The "Out-of-Sample" Performance of Long-Run Risk Models

This article studies the ability of long-run risk models, following Bansal and Yaron (2004) and others, to explain out-of-sample asset returns associated with the equity premium puzzle, size and book-to-market effects, momentum, reversals, and bond returns of different maturity and credit ratings. We examine stationary and cointegrated versions of the models using annual data for 1931–2006. We find that the models perform comparably overall to the simple CAPM. A cointegrated version of the model outperforms a stationary version. The long-run risk models perform relatively well on the momentum effect, and earnings momentum in particular. For some of the excess returns the long-run risk models deliver smaller average pricing errors than the CAPM, but they often have larger error variances, and the mean squared prediction errors are broadly similar.