Conditional Dynamics and the Multi-Horizon Risk-Return Trade-Off

We propose testing asset-pricing models using multi-horizon returns (MHR). MHR serve as powerful source of conditional information that is economically important and not data-mined. We apply MHR-based testing to linear factor models. These models seek to construct the unconditionally mean-variance efficient portfolio. We reject all state-of-the-art models that imply high maximum Sharpe ratios in a single-horizon setting. Thus, the models do a poor job in accounting for the risk-return trade-off at longer horizons. Across the different models, the mean absolute pricing errors associated with MHR are positively related to the magnitude of maximal Sharpe ratio in the single-horizon setting. Model misspecification manifests itself in strong intertemporal dynamics of the factor loadings in the SDF representation. We suggest that misspecification of the dynamics of loadings arises from the common approach towards factor construction via portfolio sorts.