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International Stock Return Predictability: On the Role of the United States in Bad and Good Times

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Abstract

In this paper we document the asymmetric role that the U.S. stock market plays in the international predictability of excess stock returns during recession and expansion periods. Most of the positive evidence accrues during the periods of recessions in the United States. During the expansions there is only a limited evidence supporting the importance of lagged U.S. returns in predictability of stock returns in 10 industrialised countries.

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  • Boriss Siliverstovs, 2016. "International Stock Return Predictability: On the Role of the United States in Bad and Good Times," KOF Working papers 16-408, KOF Swiss Economic Institute, ETH Zurich.
    • Handle: RePEc:kof:wpskof:16-408
    DOI: 10.3929/ethz-a-010689622
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    1. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    2. Andrew Ang & Geert Bekaert, 2007. "Stock Return Predictability: Is it There?," The Review of Financial Studies, Society for Financial Studies, vol. 20(3), pages 651-707.
    3. Zhu, Xiaoneng, 2013. "Perpetual learning and stock return predictability," Economics Letters, Elsevier, vol. 121(1), pages 19-22.
    4. Fama, Eugene F. & Schwert, G. William, 1977. "Asset returns and inflation," Journal of Financial Economics, Elsevier, vol. 5(2), pages 115-146, November.
    5. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    6. John Y. Campbell & Samuel B. Thompson, 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1509-1531, July.
    7. David E. Rapach & Jack K. Strauss & Guofu Zhou, 2013. "International Stock Return Predictability: What Is the Role of the United States?," Journal of Finance, American Finance Association, vol. 68(4), pages 1633-1662, August.
    8. David E. Rapach & Jack K. Strauss & Guofu Zhou, 2010. "Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy," The Review of Financial Studies, Society for Financial Studies, vol. 23(2), pages 821-862, February.
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    1. Takuro Hidaka & Yuta Saito & Jun Sakamoto, 2021. "Historical Relationships and International Market Return Predictability: The Role of the UK in the Former British Colonies, Protectorates and Mandates," Discussion Papers in Economics and Business 21-08-Rev., Osaka University, Graduate School of Economics, revised Oct 2023.
    2. Labidi, Chiaz & Rahman, Md Lutfur & Hedström, Axel & Uddin, Gazi Salah & Bekiros, Stelios, 2018. "Quantile dependence between developed and emerging stock markets aftermath of the global financial crisis," International Review of Financial Analysis, Elsevier, vol. 59(C), pages 179-211.
    3. Xiaozhen Jing & Dezhong Xu & Bin Li & Tarlok Singh, 2024. "Does the U.S. extreme indicator matter in stock markets? International evidence," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-27, December.
    4. Georges Prat & David Le Bris, 2019. "Equity Risk Premium and Time Horizon: what do the French secular data say ?," Working Papers hal-04141877, HAL.
    5. Georges Prat & David Le Bris, 2019. "Equity Risk Premium and Time Horizon: what do the French secular data say ?," EconomiX Working Papers 2019-8, University of Paris Nanterre, EconomiX.
    6. Boriss Siliverstovs & Daniel S. Wochner, 2021. "State‐dependent evaluation of predictive ability," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 547-574, April.
    7. Yi-Chieh Wen & Bin Li, 2020. "Lagged country returns and international stock return predictability during business cycle recession periods," Applied Economics, Taylor & Francis Journals, vol. 52(46), pages 5005-5019, October.
    8. Jonathan Iworiso & Spyridon Vrontos, 2020. "On the directional predictability of equity premium using machine learning techniques," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 449-469, April.

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