Time-Varying Factor Allocation

Abstract

In this empirical study, we provide evidence on how predictive information can be utilized to profitably allocate a cross-asset factor portfolio, covering various well-known factors over the asset classes equity, commodity, fixed income, and foreign exchange. We investigate the performance of a meaningful set of predictors, which we broadly divide into macro and market indicators. Our analysis shows that tilting a global factor portfolio according to signals derived from business cycle indicators, inflation, and short-term interest rates, among other predictors, significantly outperforms a static factor benchmark. The established results are based on practical considerations, survive conservative transaction cost assumptions, and are validated over an extensive out-of-sample period. In sum, we highlight the potential benefits of an asset-allocation framework conditioned on predictive variables, but caution to time factors on a standalone basis.