Average skewness, which is defined as the average of monthly skewness values across firms, performs well at predicting future market returns. This result still holds after controlling for the size or liquidity of the firms or for current business cycle conditions. We also find that average...

Using a sample of S&P 500 firms between 2013 and 2017, we study the impact of ESG rating disagreement on stock returns. We conjecture that for disagreement about environmental ratings, a risk-based explanation induces a positive relationship between rating disagreement and stock returns. In...

We propose a new asset-pricing framework in which all securities' signals are used to predict each individual return. While the literature focuses on each security's own- signal predictability, assuming an equal strength across securities, our framework is flexible and includes...

We theoretically characterize the behavior of machine learning asset pricing models. We prove that expected out-of-sample model performance—in terms of SDF Sharpe ratio and average pricing errors—is improving in model parameterization (or “complexity”). Our results predict that the best...

This paper develops a new estimation procedure for characteristic-based factor models of security returns. We treat the factor model as a weighted additive nonparametric regression model, with the factor returns serving as time-varying weights, and a set of univariate nonparametric functions...

When investors have incomplete information, expected returns, as measured by an econometrician, deviate from those predicted by standard asset pricing models by including a term that is the product of the stock's idiosyncratic volatility and the investors' aggregated forecast errors. If...

We show that in a consumption-based asset-pricing model with hyperbolic discounting leading to dynamically inconsistent time preferences value premium increases nonlin-early with the degree of discounting and thus affects cross section of returns. To test our model empirically, we relate the...

We document a curious feature of the German mutual fund industry. Unlike U.S. mutual funds, funds domiciled in Germany do not necessarily compute their net asset values (NAV) as of market close. Using a sample of German equity funds, we infer each fund's NAV closing time from the best-fit market...

We report strong evidence that changes of momentum, i.e. "acceleration", defined as the first difference of successive returns, provide better performance and higher explanatory power than momentum. The corresponding Γ-factor explains the momentum-sorted portfolios entirely but not the reverse....