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International stock return predictability |
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| Affiliation: | 1. King''s Business School, King''s College London, Level 1, Bush House, 30 Aldwych, London WC2B 4BG, United Kingdom;2. Department of Finance, CUHK Business School, The Chinese University of Hong Kong, Shatin, NT, Hong Kong, China;1. School of Accounting, Information Systems & Supply Chain, RMIT University, 445 Swanston, Melbourne, VIC 3000, Australia;2. School of Accounting, Information Systems & Supply Chain, RMIT University, 445 Swanston Street, Melbourne, VIC 3000, Australia |
| Abstract: | We propose a new methodology for predicting international stock returns. Our Bayesian framework performs probabilistic selection of predictors that can shift at multiple unknown structural break dates. The approach generates significantly more accurate forecasts of international stock returns than a range of popular models that are economically meaningful for a risk-averse mean–variance investor. Allowing for regime-specific variable selection reduces considerably the international diversification of an unhedged U.S. investor’s portfolio. |
| Keywords: | International stock return predictability Predictor selection Structural breaks Bayesian analysis |
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