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在本研究中所定義的公司規模(1)： ln( 營業收入淨額 ) 在本研究中所定義的公司規模(2)： ln( 營業收入淨額+營業外收入 )
Abstract In the Moody’ s KMV model, the default point is defined as short-term liabilities plus one-half long-term liabilities. But the regionalism, national condition, business scale, financial structure and industrial type may not be the same in different countries. Therefore, it should be verified whether the generality of this definition of default point still exists, otherwise this will result in error of measuring default probability and risk. Hence, we would base on Moody’ s KMV model, and take use of threshold regression and quantile regression to modify the definition of default of point and compare with each other. In other words, we try to renew the definition of default point, and find out whether that it existed structural change in this model or not. Besides, we want to estimate whether the new definition of default point were better and more persuasive than the original Moody’ s KMV model under threshold regression and quantile regression. In the research, we take seventeen variables to test the points of threshold and quantile respectively in threshold regression model and quantile regression model. As far as threshold regression model is concerned, we explore that receivable turnover, current ratio, short-term liability/ scales (1)1, short-term liability/ scales (2), firm size(1), firm size(2), interest coverage ratio, financial leverage, short-term liability, debt ratio, all these ten variables exist threshold effect significantly to the default point of listed companies in Taiwan. However, taking the quantile regression as an example, there are only two variables, such are long-term liability and short-liability, significantly affect the assets value of company, but the other fifteen financial variables are insignificantly. Furthermore, by the modified definition of default point with threshold regression model and quantile regression model, we calculate the verified default probabilities. Finally, we employ ROC curve and CAP curve to examine the accuracy and the efficiency of predictability. We explore that if we considered receivable turnover, current ratio, short-term liability/ scales (1), short-term liability/ scales (2), firm size(1), firm size(2), interest coverage ratio, financial leverage, short-term liability under threshold regression model; and besides if we take account of 0.85 quantile2 under quantile regression model , we have better accuracy and the efficiency than original Moody’ s KMV model. Moreover, we also find the threshold regression model is superior to the quantile regression model. Keywords: KMV, default probability, default point, threshold regression model, quantile regression model
