• DocumentCode
    2116225
  • Title

    An Empirical Study on Financial Distress Prediction Taking into Account the Expected Default Frequency

  • Author

    Song, Xiaoli

  • Author_Institution
    Sch. of Manage., Zhejiang Univ., Hangzhou, China
  • Volume
    2
  • fYear
    2010
  • fDate
    7-8 Aug. 2010
  • Firstpage
    507
  • Lastpage
    510
  • Abstract
    Based on a lot of related literatures, the authors suggest a Financial Distress Prediction System incorporated the Expected Default Frequency (EDF) into Logit regression model. The empirical findings suggest that the EDF calculated by KMV model is significantly associated with the probability of default in both 3rd and 4th quarters prior to the financial crisis of sample firms. Thus, an incorporation of EDF into the financial distress system does enhance its overall accuracy.
  • Keywords
    finance; regression analysis; KMV model; expected default frequency; financial distress prediction system; logit regression model; Banking; Biological system modeling; Companies; Correlation; Data models; Finance; Predictive models; KMV model; Logit regression; credit risk; financial distress;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science and Management Engineering (ISME), 2010 International Conference of
  • Conference_Location
    Xi´an
  • Print_ISBN
    978-1-4244-7669-5
  • Electronic_ISBN
    978-1-4244-7670-1
  • Type

    conf

  • DOI
    10.1109/ISME.2010.107
  • Filename
    5573776