Bankruptcy Model Construction and its Limitation in Input Data Quality

Dana Kubíčková, Vladimír Nulíček
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引用次数: 1

Abstract

The aim of the research project solved at the University of Finance and administration is to construct a new bankruptcy model. The intention is to use data of the firms that have to cease their activities due to bankruptcy. The most common method for bankruptcy model construction is multivariate discriminant analyses (MDA). It allows to derive the indicators most sensitive to the future companies’ failure as a parts of the bankruptcy model. One of the assumptions for using the MDA method and reassuring the reliable results is the normal distribution and independence of the input data. The results of verification of this assumption as the third stage of the project are presented in this article. We have revealed that this assumption is met only in a few selected indicators. Better results were achieved in the indicators in the set of prosperous companies and one year prior the failure. The selected indicators intended for the bankruptcy model construction thus cannot be considered as suitable for using the MDA method.
破产模型的构建及其对输入数据质量的限制
财管学院的研究课题旨在构建一种新的破产模式。其目的是利用因破产而不得不停止经营的企业的数据。最常用的破产模型构建方法是多元判别分析(MDA)。作为破产模型的一部分,它可以推导出对未来公司破产最敏感的指标。使用MDA方法并保证结果可靠的一个假设是输入数据的正态分布和独立性。本文给出了作为项目第三阶段的这一假设的验证结果。我们已经表明,只有少数选定的指标符合这一假设。成功企业和失败企业前一年的各项指标都取得了较好的成绩。因此,所选择的用于破产模型构建的指标不能被认为适合使用MDA方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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