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Revisiting dividend yield dynamics and returns predictability: Evidence from a time-varying ESTR model

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  • McMillan, David G.

Abstract

Since the bubble of the late 1990s the dividend yield appears non-stationary indicating the breakdown of the equilibrium relationship between prices and dividends. Two lines of research have developed in order to explain this apparent breakdown. First, that the dividend yield is better characterised as a non-linear process and second, that it is subject to mean level shifts. This paper jointly models both of these characteristics by allowing non-linear reversion to a changing mean level. Results support stationarity of this model for eight international dividend yield series. This model is than applied to the forecast of monthly stock returns. Evidence supports our time-varying non-linear model over linear alternatives, particularly so on the basis of an out-of-sample R-squared measure and a trading rule exercise. More detailed examination of the trading rule measure suggests that investors could obtain positive returns, as the model forecasts do not imply excessive trading such that costs would not outweigh returns. Finally, the superior performance of the non-linear model largely arises from its ability to forecast negative returns, whereas linear models are unable to do.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:quaeco:v:49:y:2009:i:3:p:870-883
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    Cited by:

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    2. Daniel Mantilla-García & Vijay Vaidyanathan, 2017. "Predicting stock returns in the presence of uncertain structural changes and sample noise," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 31(3), pages 357-391, August.
    3. Adelina Gschwandtner & Michael Hauser, 2016. "Profit persistence and stock returns," Applied Economics, Taylor & Francis Journals, vol. 48(37), pages 3538-3549, August.
    4. Xie, Zixiong & Chen, Shyh-Wei & Wu, An-Chi, 2019. "Asymmetric adjustment, non-linearity and housing price bubbles: New international evidence," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    5. Chen, Shyh-Wei & Xie, Zixiong, 2017. "Asymmetric adjustment and smooth breaks in dividend yields: Evidence from international stock markets," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 339-354.
    6. Ruey-Shii Chen & Tai-Wei Zhang, 2018. "Dividend cuts and predictability," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 42(2), pages 249-267, April.
    7. Vicente Esteve & Manuel Navarro-Ibáñez & María A. Prats, 2013. "The present value model of U.S. stock prices revisited: long-run evidence with structural breaks, 1871-2010," Working Papers 1305, Department of Applied Economics II, Universidad de Valencia.
    8. McMillan, David G., 2019. "Stock return predictability: Using the cyclical component of the price ratio," Research in International Business and Finance, Elsevier, vol. 48(C), pages 228-242.
    9. Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.

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