Dividend Dynamics, Learning, and Expected Stock Index Returns

Ravi Jagannathan, Binying Liu

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


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, with learning contributing approximately half of the predictability in returns. These findings support the view that investors' aversion to long-run risks and their learning about these risks are important in determining stock index prices and expected returns.

Original languageEnglish (US)
Pages (from-to)401-448
Number of pages48
JournalJournal of Finance
Issue number1
StatePublished - Feb 1 2019

ASJC Scopus subject areas

  • Accounting
  • Finance
  • Economics and Econometrics


Dive into the research topics of 'Dividend Dynamics, Learning, and Expected Stock Index Returns'. Together they form a unique fingerprint.

Cite this