LAUSR

Abstract In this paper, we offer an alternative approach to test the predictive power of commodity prices in stock returns of G7 countries. The new approach accounts for asymmetry, conditional heteroscedasticity, endogeneity, persistence, and structural breaks that may bias the forecast outcomes. Three striking findings are highlighted from the various analyses. First, commodity prices are good predictors of stock returns both for in-sample and out-of-sample forecasts. Second, the proposed commodity-based model for stock returns outperforms both the time series models as well as historical average models that ignore same. Third, these conclusions are robust to different components of commodity prices, multiple data samples and alternative forecast horizons.