| Popis: |
This paper examines the cross-sectional properties of stock return forecasts based on Fama-MacBeth regressions using all firms contained in the STOXX Europe 600 index during the September 1999-December 2018 period. Our estimation approach is strictly out-of-sample, mimicking an investor who exploits both historical and real-time information on multiple firm characteristics to predict returns. The models capture a substantial amount of the cross-sectional variation in true expected returns and generate predictive slopes close to one, i.e., the forecast dispersion mostly reflects cross-sectional variation in true expected returns. The predictions translate into a high value added for investors. For an active trading strategy, we find strong market outperformance net of transaction costs based on a variety of performance measures. |
