A Fuzzy Decision Aiding Method for the Assessment of Corporate Bankruptcy
In many real world problems it is often difficult to find dependencies between the variables of a process or more general of a system, dependencies which can be used for controlling a plant, forecasting a value or classifying a group of objects into pre-defined classes. Since in many cases, analytic dependencies are unknown or very difficult to set up, the formulation of dependencies with the help of fuzzy rules offers a useful alternative. This paper presents the combined use of a fuzzy rule generation method and a data mining technique for financial risk assessment. The case of business failure is considered here and the classification of the firms into two classes is sought. Initially, a method for the generation of fuzzy rules is used. Then these rules are imported to a data mining technique so as the firms can be classified into as bankrupt or non-bankrupt. The fuzzy method supports the discovery of relevant dependencies by the automatic generation of if/then rules on the basis of expert knowledge, while the data mining technique, with the help of a fuzzy rule-based classifier, assigns an object to different classes on the basis of various different characteristics (financial ratios). Finally, a thorough comparison with discriminant analysis, logit and probit analysis is performed based on the same sample.
To our knowledge, this item is not available for
download. To find whether it is available, there are three
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
Volume (Year): VIII (2003)
Issue (Month): 1 (May)
|Contact details of provider:|| Phone: +34 977759833|
Web page: http://www.sigef.net
More information through EDIRC