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

Chunji Xuan and Chang-Jin Kim

Japan and the World Economy, 2020, vol. 55, issue C

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.

Keywords: Constant-gain learning; Stock return predictability; Steady-state shifts in mean; Out-of-sample forecasts (search for similar items in EconPapers)
JEL-codes: G12 G17 (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:eee:japwor:v:55:y:2020:i:c:s0922142520300281

DOI: 10.1016/j.japwor.2020.101027

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