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%).
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
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;
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- 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.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Journal Division).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.