Predictable returns and asset allocation: Should a skeptical investor time the market?

Are excess returns predictable and if so, what does this mean for investors? Previous literature has tended toward two polar viewpoints: that predictability is useful only if the statistical evidence for it is incontrovertible, or that predictability should affect portfolio choice, even if the evidence is weak according to conventional measures. This paper models an intermediate view: that both data and theory are useful for decision-making. We investigate optimal portfolio choice for an investor who is skeptical about the amount of predictability in the data. Skepticism is modeled as an informative prior over the improvement in the Sharpe ratio generated by using the predictor variable. We find that the evidence is sufficient to convince even an investor with a highly skeptical prior to vary his portfolio on the basis of the dividend-price ratio and the yield spread. The resulting weights are less volatile, and, as we show, deliver superior out-of-sample performance compared with weights implied by diffuse priors, dogmatic priors, and ordinary least squares regression.