Measuring the Predictable Variation in Stock and Bond Returns

Abstract

Recent studies show that when a regression model is used to forecast stock and bond returns, the sample R 2 increases dramatically with the length of the return horizon. These studies argue, therefore, that long-horizon returns are highly predictable. This article presents evidence that suggests otherwise. Long-horizon regressions can easily yield large values of the sample R 2 , even if the populations R 2 is smaller or zero. Moreover, long-horizon regressions with a small or zero population R 2 can produce t-ratios that might be interpreted as evidence of strong predictability. In general, the analysis provides little support for the view that long-horizon returns are highly predictable.