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Redefinition of the KMV model’s optimal default point based on genetic algorithms – Evidence from Taiwan

Authors :
Lee, Wo-Chiang
Source :
Expert Systems with Applications. Aug2011, Vol. 38 Issue 8, p10107-10113. 7p.
Publication Year :
2011

Abstract

Abstract: 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. [Copyright &y& Elsevier]

Details

Language :
English
ISSN :
09574174
Volume :
38
Issue :
8
Database :
Academic Search Index
Journal :
Expert Systems with Applications
Publication Type :
Academic Journal
Accession number :
59773764
Full Text :
https://doi.org/10.1016/j.eswa.2011.02.084