Forecasting Corporate Bond Returns: A Regressed Combination Approach

Using a comprehensive data set, we find that corporate bond returns not only remain predictable by traditional predictors (dividend yields, default, term spreads and issuer quality), but highly predictable by a new regressed combination approach that combines information from an array of 27 macroeconomic, stock and bond predictors. Results strongly suggest that stock and macroeconomic variables contain important information for future bond returns. Our model delivers significant out-of-sample gains over other predictive models and generates forecasts that are closely linked to the real economy. These advantages reflect the model's ability to reduce forecast bias and volatility while incorporating more information.