International stock return predictability under model uncertainty
Andreas Schrimpf
Journal of International Money and Finance, 2010, vol. 29, issue 7, 1256-1282
Abstract:
This paper examines return predictability when the investor is uncertain about the right state variables. A novel feature of the model averaging approach used in this paper is to account for finite-sample bias of the coefficients in the predictive regressions. Drawing on an extensive international dataset, we find that interest-rate related variables are usually among the most prominent predictive variables, whereas valuation ratios perform rather poorly. Yet, predictability of market excess returns weakens substantially, once model uncertainty is accounted for. We document notable differences in the degree of in-sample and out-of-sample predictability across different stock markets. Overall, these findings suggest that return predictability is neither a uniform, nor a universal feature across international capital markets.
Keywords: Stock; return; predictability; Bayesian; model; averaging; Model; uncertainty; International; stock; markets (search for similar items in EconPapers)
Date: 2010
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (21)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0261-5606(10)00039-2
Full text for ScienceDirect subscribers only
Related works:
Working Paper: International Stock Return Predictability Under Model Uncertainty (2008) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:jimfin:v:29:y:2010:i:7:p:1256-1282
Access Statistics for this article
Journal of International Money and Finance is currently edited by J. R. Lothian
More articles in Journal of International Money and Finance from Elsevier
Bibliographic data for series maintained by Catherine Liu ().