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The predictability of aggregate Japanese stock returns: Implications of dividend yield

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  • Chen, Sichong

Abstract

This paper explores the implications of a dividend yield model for predicting aggregate Japanese stock returns using long time-series data from 1949 to 2009. In addition to one-period return tests, we conduct statistical tests based on dividend growth forecasts and long-horizon return forecasts implied by one-year regressions to provide significant evidence for the predictability of aggregate Japanese stock returns. Our findings therefore strengthen the international evidence for the role of dividend yield in predicting returns. However, we find that direct long-horizon regressions are not a powerful way of testing the null hypothesis of no return predictability. Moreover, we find that current cash flow is a more important driving force than future cash flow in the stock market fluctuations, although the dominant force is attributed to expected future returns.

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  • 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.
    • Handle: RePEc:eee:reveco:v:22:y:2012:i:1:p:284-304
    DOI: 10.1016/j.iref.2011.10.009
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    1. Martin Lettau & Stijn Van Nieuwerburgh, 2008. "Reconciling the Return Predictability Evidence," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1607-1652, July.
    2. Markus K. Brunnermeier & Christian Julliard, 2008. "Money Illusion and Housing Frenzies," The Review of Financial Studies, Society for Financial Studies, vol. 21(1), pages 135-180, January.
    3. 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.
    4. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
    5. Campbell, John Y, 1991. "A Variance Decomposition for Stock Returns," Economic Journal, Royal Economic Society, vol. 101(405), pages 157-179, March.
    6. Martin Lettau & Sydney C. Ludvigson, 2014. "Shocks and Crashes," NBER Macroeconomics Annual, University of Chicago Press, vol. 28(1), pages 293-354.
    7. Campbell, John Y. & Yogo, Motohiro, 2006. "Efficient tests of stock return predictability," Journal of Financial Economics, Elsevier, vol. 81(1), pages 27-60, July.
    8. John Y. Campbell, Robert J. Shiller, 1988. "The Dividend-Price Ratio and Expectations of Future Dividends and Discount Factors," The Review of Financial Studies, Society for Financial Studies, vol. 1(3), pages 195-228.
    9. Campbell, John Y & Hamao, Yasushi, 1992. "Predictable Stock Returns in the United States and Japan: A Study of Long-Term Capital Market Integration," Journal of Finance, American Finance Association, vol. 47(1), pages 43-69, March.
    10. Schrimpf, Andreas, 2010. "International stock return predictability under model uncertainty," Journal of International Money and Finance, Elsevier, vol. 29(7), pages 1256-1282, November.
    11. Bekaert, Geert & Hodrick, Robert J, 1992. "Characterizing Predictable Components in Excess Returns on Equity and Foreign Exchange Markets," Journal of Finance, American Finance Association, vol. 47(2), pages 467-509, June.
    12. Lettau, Martin & Ludvigson, Sydney C., 2005. "Expected returns and expected dividend growth," Journal of Financial Economics, Elsevier, vol. 76(3), pages 583-626, June.
    13. John H. Cochrane, 2008. "The Dog That Did Not Bark: A Defense of Return Predictability," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1533-1575, July.
    14. Fama, Eugene F. & French, Kenneth R., 1988. "Dividend yields and expected stock returns," Journal of Financial Economics, Elsevier, vol. 22(1), pages 3-25, October.
    15. John H. Cochrane, 1994. "Permanent and Transitory Components of GNP and Stock Prices," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 109(1), pages 241-265.
    16. Stambaugh, Robert F., 1999. "Predictive regressions," Journal of Financial Economics, Elsevier, vol. 54(3), pages 375-421, December.
    17. Amit Goyal & Ivo Welch, 2003. "Predicting the Equity Premium with Dividend Ratios," Management Science, INFORMS, vol. 49(5), pages 639-654, May.
    18. Hjalmarsson, Erik, 2010. "Predicting Global Stock Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(1), pages 49-80, February.
    19. Hodrick, Robert J, 1992. "Dividend Yields and Expected Stock Returns: Alternative Procedures for Inference and Measurement," The Review of Financial Studies, Society for Financial Studies, vol. 5(3), pages 357-386.
    20. Goetzmann, William Nelson & Jorion, Philippe, 1993. "Testing the Predictive Power of Dividend Yields," Journal of Finance, American Finance Association, vol. 48(2), pages 663-679, June.
    21. Jacob Boudoukh & Roni Michaely & Matthew Richardson & Michael R. Roberts, 2007. "On the Importance of Measuring Payout Yield: Implications for Empirical Asset Pricing," Journal of Finance, American Finance Association, vol. 62(2), pages 877-915, April.
    22. Jacob Boudoukh & Matthew Richardson & Robert F. Whitelaw, 2008. "The Myth of Long-Horizon Predictability," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1577-1605, July.
    23. 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.
    24. Campbell, John Y & Ammer, John, 1993. "What Moves the Stock and Bond Markets? A Variance Decomposition for Long-Term Asset Returns," Journal of Finance, American Finance Association, vol. 48(1), pages 3-37, March.
    25. Chen, Carl R. & Lung, Peter P. & Wang, F. Albert, 2009. "Stock Market Mispricing: Money Illusion or Resale Option?," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 44(5), pages 1125-1147, October.
    26. Chen, Long, 2009. "On the reversal of return and dividend growth predictability: A tale of two periods," Journal of Financial Economics, Elsevier, vol. 92(1), pages 128-151, April.
    27. John H. Cochrane, 2011. "Presidential Address: Discount Rates," Journal of Finance, American Finance Association, vol. 66(4), pages 1047-1108, August.
    28. JULES H. Van BINSBERGEN & RALPH S. J. KOIJEN, 2010. "Predictive Regressions: A Present‐Value Approach," Journal of Finance, American Finance Association, vol. 65(4), pages 1439-1471, August.
    29. Nelson, Charles R & Kim, Myung J, 1993. "Predictable Stock Returns: The Role of Small Sample Bias," Journal of Finance, American Finance Association, vol. 48(2), pages 641-661, June.
    30. Cochrane, John H, 1992. "Explaining the Variance of Price-Dividend Ratios," The Review of Financial Studies, Society for Financial Studies, vol. 5(2), pages 243-280.
    31. repec:bla:jfinan:v:53:y:1998:i:3:p:879-904 is not listed on IDEAS
    32. John H. Cochrane, 2011. "Discount Rates," NBER Working Papers 16972, National Bureau of Economic Research, Inc.
    33. Deaves, Richard & Miu, Peter & Barry White, C., 2008. "Canadian stock market multiples and their predictive content," International Review of Economics & Finance, Elsevier, vol. 17(3), pages 457-466.
    34. Haw, In-Mu & Ho, Simon S.M. & Hu, Bingbing & Zhang, Xu, 2011. "The contribution of stock repurchases to the value of the firm and cash holdings around the world," Journal of Corporate Finance, Elsevier, vol. 17(1), pages 152-166, February.
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    2. Laih, Yih-Wenn & Lai, Hung-Neng & Li, Chun-An, 2015. "Analyst valuation and corporate value discovery," International Review of Economics & Finance, Elsevier, vol. 35(C), pages 235-248.
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    More about this item

    Keywords

    Stock return predictability; Dividend yield; Japanese stock market; Dividend growth forecasts; Long-horizon return forecasts;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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