[We propose a theory of momentum and reversal based on flows between investment funds. Flows are triggered by changes in fund managers' efficiency, which investors either observe directly or infer from past performance. Momentum arises if flows exhibit inertia, and because rational prices underreact to expected future flows. Reversal arises because flows push prices away from fundamental values. Besides momentum and reversal, flows generate comovement, lead-lag effects, and amplification, with these being larger for high idiosyncratic risk assets. A calibration of our model using evidence on mutual fund returns and flows generates sizeable Sharpe ratios for momentum and value strategies.]

We study the dynamics of an innovative industry in which agents learn about the likelihood of negative shocks. Managers can exert risk prevention effort to mitigate the consequences of shocks. If no shock occurs, confidence improves, attracting managers to the innovative sector. But, when confidence becomes high, inefficient managers exerting low risk-prevention effort also enter. This stimulates growth, while reducing risk prevention. The longer the boom, the larger the losses if a shock occurs. Although these dynamics arise in the first-best, asymmetric information generates excessive entry of inefficient managers, earning informational rents, inflating the innovative sector, and increasing its vulnerability.

We propose a theory of momentum and reversal based on flows between investment funds. Flows are triggered by changes in fund managers' efficiency, which investors either observe directly or infer from past performance. Momentum arises if flows exhibit inertia, and because rational prices underreact to expected future flows. Reversal arises because flows push prices away from fundamental values. Besides momentum and reversal, flows generate comovement, lead-lag effects, and amplification, with these being larger for high idiosyncratic risk assets. A calibration of our model using evidence on mutual fund returns and flows generates sizeable Sharpe ratios for momentum and value strategies.

We study the dynamics of an innovative industry when agents learn about its strength, i.e., the likelihood that it gets hit by negative shocks. Managers can exert risk-prevention effort to mitigate the consequences of such shocks. As time goes by, if no shock occurs, confidence improves. This attracts managers to the innovative sector. But, when confidence becomes high, less managers exerting low risk-prevention effort also enter. This accelerates the growth of the industry, while inducing a decline in risk-prevention. The longer the boom, the stronger the confidence, the larger the losses if a shock occurs. While the above dynamics arise in the first best, with asymmetric information there is excessive entry of inefficient managers, earning informational rents at the expense of efficient managers. This inflates the innovative sector and increases its vulnerability.

We model asset management as a continuum between active and passive: managers can deviate from benchmark indices to exploit noise trader–induced distortions, but agency frictions constrain these deviations. Because constraints force managers to buy assets that they underweight when these assets appreciate, overvalued assets have high volatility, and the risk-return relationship becomes inverted. Distortions are more severe for overvalued assets than for undervalued ones because trading against the former entails more risk and tighter constraints. We provide empirical evidence supporting our model’s main mechanisms. Using the data, we infer the constraints’ tightness and compute a measure of effective arbitrage capital.