A Financial Distress Pre-Warning Study by Fuzzy Regression Model of TSE-Listed Companies
AbstractThe purpose of this paper is to construct a financial distress pre-warning model for investors and risk supervisors. Through the Securities and Futures Institute Network, we collect the financial data of the electronic companies listing on the Taiwan Security Exchange (TSE) from 1998 to 2005. By binary logistic regression test, we found that financial statement ratios show significant difference in different financial stages. On the other hand, using fuzzy regression model, we construct a rating model of financial administration stages for investors and risk supervisors and found that prediction validity for financial distress companies and total companies by fuzzy regression model are better than binary logistic regression model using our research sample (89.77 and 90.98% vs. 85.27 and 90.30%).
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Bibliographic InfoArticle provided by Penerbit Universiti Sains Malaysia in its journal Asian Academy of Management Journal of Accounting and Finance.
Volume (Year): 2 (2006)
Issue (Month): 2 ()
risk management; financial distress; pre-warning; binary logistic regression; fuzzy regression model;
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- Eleftherios Giovanis, 2010. "Application of logit model and self-organizing maps (SOMs) for the prediction of financial crisis periods in US economy," Journal of Financial Economic Policy, Emerald Group Publishing, vol. 2(2), pages 98-125, June.
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