Application of Company Financial Crisis Early Warning Model- Use of “Financial Reference Database“

In July 1, 2007, Taiwan Stock Exchange (TWSE) on market observation post system (MOPS) adds a new "Financial reference database" for investors to do investment reference. This database as a warning to public offering companies listed on the public financial information and it original within eight targets. In this paper, this database provided by the indicators for the application of company financial crisis early warning model verify that the database provided by the indicator forecast for the financial crisis, whether or not companies have a high accuracy rate as opposed to domestic and foreign scholars have positive results. There is use of Logistic Regression Model application of the financial early warning model, in which no joined back-conditions is the first model, joined it in is the second model, has been taken occurred in the financial crisis of companies to research samples and then business took place before the financial crisis point with T-1 and T-2 sample data to do positive analysis. The results show that this database provided the debt ratio and net per share for the best forecast variables.

Authors:

• Chiung-ying Lee
• Chia-hua Chang

Keywords:

• Financial reference database
• Financial early warning model
• Logistic Regression.

References:

[1] Altman, E. I., "Financial Ratios, Discriminant Analysis and the
Predictionof Corporate Bankruptcy," Journal of Finance, vol.23, no.4,
1968, pp.589-609.
[2] Beaver, W. H., "Financial Ratios as Predictors of Failure," Journal of
Accounting Research, vol.4, 1966, pp.71-111.
[3] Cox, D.R. and E. J. Snell. Analysis of binary data (2nd edition). London:
Chapman & Hall, 1989.
[4] Deakin, E. B.. "A discriminant analysis of predictors of business
failure." Journal of Accounting Research, vol.10, no1, 1972, pp.167-
179.
[5] Koh, H. C., Tan, S. S., "A Neural network approach to the prediction of
going concern status," Accounting and Business Research, vol21, 1999,
pp.211-216.
[6] Lau, H. L., "A Five-State Financial Distress Prediction Model," Journal
of Accounting Research, vol.25, no.1, 1987, pp.127-138.
[7] Martin, D. "Early warning of banking failure." Journal of Banking and
Finance, 1977, pp.249-276.
[8] Nagelkerke, N. J. D.. "A note on a general definition of the coefficient
of determination." Biometrika, vol.78, no.3, 1991, pp.691-692. Covers
the two measures of R-square for logistic regression which are found in
SPSS output.
[9] Ohlson, J. A., "Financial Rations and the Probabilistic Prediction of
Bankruptcy," Journal of Accounting Research, vol.18, 1980, pp.109-
131.
[10] Odom, M. D., Sharda, R., "A Neural Network Model for Bankruptcy
Prediction," Proceedings of the IEEE International Conference on
Neural Networks, 1990, pp.163-168.
[11] Retzlaff-Roberts, D. L.. "Relating discriminant analysis and DEA to one
another." Computers and Operations Research, vol.23, no.4, 1996,
pp.311-322.
[12] Theodossiou, P.T., "Predicting Shifts in the mean of a Multivariate Time
Series Process: An Application in Predicting Business Failures," Journal
of American Statistical Association, 1993, pp.441-449.
[13] Zeitun, R., Tian, G., Keen, S., "Default Probability for the Jordanian
Companies: A Test of Cash Flow Theory," International Research
Journal of Finance and Economics, vol.8, 2007, pp.147-162.
[14] Zmijewski, M. E. "Methodological issues related to the estimation of
financial distress prediction models." Journal of Accounting Research,
1984, pp.59-86.