Using data on 65,000 stocks from 23 countries, the authors re-evaluate the performance of the Fama-French (2015) factors in global markets. The results provide convincing evidence that the value, profitability, and investment factors are far less reliable than commonly thought. Their performance...

This paper provides global evidence supporting the hypothesis that expected return models are enhanced by the inclusion of variables that describe the evolution of book-to-market—changes in book value, changes in price, and net share issues. This conclusion is supported using data representing...

We examine return predictability with machine learning in 46 international stock markets. We calculate 148 stock characteristics and use them to feed a repertoire of different models. The algorithms extract predictability mainly from simple, yet popular, factor types—such as momentum,...

Investors often focus their attention on recent information only, underestimating the rele-vance of information from the distant past. In consequence, the ordering of historical re-turns robustly predicts future stock performance in the cross-section. Using data from 49 countries, we...