LAUSR

Abstract In this paper, we propose a new approach to impose economic constraints on the time-series forecasts of stock return. It is unlikely or risky for a rational investor to rely on forecast outliers to trade stocks. Given this, our new constraint approach truncates the stock return forecasts at the extremely positive and negative values. The empirical results suggest that the new economic constraint approach generate more accurate and reliable return forecasts than the unconstrained method for both univariate regression models and multivariate models. Furthermore, our new constraint approach also outperforms two prevailing constraint approaches of Campbell and Thompson (2008) and Pettenuzzo, Timmermann, and Valkanov (2014). In addition, a mean-variance investor can realize sizeable economic gains by using our new constraint approach to allocate asset relative to using unconstrained counterpart or other popular constrained models.