Dividend Dynamics, Learning, and Expected Stock Index Returns

Ravi Jagannathan and Binying Liu

No 21557, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: We present a latent variable model of dividends that predicts, out-of-sample, 39.5% to 41.3% of the variation in annual dividend growth rates between 1975 and 2016. Further, when learning about dividend dynamics is incorporated into a long-run risks model, the model predicts, out-of-sample, 25.3% to 27.1% of the variation in annual stock index returns over the same time horizon, and learning contributes approximately half of the predictability in returns. These findings support the view that both investors' aversion to long-run risks and their learning about these risks are important in determining the stock index prices and expected returns.

JEL-codes: G10 G11 G12 (search for similar items in EconPapers)
Date: 2015-09
New Economics Papers: this item is included in nep-cfn and nep-fmk
Note: AP
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Published as RAVI JAGANNATHAN & BINYING LIU, 2019. "Dividend Dynamics, Learning, and Expected Stock Index Returns," The Journal of Finance, vol 74(1), pages 401-448.

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