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Growth Expectations, Dividend Yields, and Future Stock Returns

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  • Zhi Da
  • Ravi Jagannathan
  • Jianfeng Shen

Abstract

According to the dynamic version of the Gordon growth model, the long-run expected return on stocks, stock yield, is the sum of the dividend yield on stocks plus some weighted average of expected future growth rates in dividends. We construct a measure of stock yield based on sell-side analysts' near-term earnings forecasts that predicts US stock index returns well, with an out-of-sample R-squared that is consistently above 2% at monthly frequency over our sample period. Stock yield also predicts future stock index returns in the US and other G7 countries and returns of US stock portfolios formed by sorting stocks based on firm characteristics, at various horizons. The findings are consistent with a single dominant factor driving expected returns on stocks over different holding periods. That single factor extracted from the cross section of stock yields using the Kelly and Pruitt (2013) partial regressions method predicts stock index returns better. The performance of the Binsbergen and Koijen (2010) latent factor model for forecasting stock returns improves significantly when stock yield is included as an imperfect observation of expected return on stocks. Consistent with folk wisdom, stock returns are more predictable coming out of a recession. Our measure performs as well in predicting stock returns as the implied cost of capital, another common stock yield measure that uses additional information.

Suggested Citation

  • Zhi Da & Ravi Jagannathan & Jianfeng Shen, 2014. "Growth Expectations, Dividend Yields, and Future Stock Returns," NBER Working Papers 20651, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:20651
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    Cited by:

    1. Ravi Jagannathan & Binying Liu, 2019. "Dividend Dynamics, Learning, and Expected Stock Index Returns," Journal of Finance, American Finance Association, vol. 74(1), pages 401-448, February.
    2. Gebka, Bartosz & Wohar, Mark E., 2019. "Stock return distribution and predictability: Evidence from over a century of daily data on the DJIA index," International Review of Economics & Finance, Elsevier, vol. 60(C), pages 1-25.
    3. Cao, Charles & Simin, Timothy & Xiao, Han, 2020. "Predicting the equity premium with the implied volatility spread," Journal of Financial Markets, Elsevier, vol. 51(C).
    4. Cao, Charles & Simin, Timothy & Xiao, Han, 2019. "Predicting the equity premium with the implied volatility spread," MPRA Paper 103651, University Library of Munich, Germany.

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    More about this item

    JEL classification:

    • G0 - Financial Economics - - General
    • G1 - Financial Economics - - General Financial Markets
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • 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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