This research uses macro factors to explain four standard U.S. stock market risk premia, i.e. the market excess return (RM-RF), size (SMB), value (HML), and momentum (WML). We find in-sample predictive power of macro factors, in particular at a one-year horizon. Differentiating between bull and...

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)...