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Financial distress prediction: Comparisons of logit models using receiver operating characteristic (ROC) curve analysis

机译:财务困境预测:使用接收器工作特征(ROC)曲线分析的Logit模型比较

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The prediction of future financial condition of corporations has attracted the attention of financial researchers, and finding the alerting indexes of occurrence of financial distress has turned to be one of the most attractive and significant fields of financial and economic researches. Studying the history of researches shows that many of the researchers have focused on the financial ratios of the corporations to predict the financial distress. This article studies the logit models for one and two years before the occurrence of financial distress (T-1 and T-2) by making use of financial ratios and also by utilizing the analysis of receiver operating characteristic (ROC) curve. The analysis of ROC curve, among the models employed to compare the effectiveness of different statistical models, is often used in the fields of psychology and bio-medics in order to summarize the discriminatory of a diagnostic test and also to compare the performance of different models for binary outcomes. Regarding the accuracy of classification and prediction, the results of this research indicate that T-1 logit model is better than T-2 logit model. However, by considering the measurements done by ROC curve, it could be claimed that T-2 logit model operates more efficiently than T-1 logit model in the classification of distressed corporations.
机译:对公司未来财务状况的预测引起了金融研究者的关注,发现发生财务危机的预警指标已成为财务和经济研究中最有吸引力,最重要的领域之一。对研究历史的研究表明,许多研究人员已将重点放在公司的财务比率上,以预测财务困境。本文通过使用财务比率以及通过对接收器工作特性(ROC)曲线的分析研究了发生财务困境(T-1和T-2)之前的一年和两年的对数模型。在用来比较不同统计模型有效性的模型中,ROC曲线分析经常用于心理学和生物医学领域,以总结诊断测试的歧视性并比较不同模型的性能对于二进制结果。关于分类和预测的准确性,研究结果表明,T-1 logit模型优于T-2 logit模型。但是,考虑到用ROC曲线进行的测量,可以认为在陷入困境的公司的分类中,T-2 logit模型比T-1 logit模型更有效地运行。

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