We develop a framework for estimating expected returns---a predictive system---that allows predictors to be imperfectly correlated with the conditional expected return. When predictors are imperfect, the estimated expected return depends on past returns in a manner that hinges on the correlation between unexpected returns and innovations in expected returns. We find empirically that prior beliefs about this correlation, which is most likely negative, substantially affect estimates of expected returns as well as various inferences about predictability, including assessments of a predictor's usefulness. Compared to standard predictive regressions, predictive systems deliver different and more precise estimates of expected returns.
Published: Lubos Pástor & Robert F. Stambaugh, 2009.
"Predictive Systems: Living with Imperfect Predictors,"
Journal of Finance,
American Finance Association, vol. 64(4), pages 1583-1628, 08.
This paper is a revision of the earlier NBER working paper w12814,
Predictive Systems: Living with Imperfect Predictors, Lubos Pastor, Robert F. Stambaugh
This paper is available as PDF (774 K) or via email.
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