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International stock return predictability under model uncertainty

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  • Schrimpf, Andreas

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.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of International Money and Finance.

Volume (Year): 29 (2010)
Issue (Month): 7 (November)
Pages: 1256-1282

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Handle: RePEc:eee:jimfin:v:29:y:2010:i:7:p:1256-1282

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Web page: http://www.elsevier.com/locate/inca/30443

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Keywords: Stock return predictability Bayesian model averaging Model uncertainty International stock markets;

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Cited by:
  1. Charlotte Christiansen & Maik Schmeling & Andreas Schrimpf, 2010. "A Comprehensive Look at Financial Volatility Prediction by Economic Variables," CREATES Research Papers 2010-58, School of Economics and Management, University of Aarhus.
  2. Andreas Sachs, 2012. "What really drives unemployment? A bayesian approach to determine the impact of institutions on the unemployment rate," Economics Bulletin, AccessEcon, vol. 32(1), pages 1008-1019.
  3. Chen, Sichong, 2012. "The predictability of aggregate Japanese stock returns: Implications of dividend yield," International Review of Economics & Finance, Elsevier, vol. 22(1), pages 284-304.

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