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Out of sample predictability in predictive regressions with many predictor candidates

Jean-Yves Pitarakis () and Jesus Gonzalo ()

UC3M Working papers. Economics from Universidad Carlos III de Madrid. Departamento de Economía

Abstract: This paper is concerned with detecting the presence of out of sample predictability in linear predictive regressions with a potentially large set of candidate predictors. We propose a procedure based on out of sample MSE comparisons that is implementedin a pairwise manner using one predictor at a time and resulting in an aggregate test statistic that is standard normally distributed under the none hypothesis of no linear predictability. Predictors can be highly persistent, purely stationary or a combination of both. Upon rejection of the none hypothesis we subsequently introduce a predictor screening procedure designed to identify the most active predictors.

Keywords: High; Dimensional; Predictability; Predictive; Regressions; Forecasting (search for similar items in EconPapers)
JEL-codes: C12 C32 C52 C53 (search for similar items in EconPapers)
Date: 2020-12-09
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-for and nep-ore
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Persistent link: https://EconPapers.repec.org/RePEc:cte:werepe:31554

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