Does the choice of estimator matter when forecasting returns?

Joakim Westerlund and Paresh Narayan ()

Journal of Banking & Finance, 2012, vol. 36, issue 9, 2632-2640

Abstract: While the literature concerned with the predictability of stock returns is huge, surprisingly little is known when it comes to role of the choice of estimator of the predictive regression. Ideally, the choice of estimator should be rooted in the salient features of the data. In case of predictive regressions of returns there are at least three such features; (i) returns are heteroskedastic, (ii) predictors are persistent, and (iii) regression errors are correlated with predictor innovations. In this paper we examine if the accounting of these features in the estimation process has any bearing on our ability to forecast future returns. The results suggest that it does.

Keywords: Predictive regression; Stock return predictability; Heteroskedasticity; Predictor endogeneity (search for similar items in EconPapers)
JEL-codes: C22 C23 G1 G12 (search for similar items in EconPapers)
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (185)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbfina:v:36:y:2012:i:9:p:2632-2640

DOI: 10.1016/j.jbankfin.2012.06.005

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