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
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: C53 C52 C32 C12 (search for similar items in EconPapers)
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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