• DocumentCode
    2654042
  • Title

    Financial Distress Prediction Models of China´s Listed Companies

  • Author

    Guo-ming, Qian ; Yuan, Feng ; Ling, Zhou

  • Author_Institution
    Harbin Inst. of Technol., Harbin
  • fYear
    2007
  • fDate
    20-22 Aug. 2007
  • Firstpage
    1824
  • Lastpage
    1829
  • Abstract
    Research of financial distress prediction models has just started in China, and there are some differences between the study abroad and that in China both from the methods and the perspective of research, which are mainly due to the difference of the degree of maturity of the capital market and the imperfections of research methods. Using listed manufacturing industry as its research object and whether the listed company has been special transaction because "the financial conditions are unusual" as a sign of financial distress, this paper adopts the canonical discriminant analysis method of the multivariate discriminant analysis, applies several variables which can cover every aspect of a listed company\´s financial position, utilize the financial data from the audited financial statements and search the variables and prediction models that can predict the financial distress of listed companies as accurately as possible.
  • Keywords
    financial management; investment; manufacturing industries; statistical analysis; China listed companies; audited financial statements; canonical discriminant analysis; capital market; financial distress prediction models; listed manufacturing industry; multivariate discriminant analysis; Artificial neural networks; Conference management; Engineering management; Financial management; Forward contracts; Information technology; Logistics; Predictive models; Regression analysis; Technology management; financial distress; listed company; prediction models; the multivariate discriminant analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Management Science and Engineering, 2007. ICMSE 2007. International Conference on
  • Conference_Location
    Harbin
  • Print_ISBN
    978-7-88358-080-5
  • Electronic_ISBN
    978-7-88358-080-5
  • Type

    conf

  • DOI
    10.1109/ICMSE.2007.4422105
  • Filename
    4422105