Out-of-sample equity premium predictability and sample split–invariant inference
Gueorgui I. Kolev and
Journal of Banking & Finance, 2017, vol. 84, issue C, 188-201
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: G12 G14 G17 C22 C53 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:jbfina:v:84:y:2017:i:c:p:188-201
Access Statistics for this article
Journal of Banking & Finance is currently edited by Ike Mathur
More articles in Journal of Banking & Finance from Elsevier
Series data maintained by Dana Niculescu ().