IDEAS home Printed from https://ideas.repec.org/a/rsk/journ5/7962480.html

Green risk identification and risk measurement in fintech: a particle swarm optimization fuzzy analytic hierarchy process and sparrow search algorithm quantile regression neural network approach

Author

Listed:
  • Li Zeng
  • Wee-Yeap Lau

Abstract

The development of financial technology (fintech) has given rise to a series of derivative potential risk issues, particularly in the domains of risk identification and risk measurement. This study analyzes the fintech sector by employing the fuzzy analytic hierarchy process combined with particle swarm optimization, as well as a quantile regression neural network (QRNN) model modified by the sparrow search algorithm (SSA), to comprehensively identify and measure financial risks. The SSA-QRNN model demonstrates considerable adaptability, high stability and high precision in assessing fintech risks. Suggestions are presented from diverse perspectives, offering valuable insights for risk management and sustainable development in the fintech sector.

Suggested Citation

  • Li Zeng & Wee-Yeap Lau, . "Green risk identification and risk measurement in fintech: a particle swarm optimization fuzzy analytic hierarchy process and sparrow search algorithm quantile regression neural network approach," Journal of Risk Model Validation, Journal of Risk Model Validation.
    • Handle: RePEc:rsk:journ5:7962480
    as

    Download full text from publisher

    File URL: https://www.risk.net/node/7962480
    Download Restriction: no
    ---><---

    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:rsk:journ5:7962480. 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: Thomas Paine (email available below). General contact details of provider: https://www.risk.net/journal-of-risk-model-validation .

    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.