IDEAS home Printed from https://ideas.repec.org/a/bla/jbfnac/v45y2018i9-10p1100-1138.html
   My bibliography  Save this article

Abnormal trading behavior of specific types of shareholders before US firm bankruptcy and its implications for firm bankruptcy prediction

Author

Listed:
  • Christine Cheng
  • Stewart Jones
  • William J. Moser

Abstract

This paper examines the trading behavior of US corporate insiders and certain groups of institutional investors (short‐term, transient, top‐performing, and those with fiduciary responsibility) in the eight quarters leading up to a US firm bankruptcy filing. Using a matched sample based on year, industry, and a probability of future bankruptcy model, we find that US corporate insiders display abnormal reduced net trading activity in the quarters before bankruptcy, with corporate insiders ‘going quiet’ immediately preceding a US bankruptcy. In contrast, we find that our identified types of institutional shareholders display abnormal selling activity several quarters before a US bankruptcy. We then use this information to enhance the bankruptcy‐predictive capabilities of recent machine‐learning techniques such as gradient boosting, as well as the probability of future bankruptcy model. We find that the variables measuring the absolute value of net purchases by US corporate insiders in the two quarters prior to bankruptcy, along with the changes in ownership by specific types of institutional shareholders, improve the out‐of‐sample predictive capabilities of our two different bankruptcy prediction models. Overall, we find that specific types of shareholder display abnormal trading in the quarters preceding US firm bankruptcy, and such information improves the out‐of‐sample accuracy of firm bankruptcy prediction models.

Suggested Citation

  • Christine Cheng & Stewart Jones & William J. Moser, 2018. "Abnormal trading behavior of specific types of shareholders before US firm bankruptcy and its implications for firm bankruptcy prediction," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 45(9-10), pages 1100-1138, October.
  • Handle: RePEc:bla:jbfnac:v:45:y:2018:i:9-10:p:1100-1138
    DOI: 10.1111/jbfa.12338
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/jbfa.12338
    Download Restriction: no

    File URL: https://libkey.io/10.1111/jbfa.12338?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
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lohmann, Christian & Möllenhoff, Steffen, 2023. "Dark premonitions: Pre-bankruptcy investor attention and behavior," Journal of Banking & Finance, Elsevier, vol. 151(C).
    2. Beiqi Lin & Chelsea Liu & Kelvin Jui Keng Tan & Qing Zhou, 2020. "CEO turnover and bankrupt firms’ emergence," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 47(9-10), pages 1238-1267, October.
    3. Marc J. M. Bohmann & Vinay Patel, 2022. "Informed options trading prior to FDA announcements," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 49(7-8), pages 1211-1236, July.
    4. Noora Alzayed & Rasol Eskandari & Hassan Yazdifar, 2023. "Bank failure prediction: corporate governance and financial indicators," Review of Quantitative Finance and Accounting, Springer, vol. 61(2), pages 601-631, August.
    5. Mohammad Shamsu Uddin & Guotai Chi & Mazin A. M. Al Janabi & Tabassum Habib & Kunpeng Yuan, 2022. "Modeling credit risk with a multi‐stage hybrid model: An alternative statistical approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(7), pages 1386-1415, November.
    6. Ying Zhou & Xia Lin & Guotai Chi & Peng Jin & Mengtong Li, 2024. "EWT‐SMOTE to improve default prediction performance in imbalanced data: Analysis of Chinese data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(3), pages 615-643, April.

    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:bla:jbfnac:v:45:y:2018:i:9-10:p:1100-1138. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0306-686X .

    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.