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Tug-of-War: Time-Varying Predictability of Stock Returns and Dividend Growth

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  • Xiaoneng Zhu

Abstract

We propose a regime-switching present-value model with latent variables to jointly investigate the predictability of stock returns and dividend growth. We find that both return predictability and dividend growth predictability are time-varying. Interestingly, the predictability of stock returns and dividend growth is a tug-of-war contest: when dividend growth is highly predictable in the high-volatility regime, stock returns are largely unpredictable; in contrast, when dividend growth is less predictable in the low-volatility regime, stock returns are significantly predictable. We also investigate macroeconomic determinants of regime switches and find that two regimes are intimately related to macroeconomic risk and economic activity.

Suggested Citation

  • Xiaoneng Zhu, 2015. "Tug-of-War: Time-Varying Predictability of Stock Returns and Dividend Growth," Review of Finance, European Finance Association, vol. 19(6), pages 2317-2358.
  • Handle: RePEc:oup:revfin:v:19:y:2015:i:6:p:2317-2358.
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    References listed on IDEAS

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    1. Bakshi, Gurdip & Chen, Zhiwu, 2005. "Stock valuation in dynamic economies," Journal of Financial Markets, Elsevier, vol. 8(2), pages 111-151, May.
    2. Goetzmann, William N & Jorion, Philippe, 1995. "A Longer Look at Dividend Yields," The Journal of Business, University of Chicago Press, vol. 68(4), pages 483-508, October.
    3. Leitch, Gordon & Tanner, J Ernest, 1991. "Economic Forecast Evaluation: Profits versus the Conventional Error Measures," American Economic Review, American Economic Association, vol. 81(3), pages 580-590, June.
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    Cited by:

    1. Kim, Jan R. & Chung, Keunsuk, 2020. "Regime switching in the present value models: A backward-solving method," Finance Research Letters, Elsevier, vol. 32(C).
    2. Zhu, Xiaoneng & Rahman, Shahidur, 2015. "A regime-switching Nelson–Siegel term structure model of the macroeconomy," Journal of Macroeconomics, Elsevier, vol. 44(C), pages 1-17.
    3. Lawrenz, Jochen & Zorn, Josef, 2018. "Decomposing the predictive power of local and global financial valuation ratios," The Quarterly Review of Economics and Finance, Elsevier, vol. 70(C), pages 137-149.
    4. He, Zhongzhi (Lawrence) & Zhu, Jie & Zhu, Xiaoneng, 2015. "Dynamic factors and asset pricing: International and further U.S. evidence," Pacific-Basin Finance Journal, Elsevier, vol. 32(C), pages 21-39.
    5. Lof, Matthijs & Nyberg, Henri, 2024. "Discount rates and cash flows: A local projection approach," Journal of Banking & Finance, Elsevier, vol. 162(C).
    6. Cenesizoglu, Tolga, 2022. "Return decomposition over the business cycle," Journal of Banking & Finance, Elsevier, vol. 143(C).
    7. Chen, Junping & Xiong, Xiong & Zhu, Jie & Zhu, Xiaoneng, 2017. "Asset prices and economic fluctuations: The implications of stochastic volatility," Economic Modelling, Elsevier, vol. 64(C), pages 128-140.
    8. Hammami, Yacine & Zhu, Jie, 2020. "Understanding time-varying short-horizon predictability✰," Finance Research Letters, Elsevier, vol. 32(C).
    9. Guillaume Coqueret & Romain Deguest, 2024. "Unexpected opportunities in misspecified predictive regressions," Post-Print hal-04595355, HAL.

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