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- W2095701169 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." @default.
- W2095701169 created "2016-06-24" @default.
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- W2095701169 date "2008-01-01" @default.
- W2095701169 modified "2023-10-17" @default.
- W2095701169 title "Predictive Systems: Living with Imperfect Predictors" @default.
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- W2095701169 doi "https://doi.org/10.2139/ssrn.953272" @default.
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