IDEAS home Printed from https://ideas.repec.org/a/eee/ecmode/v157y2026ics0264999326000295.html

Market professional performance under insider information leakage

Author

Listed:
  • Ma, Yu
  • Liu, Hong
  • Wang, Jing

Abstract

We construct a multiagent model in which an insider simultaneously discloses information to a market professional and outsiders, and characterize the resulting linear equilibrium. Our analysis yields three main results. First, the insider strategically adjusts the precision of disclosure based on the quality of the market professional information. Second, when the market professional is well-informed, their expected profits under information leakage exceed those without leakage, resulting in a form of self-relative outperformance that departs from previous theories. Third, market liquidity and price efficiency exhibit an inverted U-shaped relationship with the precision of the market professional’s information. Using Chinese A-share data, we find empirical evidence consistent with these predictions. We find that information spillovers may coexist with stronger incentives for information production, underscoring the need for tailored regulatory approaches.

Suggested Citation

  • Ma, Yu & Liu, Hong & Wang, Jing, 2026. "Market professional performance under insider information leakage," Economic Modelling, Elsevier, vol. 157(C).
  • Handle: RePEc:eee:ecmode:v:157:y:2026:i:c:s0264999326000295
    DOI: 10.1016/j.econmod.2026.107500
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0264999326000295
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.econmod.2026.107500?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

    for a different version of it.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:ecmode:v:157:y:2026:i:c:s0264999326000295. 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/inca/30411 .

    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.