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
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