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...

We investigate the stock return predictability for the aggregate Central and Eastern European (CEE) markets from 1998 through the mid-2017. Using the firm-level data we construct country portfolios and sets of component portfolios: 10 industry portfolios, 10 size portfolios, 10 market-to-book...

We operationalize the definition of systemic risk provided by the IMF, BIS, and FSB and derive testable hypotheses to identify indicators of systemic risk. We map these hypotheses into a two-stage hierarchical testing framework, combining insights from the early-warning literature on financial...

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...