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Stock Returns and Dividend Yields Revisited: A New Way to Look at an Old Problem

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  • Wolf, Michael

Abstract

The problem of whether stock returns can he predicted from dividend yields is discussed. I apply a new statistical method for finding reliable confidence intervals for regression parameters in the context of dependent and possibly heteroscedastic data, called subsampling. The method works under very weak conditions and avoids the pitfalls of having to choose a structural model to fit to observed data. Appropriate simulation studies suggest that it has better small-sample properties than the generalized method of moments, which is also model free and works under weak conditions. Applying the subsampling method to three datasets, I do not find convincing evidence for the predictability of stock returns.

Suggested Citation

  • Wolf, Michael, 2000. "Stock Returns and Dividend Yields Revisited: A New Way to Look at an Old Problem," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(1), pages 18-30, January.
  • Handle: RePEc:bes:jnlbes:v:18:y:2000:i:1:p:18-30
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    Cited by:

    1. Goncalves, Silvia & Kilian, Lutz, 2004. "Bootstrapping autoregressions with conditional heteroskedasticity of unknown form," Journal of Econometrics, Elsevier, vol. 123(1), pages 89-120, November.
    2. Erdenebat Bataa & Dong H. Kim & Denise R. Osborn, 2007. "Expectations Hypothesis Tests in the Presence of Model Uncertainty," Discussion Paper Series 0703, Institute of Economic Research, Korea University.
    3. David G. McMillan & Mark E. Wohar, 2010. "Stock return predictability and dividend-price ratio: a nonlinear approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 15(4), pages 351-365.
    4. McMillan, David G., 2009. "Revisiting dividend yield dynamics and returns predictability: Evidence from a time-varying ESTR model," The Quarterly Review of Economics and Finance, Elsevier, vol. 49(3), pages 870-883, August.
    5. David McMillan & Alan Speight, 2006. "Non-linear long horizon returns predictability: evidence from six south-east Asian markets," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 13(2), pages 95-111, June.
    6. Cheolbeom Park, 2006. "The Persistence and Predictive Power of the Dividend-Price Ratio," Departmental Working Papers wp0603, National University of Singapore, Department of Economics.
    7. Erdenebat Bataa & Dong H. Kim & Denise R. Osborn, 2006. "A Further Examination of the Expectations Hypothesis for the Term Structure," The School of Economics Discussion Paper Series 0611, Economics, The University of Manchester.
    8. Nikolaos Mitinanoudis & Theologos Dergiades, 2017. "Stock Prices Predictability at Long-horizons: Two Tales from the Time-Frequency Domain," Credit and Capital Markets, Credit and Capital Markets, vol. 50(1), pages 37-61.
    9. Maynard, Alex & Shimotsu, Katsumi, 2009. "Covariance-Based Orthogonality Tests For Regressors With Unknown Persistence," Econometric Theory, Cambridge University Press, vol. 25(01), pages 63-116, February.
    10. Goetzmann, William N. & Ibbotson, Roger G. & Peng, Liang, 2001. "A new historical database for the NYSE 1815 to 1925: Performance and predictability," Journal of Financial Markets, Elsevier, vol. 4(1), pages 1-32, January.
    11. Sizova, Natalia, 2014. "A frequency-domain alternative to long-horizon regressions with application to return predictability," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 261-272.
    12. Safari, Meysam & TahmooresPour, Reza, 2011. "Moderation Effect of Market Condition on the Relationship between Dividend Yield and Stock Return," MPRA Paper 28913, University Library of Munich, Germany.
    13. Charlotte S. Hansen & Bjorn E. Tuypens, 2004. "Long-Run Regressions: Theory and Application to US Asset Markets," Finance 0410018, EconWPA.
    14. David G. McMillan, 2010. "Level-shifts and non-linearity in US financial ratios: Implications for returns predictability and the present value model," Review of Accounting and Finance, Emerald Group Publishing, vol. 9(2), pages 189-207, May.
    15. Ivan Paya & David A. Peel, 2005. "A New Analysis Of The Determinants Of The Real Dollar-Sterling Exchange Rate: 1871-1994," Working Papers. Serie AD 2005-16, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    16. Deniz Baglan & Emre Yoldas, 2013. "Government debt and macroeconomic activity: a predictive analysis for advanced economies," Finance and Economics Discussion Series 2013-05, Board of Governors of the Federal Reserve System (U.S.).
    17. Lorenzo Camponovo & Olivier Scaillet & Fabio Trojani, 2018. "Predictability Hidden by Anomalous Observations," School of Economics Discussion Papers 0418, School of Economics, University of Surrey.
    18. Lorenzo Camponovo & Olivier Scaillet & Fabio Trojani, 2016. "Predictability Hidden by Anomalous Observations," Papers 1612.05072, arXiv.org.
    19. Michael Scholz & Jens Perch Nielsen & Stefan Sperlich, 2012. "Nonparametric prediction of stock returns guided by prior knowledge," Graz Economics Papers 2012-02, University of Graz, Department of Economics.
    20. Park, Cheolbeom, 2010. "When does the dividend-price ratio predict stock returns?," Journal of Empirical Finance, Elsevier, vol. 17(1), pages 81-101, January.

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