This paper examines the evidence regarding predictability in the market risk premium using artificial neural networks (ANNs), namely the Elman Network (EN) and the Higher Order Neural network (HONN), univariate ARMA and exponential smoothing techniques, such as Single Exponential Smoothing (SES)...

Using 719,830 analyst recommendations from 1994 to 2017, we construct various portfolios based on levels and changes in analyst recommendations and examine how the value of those recommendations in predicting the abnormal stock returns has changed over time. We find that the predictive value of...

The predictability of stock market is of great interest to both reseachers and investors. Despite voluminous evidence of in-sample predictability, the out-of-sample predictability of stock returns remains an ongoing debate. In this paper, motivated by both the financial theories and the well...