IDEAS home Printed from https://ideas.repec.org/a/taf/applec/v55y2023i21p2455-2476.html
   My bibliography  Save this article

Does a firm’s geographic feature matter for stock returns? Evidence from the Chinese A-share market

Author

Listed:
  • Changyang Liu
  • Tian Yue
  • Yugang Yin

Abstract

This study reveals a new stock return predictability that relates to firms’ geographic features in the Chinese A-share market. Using a text-based measure of the degree of localness to capture the economic ties between firms and their provinces, we find that low-localized firms are slow to incorporate local information into stock prices. Specifically, there is a significant lead-lag effect in stock returns between high- and low-localized firms in the same region, and a portfolio that exploits this pattern can generate a monthly alpha of about 1%. This effect cannot be explained by geographic or industry return momentum, investors’ inattention, and limits to arbitrage. We find that this return predictability is mainly driven by investors’ limited information-processing capacity, and the evidence of predictability is stronger among low-localized firms with highly complicated business structures.

Suggested Citation

  • Changyang Liu & Tian Yue & Yugang Yin, 2023. "Does a firm’s geographic feature matter for stock returns? Evidence from the Chinese A-share market," Applied Economics, Taylor & Francis Journals, vol. 55(21), pages 2455-2476, May.
    • Handle: RePEc:taf:applec:v:55:y:2023:i:21:p:2455-2476
    DOI: 10.1080/00036846.2022.2103080
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00036846.2022.2103080
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00036846.2022.2103080?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

    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:taf:applec:v:55:y:2023:i:21:p:2455-2476. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RAEC20 .

    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.