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On the Long-Run Volatility of Stocks

Author

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  • Carlos M. Carvalho
  • Hedibert F. Lopes
  • Robert E. McCulloch

Abstract

In this article, we investigate whether or not the volatility per period of stocks is lower over longer horizons. Taking the perspective of an investor, we evaluate the predictive variance of k-period returns under different model and prior specifications. We adopt the state-space framework of Pástor and Stambaugh to model the dynamics of expected returns and evaluate the effects of prior elicitation in the resulting volatility estimates. Part of the developments includes an extension that incorporates time-varying volatilities and covariances in a constrained prior information set-up. Our conclusion for the U.S. market, under plausible prior specifications, is that stocks are less volatile in the long run. Model assessment exercises demonstrate the models and priors supporting our main conclusions are in accordance with the data. To assess the generality of the results, we extend our analysis to a number of international equity indices. Supplementary materials for this article are available online.

Suggested Citation

  • Carlos M. Carvalho & Hedibert F. Lopes & Robert E. McCulloch, 2018. "On the Long-Run Volatility of Stocks," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(523), pages 1050-1069, July.
    • Handle: RePEc:taf:jnlasa:v:113:y:2018:i:523:p:1050-1069
    DOI: 10.1080/01621459.2017.1407769
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    Citations

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    Cited by:

    1. Davide Delle Monache & Ivan Petrella & Fabrizio Venditti, 2021. "Price Dividend Ratio and Long-Run Stock Returns: A Score-Driven State Space Model," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(4), pages 1054-1065, October.
    2. Mazur Błażej & Pipień Mateusz, 2018. "Time-varying asymmetry and tail thickness in long series of daily financial returns," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(5), pages 1-21, December.
    3. repec:wrk:wrkemf:29 is not listed on IDEAS
    4. Lopes, Hedibert F. & McCulloch, Robert E. & Tsay, Ruey S., 2022. "Parsimony inducing priors for large scale state–space models," Journal of Econometrics, Elsevier, vol. 230(1), pages 39-61.
    5. Scott Cederburg & Travis L Johnson & Michael S O’Doherty, 2023. "On the Economic Significance of Stock Return Predictability," Review of Finance, European Finance Association, vol. 27(2), pages 619-657.
    6. Anarkulova, Aizhan & Cederburg, Scott & O’Doherty, Michael S., 2022. "Stocks for the long run? Evidence from a broad sample of developed markets," Journal of Financial Economics, Elsevier, vol. 143(1), pages 409-433.

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