• DocumentCode
    2833312
  • Title

    The Study of Impact from the GAANFIS Model on Business Performance

  • Author

    Pan Wen-tsao

  • Author_Institution
    Dept. of Finance, Jinwen Univ. of Sci. & Technol., Taipei
  • fYear
    2008
  • fDate
    Aug. 29 2008-Sept. 2 2008
  • Firstpage
    233
  • Lastpage
    237
  • Abstract
    Not only does business performance serve a major indicator for investors´ decision, but it also has a lot to do with employees´ living. Generally speaking, when predicting or analyzing business performance classification, most researchers adopt corporate financial early-warning or credit rating models, which pretty much use previous data and facts. Therefore, this paper brings about an alternative method to discriminate between excellent and poor business management, so as to take preventive measures prior to business crisis or bankruptcy. We collect the financial reports and financial ratios from the listed firms in mainland China and Taiwan as our samples to build up four kinds of forecasting models for business performance. The empirical results show that the GAANFIS model provides better classification forecasting capability than other models do, while ANFIS model adjusted by Genetic Algorithm could effectively enhance the classification forecasting capability.
  • Keywords
    financial management; forecasting theory; genetic algorithms; China; GAANFIS model; Taiwan; bankruptcy; business crisis; business management; business performance; classification forecasting; corporate financial early-warning; credit rating models; forecasting models; genetic algorithm; Companies; Computer science; Economic forecasting; Energy management; Financial management; Genetic algorithms; Performance analysis; Power generation economics; Power system management; Predictive models; ANFIS; Genetic Algorithm; Grey Relational Analysis; ROC curve; ZSCORE;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Information Technology, 2008. ICCSIT '08. International Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-0-7695-3308-7
  • Type

    conf

  • DOI
    10.1109/ICCSIT.2008.11
  • Filename
    4624867