A Study for Moody’s KMV Model with Calibration of Default Point Based on Genetic Algorithms

• Main Authors: Wu,Hung-Hsuan, 吳虹萱
• Other Authors: Lin,Wen-Shiu
• Format: Others
• Language: zh-TW
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/72836523943685546714

碩士 === 輔仁大學 === 資訊管理學系 === 99 === There are many empirical studies testing weather the original definition of Moody's KMV's default point is appropriate. Financial Supervisory Commission, Executive Yuan announced January 1, 2013 will be officially adopted International Financial Accounting Standards (IFRS) and in 2010 the Basel Committee (BSBC) proposed new Basel Capital Accord (Basel III), which both prove the importance of the implied credit risk of the OBF. Based on the above statement of motivation, this study was to redefine the Moody's KMV's default point, and the added genetic algorithms (Genetic Algorithms) used to find the optimal solution on the coefficient of contignent liability, and to identify the best Cut-value of each model as a decision-making rules in order to compare their predictive ability. As the results show that the modified GA KMV model is the best performance of three models. This result not only enhances the bank for early detection of companies that may face default risk, but also ensures that the implementation of debt recovery could be done successfully and precisely. For investors, the information can help them avoid the suspectedcompany with financial crisis and to improve higher attention to the importance of information included in OBF.