Do Cross-Sectional Predictors Contain Systematic Information?
American Finance Association Annual Meeting Paper, 2019
50 Pages Posted: 5 Oct 2019 Last revised: 27 Oct 2020
Date Written: October 26, 2020
Firm-level variables that predict cross-sectional stock returns, such as price-to-earnings and short interest, are often averaged and used to predict the time series of market returns. We extend this literature and limit the data-snooping bias by using a large population of the literature’s cross-sectional return predictors. We find the literature has ignored several cross-sectional variables–such as asset turnover and Z-score–that contain strong in-sample predictability when examined in isolation. However, after accounting for the number of predictors and their interdependence, we find only weak evidence that cross-sectional predictors make good time-series predictors, especially out-of-sample.
Keywords: Return predictability, data snooping, statistical bias, market risk premium.
JEL Classification: G00, G14, L3, C1
Suggested Citation: Suggested Citation