In-sample tests of predictability are superior to pseudo-out-of-sample tests, even when data mining

Ian Hunt

International Journal of Forecasting, 2022, vol. 38, issue 3, 872-877

Abstract: This paper analyses straightforward Bonferroni adjustments to critical values of in-sample tests of predictability, when data mining is used to search across models. Unlike conventional pseudo-out-of-sample tests, these in-sample tests have stable family-wise error rates (FWERs) when searching for models that predict well. Furthermore, when data mining, these in-sample tests have more power than pseudo-out-of-sample tests for identifying true predictability.

Keywords: Pseudo-out-of-sample tests; Over-fitting; Data mining; FWER; False discovery rate (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:38:y:2022:i:3:p:872-877

DOI: 10.1016/j.ijforecast.2021.05.006

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