Out-of-sample equity premium predictability and sample split–invariant inference

Gueorgui I. Kolev and Rasa Karapandza

Journal of Banking & Finance, 2017, vol. 84, issue C, 188-201

Abstract: For a comprehensive set of 21 equity premium predictors we find extreme variation in out-of-sample predictability results depending on the choice of the sample split date. To resolve this issue we propose reporting in graphical form the out-of-sample predictability criteria for every possible sample split, and two out-of-sample tests that are invariant to the sample split choice. We provide Monte Carlo evidence that our bootstrap-based inference is valid. The in-sample, and the sample split invariant out-of-sample mean and maximum tests that we propose, are in broad agreement. Finally we demonstrate how one can construct sample split invariant out-of-sample predictability tests that simultaneously control for data mining across many variables.

Keywords: Equity premium predictability; Out-of-sample inference; Sample split choice; Bootstrap (search for similar items in EconPapers)
JEL-codes: C22 C53 G12 G14 G17 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbfina:v:84:y:2017:i:c:p:188-201

DOI: 10.1016/j.jbankfin.2016.07.017

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