Prévoir sans persistance

Christophe Boucher () and Bertrand Maillet
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Christophe Boucher: ABN AMRO Variances et Centre d'Economie de la Sorbonne, https://centredeconomiesorbonne.cnrs.fr

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

Abstract: The forecasting literature has identified three important and broad issues: the predictive content is unstable over time, in-sample and out-of-sample discordant results and the problematic statistical inference with highly persistent predictors. In this paper, we simultaneously address these three issues, proposing to directly treat the persistence of forecasting variables before use. We thus cut-out the low frequency components and show, in simulations and on financial data, that this pre-treatment improves the predictive power of the studied economic variables

Keywords: Forecasting; persistence; filters (search for similar items in EconPapers)
JEL-codes: C14 C53 G17 (search for similar items in EconPapers)
Pages: 11 pages
Date: 2012-01
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Persistent link: https://EconPapers.repec.org/RePEc:mse:cesdoc:12001

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