Detrending Persistent Predictors

Christophe Boucher () and Bertrand Maillet
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Bertrand Maillet: A.A.Advisors-QCG (ABN AMRO), Variances et Centre d'Economie de la Sorbonne et EIF

Documents de travail du Centre d'Economie de la Sorbonne from Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne

Abstract: Researchers in finance very often rely on highly persistent nearly integrated explanatory variables to predict returns. This paper proposes to stand up to the usual problem of persistent regressor bias, by detrending the highly auto-correlated predictors. We find that the statistical evidence of out-of-sample predictability of stock returns is stronger, once predictors are adjusted for high persistence

Keywords: Forecasting; persistence; detrending; expected returns (search for similar items in EconPapers)
JEL-codes: C1 C14 G1 (search for similar items in EconPapers)
Pages: 10 pages
Date: 2011-03
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https://shs.hal.science/halshs-00587775 (application/pdf)

Related works:
Working Paper: Detrending Persistent Predictors (2011)
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Persistent link: https://EconPapers.repec.org/RePEc:mse:cesdoc:11019

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