IDEAS home Printed from https://ideas.repec.org/a/wly/jforec/v33y2014i8p611-626.html
   My bibliography  Save this article

Application of Machine Learning Methods to Risk Assessment of Financial Statement Fraud: Evidence from China

Author

Listed:
  • Xin‐Ping Song
  • Zhi‐Hua Hu
  • Jian‐Guo Du
  • Zhao‐Han Sheng

Abstract

No abstract is available for this item.

Suggested Citation

  • Xin‐Ping Song & Zhi‐Hua Hu & Jian‐Guo Du & Zhao‐Han Sheng, 2014. "Application of Machine Learning Methods to Risk Assessment of Financial Statement Fraud: Evidence from China," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(8), pages 611-626, December.
  • Handle: RePEc:wly:jforec:v:33:y:2014:i:8:p:611-626
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Yasheng Chen & Zhuojun Wu, 2022. "Financial Fraud Detection of Listed Companies in China: A Machine Learning Approach," Sustainability, MDPI, vol. 15(1), pages 1-15, December.
    2. Mohammad Abdullah & Mohammad Ashraful Ferdous Chowdhury & Ajim Uddin & Syed Moudud‐Ul‐Huq, 2023. "Forecasting nonperforming loans using machine learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1664-1689, November.
    3. Md Jahidur Rahman & Hongtao Zhu, 2023. "Predicting accounting fraud using imbalanced ensemble learning classifiers – evidence from China," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(3), pages 3455-3486, September.
    4. Bangzhu Zhu & Shunxin Ye & Ping Wang & Julien Chevallier & Yi‐Ming Wei, 2022. "Forecasting carbon price using a multi‐objective least squares support vector machine with mixture kernels," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(1), pages 100-117, January.
    5. Islam, Md Rafiqul & Liu, Shaowu & Biddle, Rhys & Razzak, Imran & Wang, Xianzhi & Tilocca, Peter & Xu, Guandong, 2021. "Discovering dynamic adverse behavior of policyholders in the life insurance industry," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    6. Zhang, Yi & Hu, Ailing & Wang, Jiahua & Zhang, Yaojie, 2022. "Detection of fraud statement based on word vector: Evidence from financial companies in China," Finance Research Letters, Elsevier, vol. 46(PB).
    7. He Jiang, 2023. "Forecasting global solar radiation using a robust regularization approach with mixture kernels," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 1989-2010, December.
    8. Behera, Rajat Kumar & Bala, Pradip Kumar & Rana, Nripendra P. & Kizgin, Hatice, 2022. "Cognitive computing based ethical principles for improving organisational reputation: A B2B digital marketing perspective," Journal of Business Research, Elsevier, vol. 141(C), pages 685-701.
    9. Salonee Patel & Manan Shah, 2023. "A Comprehensive Study on Implementing Big Data in the Auditing Industry," Annals of Data Science, Springer, vol. 10(3), pages 657-677, June.

    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:wly:jforec:v:33:y:2014:i:8:p:611-626. 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://www3.interscience.wiley.com/cgi-bin/jhome/2966 .

    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.