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標題: 農業行庫授信風險評估模式之研究
A Study on Credit Risk Rating Models of Agricultural Banks
作者: 龐欽元
Pang, Chin-Yuan
關鍵字: Agricultural Banks;上市公司;Credit Risk;Finance Ratio;Listed Companies;Full Delivery;Credit Crisis;Factor Analysis;Multiple Discriminate Analysis;Probit Regression Analysis;Logit Regression Analysis;因素分析;多變量區別分析;Probit迴歸分析;Logit迴歸分析;農業行庫;全額交割;信用危機;財務比率;授信風險
出版社: 農業經濟學系

Because of the internationalization and Liberalization of the nation''s financial system, new banks have been established one by one, and the financial products have been changed very fast. The competition in loan making among banks has become harder. Then the banking cannot use leverage as ever, and both the revenues of interest and the profits are declining. Most banks start increasing the loan business, they may neglect the quality of loan. When the debtors are involved with recession, they may face cash insolvency and cash inadequacy. Therefore the environment of bank operation becomes more uncertain and risky. Agricultural banks (The Farmers Bank of China, Taiwan Land Bank and Taiwan Cooperative Bank) are the professional banks of agriculture. They play an important role in adjusting agricultural finance and providing credit related to agriculture. As result, banks urgently need a concrete and definite credit risk evaluation model as a criterion before loan making.
The data of this study was derived from 102 sample stock companies listed in Taiwan stock exchange corporation, which the agricultural banks made loans to them. We used those companies with full delivery or were previously removed from the list as the criterion of credit crisis and then chose 34 credit crisis samples for data collection. On the other hand, we separately found 68 normal samples with the similar scales in the same industry by means of pair-making method. And all these 102 samples were divided into two groups: the first subsameple of 69 companies was used as the original set; the second subsameple consisted of 33 companies was used as the predictive set. The balance sheet, income statement, schedule of changes in stockholders'' equity and cash flow statement were traced back to 4 years before failure to compute the 20 annual financial ratios. The financial status of failure and non-failure companies were first compared and contrasted. The factor analysis was then applied to extract the most significant ratios in predicting the business failures. Based on the common ratios extracted annually, multiple discriminant analysis model, probit regression model and logistic regression model were developed by using the data of three years for each model prior to the credit failure. We can compare the differences and the predicted performances of these models.
The empirical results led to the following conclusions:
(1) The significant financial ratios were not identical in
three years. 5 to 6 factors were extracted from 20 ratios
through factor analysis, the variance of significant ratios
were found to be 71.052%, 84.358% and 80.564% respectively.
(2) As the study showed, the explanatory ability and
discriminanting ability in this study were significant.
The correct rates of the classification and the prediction
of multiple discriminate analysis model in three years were
separately 65.22%, 65.22% and 60.87%; 63.64%, 60.87% and
63.64%. Probit regression model were 76.81%, 73.91% and
75.36%; 75.76%, 66.67% and 75.76%. Logistic regression
model were 78.26%, 73.91% and 75.36%; 75.76%, 66.67% and
(3) The results of this research revealed that the logistic
regression model performed better on both the correct
classification and the prediction than the other two models.
Appears in Collections:應用經濟學系

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