IDEAS home Printed from https://ideas.repec.org/a/eee/riibaf/v69y2024ics027553192400062x.html
   My bibliography  Save this article

Quality acceleration and cross-sectional returns: Empirical evidence

Author

Listed:
  • Ma, Yao
  • Yang, Baochen
  • Ye, Tao

Abstract

This study investigates the relationship between quality acceleration and cross-sectional returns, and explores the source of quality acceleration effect. We provide empirical evidence that quality acceleration positively and significantly predicts subsequent stock returns, and this predictive ability of quality acceleration lasts for three months, and does not reverse in the long term. These results are robust to alternative subsamples and alternative measures of quality acceleration, and common anomalies. The prediction information contained in quality acceleration is not subsumed by quality level and quality growth, and even exceeds the prediction information contained in quality level and growth. Consistent with a behavioral mispricing explanation, we find that the quality acceleration effect becomes stronger in the period of high investor sentiment, while the quality acceleration effect becomes weaker or even disappears in the period of low investor sentiment. However, the quality acceleration effect cannot be explained by limits to arbitrage and investor attention. Finally, quality acceleration has incremental predictive power for future one-quarter-ahead earnings growth, as well as future two- and three-quarters-ahead quality growth, which could be overlooked by investors.

Suggested Citation

  • Ma, Yao & Yang, Baochen & Ye, Tao, 2024. "Quality acceleration and cross-sectional returns: Empirical evidence," Research in International Business and Finance, Elsevier, vol. 69(C).
  • Handle: RePEc:eee:riibaf:v:69:y:2024:i:c:s027553192400062x
    DOI: 10.1016/j.ribaf.2024.102269
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S027553192400062X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ribaf.2024.102269?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.

    More about this item

    Keywords

    Quality acceleration; Return predictability; Mispricing; Investor sentiment; Limits to arbitrage;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

    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:riibaf:v:69:y:2024:i:c:s027553192400062x. 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.

    We have no bibliographic references for this item. You can help adding them by using 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/ribaf .

    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.