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Horizon Effects in Average Returns: The Role of Slow Information Diffusion

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  • Oliver Boguth
  • Murray Carlson
  • Adlai Fisher
  • Mikhail Simutin

Abstract

We characterize linkages between average returns calculated at different horizons. Theoretically, when stocks incorporate information slowly, average short-horizon returns are downward biased. Buy-and-hold strategies can amplify the effect. In contrast, existing theories analyze price noises that are independent of fundamentals, and buy-and-hold portfolio returns are unaffected. We document horizon effects as large as 10% annualized in daily and monthly style portfolios and international indices. Slow reaction to market information, identified by gradually declining lagged betas, is an important cause. These findings have natural consequences for performance evaluation. Received July 2, 2012; accepted June 28, 2015 by Editor Andrew Karolyi.

Suggested Citation

  • Oliver Boguth & Murray Carlson & Adlai Fisher & Mikhail Simutin, 2016. "Horizon Effects in Average Returns: The Role of Slow Information Diffusion," The Review of Financial Studies, Society for Financial Studies, vol. 29(8), pages 2241-2281.
    • Handle: RePEc:oup:rfinst:v:29:y:2016:i:8:p:2241-2281.
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    File URL: http://hdl.handle.net/10.1093/rfs/hhw024
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    Cited by:

    1. Bessembinder, Hendrik & Cooper, Michael J. & Zhang, Feng, 2023. "Mutual fund performance at long horizons," Journal of Financial Economics, Elsevier, vol. 147(1), pages 132-158.
    2. Semenov, Andrei, 2021. "Measuring the stock's factor beta and identifying risk factors under market inefficiency," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 635-649.
    3. Chenglu Jin & Thomas Conlon & John Cotter, 2023. "Co-Skewness across Return Horizons," Journal of Financial Econometrics, Oxford University Press, vol. 21(5), pages 1483-1518.
    4. Sharifkhani, Ali & Simutin, Mikhail, 2021. "Feedback loops in industry trade networks and the term structure of momentum profits," Journal of Financial Economics, Elsevier, vol. 141(3), pages 1171-1187.
    5. Jiawei Wang & Zhen Chen, 2023. "Exploring Low-Risk Anomalies: A Dynamic CAPM Utilizing a Machine Learning Approach," Mathematics, MDPI, vol. 11(14), pages 1-22, July.
    6. Oliver Boguth & Murray Carlson & Adlai Fisher & Mikhail Simutin, 2023. "The Term Structure of Equity Risk Premia: Levered Noise and New Estimates," Review of Finance, European Finance Association, vol. 27(4), pages 1155-1182.
    7. Isaenko, Sergey, 2023. "Trading strategies and the frequency of time-series," The Quarterly Review of Economics and Finance, Elsevier, vol. 90(C), pages 267-283.
    8. Peter Cziraki & Jordi Mondria & Thomas Wu, 2021. "Asymmetric Attention and Stock Returns," Management Science, INFORMS, vol. 67(1), pages 48-71, January.

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