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Asset Pricing Restrictions on Predictability: Frictions Matter

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  • Frans de Roon

    (Department of Finance and CentER, Tilburg University, 5000 LE Tilburg, The Netherlands)

  • Marta Szymanowska

    (Rotterdam School of Management, Erasmus University, 3000 DR Rotterdam, The Netherlands)

Abstract

U.S. stock portfolios sorted on size; momentum; transaction costs; market-to-book, investment-to-assets, and return-on-assets (ROA) ratios; and industry classification show considerable levels and variation of return predictability, inconsistent with asset pricing models. This means that a predictable risk premium is not equal to compensation for systematic risk as implied by asset pricing theory. We show that introducing market frictions relaxes these asset pricing moments from a strict equality to a range. Empirically, it is not short sales constraints but transaction costs (below 35 basis points) that help to reconcile the observed predictability with linear portfolio return-based factor models, and partly with the durable consumption model. Across the sorts, predictability in industry returns can be reconciled with all models considered with only a 25 basis point transaction cost, whereas for momentum and ROA portfolios, up to 115 basis points are needed. This paper was accepted by Wei Xiong, finance.

Suggested Citation

  • Frans de Roon & Marta Szymanowska, 2012. "Asset Pricing Restrictions on Predictability: Frictions Matter," Management Science, INFORMS, vol. 58(10), pages 1916-1932, October.
    • Handle: RePEc:inm:ormnsc:v:58:y:2012:i:10:p:1916-1932
    DOI: 10.1287/mnsc.1120.1522
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    Cited by:

    1. Jonathan Fletcher, 2018. "An Examination of the Benefits of Factor Investing in U.K. Stock Returns," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 10(4), pages 154-170, April.
    2. Park, Jin Suk & Newaz, Mohammad Khaleq, 2021. "Liquidity and short-run predictability: Evidence from international stock markets," Global Finance Journal, Elsevier, vol. 50(C).
    3. Michael Nwogugu, 2020. "Regret Theory And Asset Pricing Anomalies In Incomplete Markets With Dynamic Un-Aggregated Preferences," Papers 2005.01709, arXiv.org.
    4. Fletcher, Jonathan, 2018. "An empirical examination of the diversification benefits of U.K. international equity closed-end funds," International Review of Financial Analysis, Elsevier, vol. 55(C), pages 23-34.
    5. Hansen, Erwin, 2022. "Economic evaluation of asset pricing models under predictability," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 50-66.
    6. Favero, Carlo A. & Tamoni, Andrea & Ortu, Fulvio & Yang, Haoxi, 2016. "Implications of Return Predictability across Horizons for Asset Pricing Models," CEPR Discussion Papers 11645, C.E.P.R. Discussion Papers.

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