This paper develops a Monte-Carlo backtesting procedure for risk premia strategies and employs it to study Time-Series Momentum (TSM). Relying on time-series models, empirical residual distributions and copulas we overcome two key drawbacks of conventional backtesting procedures. We create...

We propose a new asset-pricing framework in which all securities' signals are used to predict each individual return. While the literature focuses on each security's own- signal predictability, assuming an equal strength across securities, our framework is flexible and includes...

We build an equilibrium model to explain why stock return predictability concentrates in bad times. The key feature is that investors use different forecasting models, and hence assess uncertainty differently. As economic conditions deteriorate, uncertainty rises and investors' opinions...

We develop a finite-sample procedure to test for mean-variance efficiency and spanning without imposing any parametric assumptions on the distribution of model disturbances. In so doing, we provide an exact distribution-free method to test uniform linear restrictions in multivariate linear...

Cross-sectional asset pricing tests with GMM can generate spuriouslyhigh explanatory power for factor models when the moment conditions are specifiedsuch that they allow the estimated factor means to substantially deviate from theobserved sample averages. In fact, by shifting the weights on the...

In the three-factor model of Fama and French (1993), portfolio returns are explained by the factors Small Minus Big (SMB and High Minus Low (HML) which capture returns related to firm capitalization (size) and the book-to-market ratio (B/M). In the standard approach of the model, both the test...