It has been documented that vertical customer-supplier links between industries are the basis for strong cross-sectional stock return predictability (Menzly and Ozbas (2010)).We show that robust predictability also arises from horizontal links between industries, i.e., from the fact that...

Many modern macro finance models imply that excess returns on arbitrary assets are predictable via the price-dividend ratio and the variance risk premium of the aggregate stock market. We propose a simple empirical test for the ability of such a model to explain the cross-section of expected...

We assess financial theory-based and machine learning-implied measurements of stock risk premia by comparing the quality of their return forecasts. In the low signal-to-noise environment of a one month horizon, we find that it is preferable to rely on a theory-based approach instead of engaging...

For the purpose of stock return prediction, we propose LASSO methods augmented by further penalties related to differences in coefficient estimates at t and t+1. The economic motivation is that the coefficient for a characteristic should not change too much from t to t+1, i.e., the market's...

In this paper we introduce a new class of approaches to empirical asset pricing research, namely LASSO methods augmented by further penalties related to differences in adjacent coefficient estimates (at t and t+1) for a given characteristic. The economic motivation for this is that the...