Please use this identifier to cite or link to this item: https://scholarhub.balamand.edu.lb/handle/uob/3568
Title: Bankruptcy prediction models : discriminant analysis vs logistic regression
Authors: Kanaan, Hassan
Melki, Fahim
Advisors: Cherif, Husni
Subjects: Logistic regression analysis
Bankruptcy--Forecasting--Statistical methods
Discriminant analysis
Issue Date: 2011
Abstract: 
The research will be addressing a problem that has been the fear of any company, which is the risk of bankruptcy. The main idea of this paper is to see which kind of model will best suits bankruptcy prediction Discriminant or Logistic. This is an important problem because of the benefits that such a model can provide in assessing the bankruptcy risk of a company from the aspect of a stakeholder and shareholder. Despite the fact that many researchers have addressed this problem, but not many of them have considered seeing which kind of model is the best. This research provides an added value that the models will possess because of the availability of companies from different countries, such as the MENA region as well as Europe, China, and the United States. A set of 10 financial ratios for 200 publicly listed companies which are equally divided between bankrupt and non-bankrupt companies will be used to evaluate the models. These models are of three types, Logistic, Discriminant, and The Altman Model, were implemented and the results show that the Logistic model has proven to be superior to the others.
Description: 
Includes bibliographical references (p. 43-44).

Supervised by Dr. Husni Cherif.
URI: https://scholarhub.balamand.edu.lb/handle/uob/3568
Rights: This object is protected by copyright, and is made available here for research and educational purposes. Permission to reuse, publish, or reproduce the object beyond the personal and educational use exceptions must be obtained from the copyright holder
Ezproxy URL: Link to full text
Type: Project
Appears in Collections:UOB Theses and Projects

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