Time-Varying Factor Allocation
Stefan Vincenz and Tom Oskar Karl Zeissler (Vienna U. of Economics and Business)
September 15, 2021
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.
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