Predictive Systems: Living with Imperfect Predictors

59 Pages Posted: 12 Jan 2007 Last revised: 21 Sep 2010

See all articles by Lubos Pastor

Lubos Pastor

University of Chicago - Booth School of Business; Centre for Economic Policy Research (CEPR); National Bureau of Economic Research (NBER)

Robert F. Stambaugh

University of Pennsylvania - The Wharton School; National Bureau of Economic Research (NBER)

Multiple version iconThere are 4 versions of this paper

Date Written: February 2008

Abstract

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.

Suggested Citation

Pastor, Lubos and Stambaugh, Robert F., Predictive Systems: Living with Imperfect Predictors (February 2008). NBER Working Paper No. w13804. Available at SSRN: https://ssrn.com/abstract=956853

Lubos Pastor (Contact Author)

University of Chicago - Booth School of Business ( email )

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Centre for Economic Policy Research (CEPR)

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National Bureau of Economic Research (NBER)

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Robert F. Stambaugh

University of Pennsylvania - The Wharton School ( email )

The Wharton School, Finance Department
University of Pennsylvania
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United States
215-898-5734 (Phone)
215-898-6200 (Fax)

National Bureau of Economic Research (NBER)

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