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Stock Return and Cash Flow Predictability: The Role of Volatility Risk

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  • Tim Bollerslev

    (Duke University, NBER and CREATES)

  • Lai Xu

    (Duke University)

  • Hao Zhou

    (Federal Reserve Board)

Abstract

We examine the joint predictability of return and cash flow within a present value framework, by imposing the implications from a long-run risk model that allow for both time-varying volatility and volatility uncertainty. We provide new evidence that the expected return variation and the variance risk premium positively forecast both short-horizon returns and dividend growth rates. We also confirm that dividend yield positively forecasts long-horizon returns, but that it cannot forecast dividend growth rates. Our equilibrium-based “structural” factor GARCH model permits much more accurate inference than the reduced form VAR and univariate regression procedures traditionally employed in the literature. The model also allows for the direct estimation of the underlying economic mechanisms, including a new volatility leverage effect, the persistence of the latent long-run growth component and the two latent volatility factors, as well as the contemporaneous impacts of the underlying “structural” shocks.

Suggested Citation

  • Tim Bollerslev & Lai Xu & Hao Zhou, 2012. "Stock Return and Cash Flow Predictability: The Role of Volatility Risk," CREATES Research Papers 2012-51, Department of Economics and Business Economics, Aarhus University.
  • Handle: RePEc:aah:create:2012-51
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    References listed on IDEAS

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    2. Chang, Chia-Lin & McAleer, Michael, 2015. "Econometric analysis of financial derivatives: An overview," Journal of Econometrics, Elsevier, vol. 187(2), pages 403-407.
    3. Dergiades, Theologos & Milas, Costas & Panagiotidis, Theodore, 2020. "A mixed frequency approach for stock returns and valuation ratios," Economics Letters, Elsevier, vol. 187(C).
    4. Shi, Jinyan & Yu, Conghui & Liu, Xiangkun & Li, Yanxi, 2020. "Predicting firm stock returns with customer stock returns: Moderating effects of customer characteristics," Research in International Business and Finance, Elsevier, vol. 54(C).
    5. Isabel Casas & Xiuping Mao & Helena Veiga, 2018. "Reexamining financial and economic predictability with new estimators of realized variance and variance risk premium," CREATES Research Papers 2018-10, Department of Economics and Business Economics, Aarhus University.
    6. Luo, Jiawen & Ji, Qiang & Klein, Tony & Todorova, Neda & Zhang, Dayong, 2020. "On realized volatility of crude oil futures markets: Forecasting with exogenous predictors under structural breaks," Energy Economics, Elsevier, vol. 89(C).
    7. Chava, Sudheer & Gallmeyer, Michael & Park, Heungju, 2015. "Credit conditions and stock return predictability," Journal of Monetary Economics, Elsevier, vol. 74(C), pages 117-132.
    8. Yiannis Karavias & Paresh Narayan & Joakim Westerlund, 2021. "Structural Breaks in Interactive Effects Panels and the Stock Market Reaction to COVID-19," Papers 2111.03035, arXiv.org.
    9. Yun, Jaeho, 2020. "A re-examination of the predictability of stock returns and cash flows via the decomposition of VIX," Economics Letters, Elsevier, vol. 186(C).
    10. Chang, C-L. & McAleer, M.J., 2014. "Econometric Analysis of Financial Derivatives," Econometric Institute Research Papers EI 2015-02, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    11. Gilles de Truchis & Elena Ivona Dumitrescu, 2019. "Narrow-band Weighted Nonlinear Least Squares Estimation of Unbalanced Cointegration Systems," EconomiX Working Papers 2019-14, University of Paris Nanterre, EconomiX.
    12. Walter Pohl & Karl Schmedders & Ole Wilms, 2018. "Higher Order Effects in Asset Pricing Models with Long‐Run Risks," Journal of Finance, American Finance Association, vol. 73(3), pages 1061-1111, June.
    13. Lopes Moreira Da Veiga, María Helena & Mao, Xiuping & Casas Villalba, Maria Isabel, 2020. "Adaptative predictability of stock market returns," DES - Working Papers. Statistics and Econometrics. WS 31648, Universidad Carlos III de Madrid. Departamento de Estadística.

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    More about this item

    Keywords

    Return and dividend growth predictability; variance risk premium; expected variation; long-run risk; equilibrium pricing; stochastic volatility and uncertainty; reduced form VAR; “structural” factor GARCH;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

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