The prevailing view in finance is that the evidence for long-horizon stock return predictability is significantly stronger than that for short horizons. We show that for persistent regressors, a characteristic of most of the predictive variables used in the literature, the estimators are almost perfectly correlated across horizons under the null hypothesis of no predictability. For example, for the persistence levels of dividend yields, the analytical correlation is 99% between the 1-and 2-year horizon estimators and 94% between the 1-and 5-year horizons, due to the combined effects of overlapping returns and the persistence of the predictive variable. Common sampling error across equations leads to ordinary least squares coefficient estimates and R2s that are roughly proportional to the horizon under the null hypothesis. This is the precise pattern found in the data. The asymptotic theory is corroborated, and the analysis extended by extensive simulation evidence. We perform joint tests across horizons for a variety of explanatory variables, and provide an alternative view of the existing evidence.

Multivariate density estimation (MDE) suggests that mortgage-backed security (MBS) prices can be well described as a function of the level and slope of the term structure. We analyze how this function varies across MBSs with different coupons. An important finding is that the interest rate level proxies for the moneyness of the option, the expected level of prepayments, and the average life of the cash flows, while the term structure slope controls for the average rate at which these cash flows should be discounted. Though the origination and prepayment behavior of mortgages differ substantially across coupons, there remains an unexplained common factor in MBS prices. This factor does not seem to be related to the usual suspects and therefore presents a puzzle to financial economists.