Forecasting classification of operating performance of enterprises by ZSCORE combining ANFIS and genetic algorithm

Original Article

Abstract

Classification of operating performance of the enterprises is not only a hot issue emphasized by the management, but it is an important reference for investors too in their decision-making. 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 collected 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 hybrid model provides better classification forecasting capability than the other models, while the ANFIS model adjusted by genetic algorithm could effectively enhance the classification forecasting capability.

Keywords

ANFIS Genetic algorithm Grey relational analysis ZSCORE Hybrid model 

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Copyright information

© Springer-Verlag London Limited 2009

Authors and Affiliations

  1. 1.TaipeiTaiwan, ROC
  2. 2.Department of FinanceJinwen University of Science and TechnologyTaipeiTaiwan, ROC

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