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A comparative examination of bankruptcy prediction: Altman MDA study versus Luther ANN study. A test of predictive strength between the two techniques.

机译:破产预测的比较研究:Altman MDA研究与Luther ANN研究。两种技术之间的预测强度测试。

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摘要

As early as 16th century BC, business inability to pay their debt has been a factor that was considered as notable concerns. As a result, the bankruptcy laws that were enacted in 1800 in the United States were in response to business inability to pay debt and these laws set the threshold point for what was considered to be reasonable factors when a business is said to be bankrupt.; The painful economic depression with business failures that the country had undergone prompted many scholars to begin to develop tools that could be used to provide warning signal for businesses that were susceptible to failures. Many studies begin with financial ratios as the empirical study conducted by Euclid in the 300 BC did. His study like the ones that followed aimed at providing business the ability to predict the likelihood of failure before they occur.; In the 1930's, Paul J. Fitzpatrick conducted a sample analysis of industrial enterprises in 16 lines of business that failed during the period of 1920 to 1929. In his study, he tested several financial ratios in order to determine if they could be important tools to predict companies' failure.; Several other researches that followed did determine that, in addition to financial ratios, other factors must be weighed even though they might not be quantitative but they could provide clues to business failures. In 1967 and 1968, the works of Beaver and Altman set the stage that led to the opening of a floodgate of literature and the development of several statistical methodologies to help predict with accuracy when firms (companies) were susceptible to bankruptcy ex-ante.; Although these studies revealed that ratios alone could not predict ex-ante but they remained grounded in every study as predictor variables. The emergence of these researches gave businesses the ability which they did not have before, to predict failures. Edward I. Altman's development of a single Z score for predicting companies that were susceptible to bankruptcy to those that were not ex-ante was the pioneer study that used multivariate techniques.; Therein, many other studies have emerged using other statistical techniques in order to confirm that other statistical techniques were more robust and had more predictive strength when predicting business failures.; This study examined multiple discriminant (MDA) technique in Altman Z score theoretical study versus the technique known as artificial neural network (ANN) as studied by Luther in 1998 to determine whether or not there is a difference in the strength of prediction of bankruptcy and robustness using ANN model versus MDA.; A sample of 100 companies was drawn from the Compustat database from 1985 to 1995 with the set up of two hypotheses at an alpha of .05 or 95 percent confidence level. The set of financial ratios that was categorized in five groups in previous two studies mentioned earlier was extended to eight groups and these groups were used as the predictor variables. They were tested and trained under both neuro network and multiple discriminant models.; The results confirmed that the strength of prediction of bankruptcy and the robustness of ANN model did not differ from multiple discriminant analysis (MDA) technique, thus prompting this study to accept both null hypotheses.
机译:早在公元前16世纪,企业无力偿还债务一直是人们关注的重要因素。结果,美国于1800年颁布的破产法是针对企业无力偿还债务而制定的,这些法律为认为企业破产的合理因素设定了门槛。该国经历了企业倒闭带来的痛苦的经济萧条,促使许多学者开始开发可用于向容易倒闭的企业提供预警信号的工具。许多研究都是从财务比率开始的,就像欧几里德在公元前300年进行的实证研究一样。他的研究类似于随后的研究,旨在为企业提供预测故障发生之前的可能性的能力。在1930年代,保罗·菲茨帕特里克(Paul J. Fitzpatrick)对16个行业的工业企业进行了抽样分析,这些企业在1920年至1929年期间倒闭。预测公司的失败。随后进行的其他几项研究确实确定,除了财务比率外,还必须权衡其他因素,即使这些因素可能不是量化的,但它们可以为企业倒闭提供线索。在1967年和1968年,Beaver和Altman的工作创造了一个舞台,导致文学闸门的开启和几种统计方法的发展,以帮助准确地预测公司(公司)在事前遭受破产的可能性。尽管这些研究表明,比率本身无法预测事前,但在每项研究中,比率仍然作为预测变量。这些研究的出现使企业能够预测以前失败的能力。爱德华·奥特曼(Edward I. Altman)通过单一Z评分来预测那些容易破产的公司,而不是那些事先未破产的公司,这是使用多元技术的先驱研究。其中,使用其他统计技术进行了许多其他研究,以确认在预测业务失败时其他统计技术更健壮并具有更强的预测能力。这项研究考察了Altman Z评分理论研究中的多判别(MDA)技术与路德(Luther)在1998年研究的称为人工神经网络(ANN)的技术,以确定破产和稳健性预测的强度是否存在差异使用ANN模型与MDA。 1985年至1995年间,从Compustat数据库中抽取了100家公司的样本,并建立了两个假设,其阿尔法系数为.05或置信度为95%。在前面提到的前两项研究中分为五个组的财务比率集合扩展到了八个组,这些组被用作预测变量。他们在神经网络和多种判别模型下进行了测试和训练。结果证实破产预测的强度和ANN模型的鲁棒性与多重判别分析(MDA)技术没有区别,从而促使本研究接受这两个零假设。

著录项

  • 作者

    Thevnin, Charles.;

  • 作者单位

    Nova Southeastern University.;

  • 授予单位 Nova Southeastern University.;
  • 学科 Economics Finance.; Statistics.
  • 学位 D.B.A.
  • 年度 2003
  • 页码 142 p.
  • 总页数 142
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 财政、金融;统计学;
  • 关键词

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