The equity risk premium and the low frequency of the term spread

Abstract

We extract cycles in the term spread (TMS) and study their role for predicting the equity risk premium (ERP) using linear models. The low frequency component of the TMS is a strong and robust out-of-sample ERP predictor. It obtains out-of-sample R-squares (versus the historical mean benchmark) of 1.98% and 22.1% for monthly and annual data, respectively. It forecasts well also during expansions and outperforms several variables that have been proposed as good ERP predictors. Its predictability power comes exclusively from the discount rate channel. Contrarily, the high and business-cycle frequency components of the TMS are poor out-of-sample ERP predictors.