淡江大學機構典藏:Item 987654321/72297
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    题名: Redefinition of the KMV model's optimal default point based on genetic algorithms – Evidence from Taiwan
    作者: Lee, Wo-Chiang
    贡献者: 淡江大學財務金融學系
    关键词: Credit risk;KMV;Default probability;Quantile regression;Genetic algorithms
    日期: 2011-08
    上传时间: 2011-10-24 10:20:30 (UTC+8)
    出版者: Kidlington: Pergamon
    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.
    關聯: Expert Systems With Applications 38(8), pp.10107–10113
    DOI: 10.1016/j.eswa.2011.02.084
    显示于类别:[財務金融學系暨研究所] 期刊論文

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