IDEAS home Printed from https://ideas.repec.org/a/taf/applec/v54y2022i59p6784-6796.html
   My bibliography  Save this article

Fractal characteristics analysis and fluctuation trend prediction of commercial bank funding liquidity

Author

Listed:
  • Xu Wu
  • Ling-Ling Li

Abstract

Funding liquidity has been considered as the lifeline of commercial banks. If there are abnormal fluctuations in funding liquidity, it may lead to bank runs, which may bring about the destruction of commercial banks and even spread to cause a financial crisis. Therefore, exploring the fluctuation characteristics and trend prediction of commercial bank funding liquidity has traditionally attracted much attention. Based on this, this paper analyzes the fluctuation characteristics of commercial bank funding liquidity by Multi-Fractal Detrended Fluctuation Analysis (MF-DFA), and innovatively uses the Moving Trend Entropy Dimension (MTED) for commercial bank funding liquidity fluctuation trend prediction. The results of the study show that the commercial bank funding liquidity is multifractal, so it has predictability; MTED can not only accurately predict the fluctuation trend of commercial bank funding liquidity, but also has robustness. Through effective monitoring of funding liquidity, commercial banks can develop their funding liquidity risk management programs and improve the effectiveness of their own funding liquidity risk control. At the same time, regulators can also achieve the goal of preventing and resolving funding liquidity risks as well as maintaining financial stability.

Suggested Citation

  • Xu Wu & Ling-Ling Li, 2022. "Fractal characteristics analysis and fluctuation trend prediction of commercial bank funding liquidity," Applied Economics, Taylor & Francis Journals, vol. 54(59), pages 6784-6796, December.
    • Handle: RePEc:taf:applec:v:54:y:2022:i:59:p:6784-6796
    DOI: 10.1080/00036846.2022.2083571
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00036846.2022.2083571
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00036846.2022.2083571?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:54:y:2022:i:59:p:6784-6796. 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.