IDEAS home Printed from https://ideas.repec.org/a/eee/jfinec/v154y2024ics0304405x2400031x.html
   My bibliography  Save this article

Persistent and transitory components of firm characteristics: Implications for asset pricing

Author

Listed:
  • Baba-Yara, Fahiz
  • Boons, Martijn
  • Tamoni, Andrea

Abstract

We study the horizon dimension of cross-sectional return predictability using a model where characteristics contain both persistent and transitory components. We test the implications of this model for the average returns of popular characteristic-based trading strategies at short versus long horizons after portfolio formation. Our evidence supports the claim that the relative compensation for persistent and transitory components varies across characteristics, in both magnitude and sign. Benchmark factor models cannot explain the returns of portfolios sorted on characteristics where either the persistent or transitory component is dominant. Finally, we discuss implications for the long-term discount rates of firms.

Suggested Citation

  • Baba-Yara, Fahiz & Boons, Martijn & Tamoni, Andrea, 2024. "Persistent and transitory components of firm characteristics: Implications for asset pricing," Journal of Financial Economics, Elsevier, vol. 154(C).
    • Handle: RePEc:eee:jfinec:v:154:y:2024:i:c:s0304405x2400031x
    DOI: 10.1016/j.jfineco.2024.103808
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304405X2400031X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jfineco.2024.103808?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Randolph B. Cohen & Christopher Polk & Tuomo Vuolteenaho, 2009. "The Price Is (Almost) Right," Journal of Finance, American Finance Association, vol. 64(6), pages 2739-2782, December.
    2. Joachim Freyberger & Andreas Neuhierl & Michael Weber & Andrew KarolyiEditor, 2020. "Dissecting Characteristics Nonparametrically," Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2326-2377.
    3. Mikhail Chernov & Lars A Lochstoer & Stig R H Lundeby, 2022. "Conditional Dynamics and the Multihorizon Risk-Return Trade-Off," The Review of Financial Studies, Society for Financial Studies, vol. 35(3), pages 1310-1347.
    4. Kelly, Bryan T. & Pruitt, Seth & Su, Yinan, 2019. "Characteristics are covariances: A unified model of risk and return," Journal of Financial Economics, Elsevier, vol. 134(3), pages 501-524.
    5. Gibbons, Michael R & Ross, Stephen A & Shanken, Jay, 1989. "A Test of the Efficiency of a Given Portfolio," Econometrica, Econometric Society, vol. 57(5), pages 1121-1152, September.
    6. Ivo Welch, 2022. "Simply Better Market Betas," Critical Finance Review, now publishers, vol. 11(1), pages 37-64, February.
    7. Kent Daniel & David Hirshleifer & Lin Sun, 2020. "Short- and Long-Horizon Behavioral Factors," The Review of Financial Studies, Society for Financial Studies, vol. 33(4), pages 1673-1736.
    8. Kent Daniel & Lira Mota & Simon Rottke & Tano Santos & Andrew KarolyiEditor, 2020. "The Cross-Section of Risk and Returns," Review of Finance, European Finance Association, vol. 33(5), pages 1927-1979.
    9. Daniel, Kent & Titman, Sheridan, 1997. "Evidence on the Characteristics of Cross Sectional Variation in Stock Returns," Journal of Finance, American Finance Association, vol. 52(1), pages 1-33, March.
    10. Martin Lettau & Markus Pelger & Stijn Van Nieuwerburgh, 2020. "Factors That Fit the Time Series and Cross-Section of Stock Returns," The Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2274-2325.
    11. Kozak, Serhiy & Nagel, Stefan & Santosh, Shrihari, 2020. "Shrinking the cross-section," Journal of Financial Economics, Elsevier, vol. 135(2), pages 271-292.
    12. Keloharju, Matti & Linnainmaa, Juhani T. & Nyberg, Peter, 2021. "Long-term discount rates do not vary across firms," Journal of Financial Economics, Elsevier, vol. 141(3), pages 946-967.
    13. Shihao Gu & Bryan Kelly & Dacheng Xiu, 2020. "Empirical Asset Pricing via Machine Learning," The Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2223-2273.
    14. Theis Ingerslev Jensen & Bryan T. Kelly & Semyon Malamud & Lasse Heje Pedersen, 2022. "Machine Learning and the Implementable Efficient Frontier," Swiss Finance Institute Research Paper Series 22-63, Swiss Finance Institute.
    15. Martin Lettau & Markus Pelger, 2020. "Factors That Fit the Time Series and Cross-Section of Stock Returns," Review of Finance, European Finance Association, vol. 33(5), pages 2274-2325.
    16. Kothari, S P & Shanken, Jay & Sloan, Richard G, 1995. "Another Look at the Cross-Section of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 50(1), pages 185-224, March.
    17. Joao Gomes & Leonid Kogan & Lu Zhang, 2003. "Equilibrium Cross Section of Returns," Journal of Political Economy, University of Chicago Press, vol. 111(4), pages 693-732, August.
    18. Kent Daniel & Lira Mota & Simon Rottke & Tano Santos, 2020. "The Cross-Section of Risk and Returns," The Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 1927-1979.
    19. Kewei Hou & Chen Xue & Lu Zhang, 2015. "Editor's Choice Digesting Anomalies: An Investment Approach," The Review of Financial Studies, Society for Financial Studies, vol. 28(3), pages 650-705.
    20. Fama, Eugene F. & French, Kenneth R., 2015. "A five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 116(1), pages 1-22.
    21. Clifford S. Asness & Tobias J. Moskowitz & Lasse Heje Pedersen, 2013. "Value and Momentum Everywhere," Journal of Finance, American Finance Association, vol. 68(3), pages 929-985, June.
