trading behavior and thus helps identify unexpected insider trades, which should be more informative in efficient markets. Consistent with this conjecture, the trades of short‐horizon insiders are both more unexpected and more informed, on average, than those of long‐horizon insiders. Short‐horizon insiders and their firms also tend to display characteristics that are associated with a greater focus on short‐termism.

We present new evidence that highlights the role of information intermediaries in the distribution and processing of earnings estimates in capital markets. We find that the time taken to activate an analyst's earnings forecast in the Thomson Reuters Institutional Brokers’ Estimate System is related to measures of investor demand for timely information processing, processing difficulty, and limited attention. Furthermore, we find that forecast announcement returns are muted and post-announcement drift is magnified for forecasts with longer unexpected activation delay and that market inefficiency is concentrated in neglected stocks and potentially exploitable. Finally, analyzing intraday returns, we find that activations facilitate price discovery.

Abstract Efficiency in the capital markets requires that capital flows are sufficient to arbitrage anomalies away. We examine the relation between flows to a quantitative (quant) strategy that is based on capital market anomalies and the subsequent performance of this strategy. When these flows are high, quant funds are able to implement arbitrage strategies more effectively, which in turn leads to lower profitability of market anomalies in the future, and vice versa. Thus, the degree of cross-sectional equity market efficiency varies across time with the availability of arbitrage capital.

We investigate the dual notions that “dumb money” exacerbates well-known stock return anomalies and “smart money” attenuates these anomalies. We find that aggregate flows to mutual funds (dumb money) appear to exacerbate cross-sectional mispricing, particularly for growth, accrual, and momentum anomalies. In contrast, hedge fund flows (smart money) appear to attenuate aggregate mispricing. Our results suggest that aggregate flows to mutual funds can have real adverse allocation effects in the stock market and that aggregate flows to hedge funds contribute to the correction of cross-sectional mispricing.