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首页> 外文期刊>Journal of the Operational Research Society >A new classifier based on the reference point method with application in bankruptcy prediction
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A new classifier based on the reference point method with application in bankruptcy prediction

机译：基于参考点法的新分类器及其在破产预测中的应用

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The finance industry relies heavily on the risk modelling and analysis toolbox to assess the risk profiles of entities such as individual and corporate borrowers and investment vehicles. Such toolbox includes a variety of parametric and nonparametric methods for predicting risk class belonging. In this paper, we expand such toolbox by proposing an integrated framework for implementing a full classification analysis based on a reference point method, namely in-sample classification and out-of-sample classification. The empirical performance of the proposed reference point method-based classifier is tested on a UK data-set of bankrupt and nonbankrupt firms. Our findings conclude that the proposed classifier can deliver a very high predictive performance, which makes it a real contender in industry applications in banking and investment. Three main features of the proposed classifier drive its outstanding performance, namely its nonparametric nature, the design of our RPM score-based cut-off point procedure for in-sample classification, and the choice of a k-nearest neighbour as an out-of-sample classifier which is trained on the in-sample classification provided by the reference point method-based classifier.
机译：金融业在很大程度上依赖于风险建模和分析工具箱来评估实体（例如个人和公司借款人以及投资工具）的风险状况。这样的工具箱包括各种用于预测风险类别归属的参数和非参数方法。在本文中，我们通过提出一个集成的框架来扩展这种工具箱，该框架用于基于参考点方法（样本内分类和样本外分类）实施完全分类分析。在英国破产和非破产公司的数据集上测试了基于参考点方法的分类器的经验性能。我们的发现得出结论，建议的分类器可以提供非常高的预测性能，这使其成为银行和投资行业应用中的真正竞争者。拟议的分类器的三个主要特点是其出色的性能，即其非参数性质，用于样本内分类的基于RPM分数的分界点程序的设计以及选择k最近邻作为非分类对象。 -样本分类器，该样本分类器是在基于参考点方法的分类器提供的样本中分类上进行训练的。

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