Predictive Systems: Living with Imperfect Predictors

Lubos Pastor and Robert Stambaugh

No 12814, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: The standard regression approach to modeling return predictability seems too restrictive in one way but too lax in another. A predictive regression models expected returns as an exact linear function of a given set of predictors but does not exploit the likely economic property that innovations in expected returns are negatively correlated with unexpected returns. We develop an alternative framework - a predictive system - that accommodates imperfect predictors and beliefs about that negative correlation. In this framework, the predictive ability of imperfect predictors is supplemented by information in lagged returns as well as lags of the predictors. Compared to predictive regressions, predictive systems deliver different and substantially more precise estimates of expected returns as well as different assessments of a given predictor's usefulness.

JEL-codes: G1 (search for similar items in EconPapers)
Date: 2007-01
New Economics Papers: this item is included in nep-ecm
Note: AP
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Citations: View citations in EconPapers (3)

Published as 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.

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Related works:
Journal Article: Predictive Systems: Living with Imperfect Predictors (2009)
Working Paper: Predictive Systems: Living with Imperfect Predictors (2008)
Working Paper: Predictive Systems: Living with Imperfect Predictors (2007)
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