Dividend Dynamics, Learning, and Expected Stock Index Returns
NBER Working Paper No. 21557
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.
Document Object Identifier (DOI): 10.3386/w21557
Published: RAVI JAGANNATHAN & BINYING LIU, 2019. "Dividend Dynamics, Learning, and Expected Stock Index Returns," The Journal of Finance, vol 74(1), pages 401-448. citation courtesy of
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