Earnings Estimates, Predictor Specification, and Measurement Error
Posted: 31 Mar 2017
Date Written: March 25, 1997
Abstract
Increased use of expectational data for modeling stock returns places a spotlight on the specification of predictor variables. Choices between alternative specifications of a given predictor such as E/P or earnings trend, for example, can have wide-ranging effects on portfolio selection and quantitative modeling. Investigation here indicates that the importance of predictor specification may vary depending upon the predictor and the investment strategy, and that the relationship between predictors and returns may vary across types of stocks.
Keywords: earnings estimates, predictor variables, return modeling, return predictors, earnings predictors, predictor specification, earnings forecasts, expectational data, measurement error, distributed effects, missing data, imputation
JEL Classification: G14
Suggested Citation: Suggested Citation