We examine two forward-looking mutual fund ratings: the analyst rating produced by human analysts and the quantitative rating generated by a machine learning technique. The analyst rating identifies outperforming funds, while the quantitative rating fails to do so—this difference is mostly due...

We propose a new measure of fund investment skill, Active Fund Overpricing (AFO), encapsulating the fund's active share of investments, the direction of fund active bets with regard to mispriced stocks, and the dispersion of mispriced stocks in the fund's investment opportunity set. We find that...

A basic intuition is that arbitrage is easier when markets are most liquid. Surprisingly, we find that momentum profits are markedly larger in liquid market states. This finding is not explained by variation in liquidity risk, time-varying exposure to risk factors, or changes in macroeconomic...

This paper shows that investments based on deep learning signals extract profitability from difficult-to-arbitrage stocks and during high limits-to-arbitrage market states. In particular, excluding microcaps, distressed stocks, or episodes of high market volatility considerably attenuates...

We show that mutual funds report their junior stakes in startups at 43% higher valuation than model fair values that consider multi-tier capital structures of startups. The latest-issued and most senior security is worth 48% per share than junior securities held by mutual funds, implying that...

We show that mutual funds report their junior stakes in startups at 43% higher valuation than model fair values that consider multi-tier capital structures of startups. The latest-issued and most senior security is worth 48% per share than junior securities held by mutual funds, implying that...