    22. Jegadeesh, Narasimhan & Titman, Sheridan, 1993. "Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency," Journal of Finance, American Finance Association, vol. 48(1), pages 65-91, March.
    23. Fama, Eugene F & French, Kenneth R, 1992. "The Cross-Section of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 47(2), pages 427-465, June.
    24. Shihao Gu & Bryan Kelly & Dacheng Xiu, 2020. "Empirical Asset Pricing via Machine Learning," Review of Finance, European Finance Association, vol. 33(5), pages 2223-2273.
    25. Jianan Liu & Tobias J. Moskowitz & Robert F. Stambaugh, 2021. "Pricing Without Mispricing," NBER Working Papers 29016, National Bureau of Economic Research, Inc.
    26. Jeremiah Green & John R. M. Hand & X. Frank Zhang, 2017. "The Characteristics that Provide Independent Information about Average U.S. Monthly Stock Returns," The Review of Financial Studies, Society for Financial Studies, vol. 30(12), pages 4389-4436.
    27. Kent Daniel & David Hirshleifer & Lin Sun, 2020. "Short- and Long-Horizon Behavioral Factors," Review of Finance, European Finance Association, vol. 33(4), pages 1673-1736.
    28. Robert Novy-Marx & Mihail Velikov, 2016. "A Taxonomy of Anomalies and Their Trading Costs," The Review of Financial Studies, Society for Financial Studies, vol. 29(1), pages 104-147.
    29. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    30. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Clarke, Charles, 2022. "The level, slope, and curve factor model for stocks," Journal of Financial Economics, Elsevier, vol. 143(1), pages 159-187.
    2. Söhnke M. Bartram & Harald Lohre & Peter F. Pope & Ananthalakshmi Ranganathan, 2021. "Navigating the factor zoo around the world: an institutional investor perspective," Journal of Business Economics, Springer, vol. 91(5), pages 655-703, July.
    3. van Binsbergen, Jules H. & Boons, Martijn & Opp, Christian C. & Tamoni, Andrea, 2023. "Dynamic asset (mis)pricing: Build-up versus resolution anomalies," Journal of Financial Economics, Elsevier, vol. 147(2), pages 406-431.
    4. Langlois, Hugues, 2023. "What matters in a characteristic?," Journal of Financial Economics, Elsevier, vol. 149(1), pages 52-72.
    5. Guillaume Coqueret, 2022. "Characteristics-driven returns in equilibrium," Papers 2203.07865, arXiv.org.
    6. Ma, Tian & Leong, Wen Jun & Jiang, Fuwei, 2023. "A latent factor model for the Chinese stock market," International Review of Financial Analysis, Elsevier, vol. 87(C).
    7. Rubesam, Alexandre, 2022. "Machine learning portfolios with equal risk contributions: Evidence from the Brazilian market," Emerging Markets Review, Elsevier, vol. 51(PB).
    8. Bandi, Federico M. & Chaudhuri, Shomesh E. & Lo, Andrew W. & Tamoni, Andrea, 2021. "Spectral factor models," Journal of Financial Economics, Elsevier, vol. 142(1), pages 214-238.
    9. Cakici, Nusret & Fieberg, Christian & Metko, Daniel & Zaremba, Adam, 2023. "Machine learning goes global: Cross-sectional return predictability in international stock markets," Journal of Economic Dynamics and Control, Elsevier, vol. 155(C).
    10. Doron Avramov & Guy Kaplanski & Avanidhar Subrahmanyam, 2022. "Postfundamentals Price Drift in Capital Markets: A Regression Regularization Perspective," Management Science, INFORMS, vol. 68(10), pages 7658-7681, October.
    11. Svetlana Bryzgalova & Jiantao Huang & Christian Julliard, 2023. "Bayesian Solutions for the Factor Zoo: We Just Ran Two Quadrillion Models," Journal of Finance, American Finance Association, vol. 78(1), pages 487-557, February.
    12. Azevedo, Vitor, 2023. "Analysts’ underreaction and momentum strategies," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).
    13. G Andrew Karolyi & Stijn Van Nieuwerburgh, 2020. "New Methods for the Cross-Section of Returns," Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 1879-1890.
    14. Chen, Andrew Y. & McCoy, Jack, 2024. "Missing values handling for machine learning portfolios," Journal of Financial Economics, Elsevier, vol. 155(C).
    15. Doron Avramov & Si Cheng & Lior Metzker, 2023. "Machine Learning vs. Economic Restrictions: Evidence from Stock Return Predictability," Management Science, INFORMS, vol. 69(5), pages 2587-2619, May.
    16. Bagnara, Matteo, 2024. "The economic value of cross-predictability: A performance-based measure," SAFE Working Paper Series 424, Leibniz Institute for Financial Research SAFE.
    17. Joachim Freyberger & Andreas Neuhierl & Michael Weber, 2020. "Dissecting Characteristics Nonparametrically," The Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2326-2377.
    18. Vitor Azevedo & Georg Sebastian Kaiser & Sebastian Mueller, 2023. "Stock market anomalies and machine learning across the globe," Journal of Asset Management, Palgrave Macmillan, vol. 24(5), pages 419-441, September.
    19. Wolfgang Drobetz & Tizian Otto, 2021. "Empirical asset pricing via machine learning: evidence from the European stock market," Journal of Asset Management, Palgrave Macmillan, vol. 22(7), pages 507-538, December.
    20. Yan, Jingda & Yu, Jialin, 2023. "Cross-stock momentum and factor momentum," Journal of Financial Economics, Elsevier, vol. 150(2).

    More about this item

    Keywords

    Characteristics; Persistent-transitory decomposition; Cross-section; Return predictability; Discount rates;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jfinec:v:154:y:2024:i:c:s0304405x2400031x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/505576 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.