Redefinition of the KMV model's optimal default point based on genetic algorithms – Evidence from Taiwan
學年 100
學期 1
出版(發表)日期 2011-08-01
作品名稱 Redefinition of the KMV model's optimal default point based on genetic algorithms – Evidence from Taiwan
作品名稱(其他語言)
著者 Lee, Wo-Chiang
單位 淡江大學財務金融學系
出版者 Kidlington: Pergamon
著錄名稱、卷期、頁數 Expert Systems With Applications 38(8), pp.10107–10113
摘要 In this paper, we propose a new method based on genetic algorithms to solve the optimal default point of the KMV model. In our empirical study, we compare the GA-KMV model with the QR-KMV and KMV models. The results indicate that the percentage of correctness of the GA-KMV model is higher than those for the other two models. This is to say, the GA-KMV model has a better goodness of fit. We also obtain the optimal default point for a Taiwan listed company. This can help us to predict the default point and improve the bank’s risk management performance.
關鍵字 Credit risk; KMV; Default probability; Quantile regression; Genetic algorithms
語言 en
ISSN 0957-4174
期刊性質 國外
收錄於 SCI
產學合作
通訊作者 Lee, Wo-Chiang
審稿制度
國別 GBR
公開徵稿
出版型式 紙本
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/72297 )

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