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

Abstract

This paper studies the ability of stationary and cointegrated versions of long-run risk models to explain out-of-sample asset returns during 1931-2009. The models perform similarly overall to the classical Capital Asset Pricing Model in a mean squared error sense, but have smaller average pricing errors. The long-run risk models perform relatively well on the momentum effect. A cointegrated version of the model outperforms a stationary version. A cointegrated model restricting the risk premiums to identify structural parameters has larger average pricing errors and smaller error variances than a reduced-form version of the model.