This paper contributes to the debate on the role of oil prices in predicting stock returns. The novelty of the paper is
that it considers monthly time-series historical data that span over 150 years (1859:10–2013:12) and applies a
predictive regression model that accommodates three salient features of the data, namely, a persistent and endogenous
oil price, and model heteroscedasticity. Three key findings are unraveled: first, oil price predicts US
stock returns. Second, in-sample evidence is corroborated by out-sample evidence of predictability. Third, both
positive and negative oil price changes are important predictors of US stock returns, with negative changes relativelymore
important. Our results are robust to the use of different estimators and choice of in-sample periods.