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Structural breaks in the mean of dividend-price ratios: Implications of learning on stock return predictability

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  • Xuan, Chunji
  • Kim, Chang-Jin

Abstract

In their out-of-sample predictions of stock returns in the presence of structural breaks, Lettau and Van Nieuwerburgh (2008) implicitly assume that economic agents’ perception of the regime-specific mean for the dividend-price ratio is time-invariant within a regime. In this paper, we challenge this assumption and employ least squares learning with constant gain (or constant-gain learning) in estimating economic agents’ time-varying perception for the mean of dividend-price ratio. We obtain better out-of-sample predictions of stock returns than in Lettau and Van Nieuwerburgh (2008) for both the U.S. and Japanese stock markets. Our empirical results suggest that economic agents’ learning plays an important role in the dynamics of stock returns.

Suggested Citation

  • Xuan, Chunji & Kim, Chang-Jin, 2020. "Structural breaks in the mean of dividend-price ratios: Implications of learning on stock return predictability," Japan and the World Economy, Elsevier, vol. 55(C).
    • Handle: RePEc:eee:japwor:v:55:y:2020:i:c:s0922142520300281
    DOI: 10.1016/j.japwor.2020.101027
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    References listed on IDEAS

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    More about this item

    Keywords

    Constant-gain learning; Stock return predictability; Steady-state shifts in mean; Out-of-sample forecasts;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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