IDEAS home Printed from https://ideas.repec.org/a/taf/tjsmxx/v16y2022i2p132-146.html
   My bibliography  Save this article

A multi-agent simulation of investment choice in the P2P lending market with bankruptcy risk

Author

Listed:
  • Jiajia Liu
  • Jichang Dong

Abstract

A challenge for investors in P2P lending marketplaces is to find an effective allocation of their funds across different loans by assessing the widespread collapse of lending platforms and each loan’s default risk. This paper investigates risk-averse/risk-tolerant/risk-neutral investors’ and borrowers’ transaction behaviours, as well as P2P lending platforms’ operating mechanism. A Heterogeneous Investors Multi-Agent Model (HIMAM) is built to simulate agents’ reactions to variance in platform’s bankruptcy risk. This enables an assessment of changes in investors’ average return rates and investment decisions. This study finds that platform bankruptcy risk influences total investment amounts and average return rates. The correlation between the transaction fee and total investment amount presents as an inverted U-shape. Furthermore, there is a negative correlation between two-part tariffs and both investors’ average return rates and the number of investors. This is because two-part tariffs are dependent on investors’ transaction volumes. High two-part tariffs increase investors’ transaction costs. Additionally, considering bankruptcy and default risk, credit E are the most popular type of borrower because such borrower tradeoff higher risk for higher return; credits B and C are the least popular type of borrower.

Suggested Citation

  • Jiajia Liu & Jichang Dong, 2022. "A multi-agent simulation of investment choice in the P2P lending market with bankruptcy risk," Journal of Simulation, Taylor & Francis Journals, vol. 16(2), pages 132-146, March.
  • Handle: RePEc:taf:tjsmxx:v:16:y:2022:i:2:p:132-146
    DOI: 10.1080/17477778.2020.1759386
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/17477778.2020.1759386
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/17477778.2020.1759386?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:tjsmxx:v:16:y:2022:i:2:p:132-146. 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/tjsm .

    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.