The Research of The Probability of Credit Risk of Corporations- Using Mutilevel Logistic Regression

• Main Authors: Meng-hung Kao, 高夢鴻
• Other Authors: Fur-hsing Wen
• Format: Others
• Language: zh-TW
• Published: 2008
• Online Access: http://ndltd.ncl.edu.tw/handle/35m6be

碩士 === 東吳大學 === 國際經營與貿易學系 === 96 === In the top down process ofrisk analysis, the first is to consider the national economic environment. The second is to assess the industry condition which the corporation belongs to. Finally, it is to analyze the company. During the process, the industrial analysis plays an important role. Hence, the industry factors are unneglectable ones. If we can consider the relativ condition of the corporations which belong to the same industry, it should be valuable to predict the companies’ posibility of default. Therefore, we use Hierarchical Linear Modeling (is abbreviated as HLM) to include the industrial factor on credit analysis condition to firms’characteristics. This research surveys all listed companies of 32 industries in Taiwan. The sample period is 2006. We use industry score to measure the industry factors. The company default is deferred as the net value are lower than the face value. Moreover, following Chung, Huang, Huang, and Hsieh(2006), we collect the firms’variables they adopted. The empirical results show that debt to equity ratio, acid-test ratio, and ROA can influence the probability of company bankruptcy. That means that the higher debt to equity ratio is, or the lower the acid-test ratio, and ROA are,the higher the probability of company bankruptcy is. But the effect of industry score is not significant. This may result from the composition of industry score is lack of valid index that might indicate the true industry factors.