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A multicriteria discrimination approach for the credit rating of Asian banks

机译:亚洲银行信用评级的多准则歧视方法

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In this paper we develop a multicriteria decision aid model, to investigate whether it is possible to replicate the credit ratings of Fitch on Asian banks using publicly available data. The model is developed with the Multi-group Hierarchical Discrimination (MHDIS) approach, following a tenfold cross validation procedure. Five financial variables are selected from a list of nineteen ones through factor analysis. An additional set of five non-financial variables covering ownership, corporate governance, auditing, strength of bank's franchise and its banking environment is also being used. The results show that equity/customer and short term funding, net interest margin and return on average equity are the most important financial variables. The number of shareholders, the number of subsidiaries and the banking environment of the country in which the banks operate are the most important non-financial ones. In terms of classification accuracies, the results show that the MHDIS model can replicate the credit ratings of Fitch with a satisfactory accuracy and is more efficient than discriminant analysis and ordered logistic regression that are used for comparison purposes.
机译:在本文中,我们开发了一种多准则决策辅助模型,以研究是否有可能使用公开数据复制惠誉在亚洲银行的信用评级。该模型是在遵循十倍交叉验证程序之后,使用多组层次区分(MHDIS)方法开发的。通过因素分析从19个变量中选择5个财务变量。还使用了另外五个非财务变量集,包括所有权,公司治理,审计,银行特许经营实力及其银行环境。结果表明,股本/客户和短期资金,净利率和平均股本收益率是最重要的财务变量。银行运营所在国家的股东数量,子公司数量和银行环境是最重要的非金融机构。在分类准确性方面,结果表明,MHDIS模型可以令人满意的精度复制Fitch的信用等级,并且比用于比较目的的判别分析和有序逻辑回归更有效。

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