Asymptotic Variances for Tests of Portfolio Efficiency and Factor Model Comparisons with Conditioning Information

Abstract

We provide asymptotic standard errors for tests of asset pricing models and factor model comparisons with dynamic trading using conditioning information in the form of lagged instruments. The tests are based on comparing squared Sharpe ratios or their normalized differences. We provide results for both traded and non-traded factor models, and we study the optimal choice of the zero beta rate. We evaluate the asymptotic standard errors with simulations and provide applications to asset pricing model tests and factor model comparisons. We find that the incremental performance improvement of the FF5 model over the FF3 and the FF3 over the CAPM is greater when dynamic trading is allowed, as is the effect of a momentum factor. Dynamically trading consumption and liquidity hedging portfolios contribute significantly to the performance of most of the models.