• DocumentCode
    2157476
  • Title

    The Financial Early-Warning Model of Listed Companies

  • Author

    Tian, Qing

  • Author_Institution
    Sch. of Manage. Sci. & Eng., Dongbei Univ. of Finance & Econ., Dalian, China
  • fYear
    2010
  • fDate
    24-26 Aug. 2010
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    This paper use Microsoft SQL Server 2005 data mining tools and three methods of neural networks, decision trees and logistic regression to establish the financial crisis early-warning model of listed companies. The conclusion is that the three kinds of methods have good results and the prediction accuracy rate are 80% or more. The accuracy of the decision tree algorithm model is higher than others.
  • Keywords
    data mining; decision trees; financial management; neural nets; regression analysis; Microsoft SQL Server 2005 data mining tool; decision trees; financial crisis early-warning model; listed companies; logistic regression; neural network; prediction accuracy; Analytical models; Artificial neural networks; Biological system modeling; Companies; Data models; Predictive models; Profitability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Management and Service Science (MASS), 2010 International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-5325-2
  • Electronic_ISBN
    978-1-4244-5326-9
  • Type

    conf

  • DOI
    10.1109/ICMSS.2010.5576555
  • Filename
    5576555
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2157476