Detecting Financial Distress : Discriminant Versus Logistic Regression Analysis

This study examines two statistical tests which are discriminant analysis and the logit model to predict the probability of financially distress companies. In addition this study also utilizes the usage of financial ratios as a predictor of a company in a state of financial distressed. The findings...

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Main Author: Abd. Halim @ Hamilton, Ahmad
Format: Thesis
Language:en
en
Published: 2003
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Online Access:https://etd.uum.edu.my/943/1/ABD._HALIM_%40_HAMILTON_B._AHMADXX.pdf
https://etd.uum.edu.my/943/2/1.ABD._HALIM_%40_HAMILTON_B._AHMADXX.pdf
https://etd.uum.edu.my/943/
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author Abd. Halim @ Hamilton, Ahmad
author_facet Abd. Halim @ Hamilton, Ahmad
author_sort Abd. Halim @ Hamilton, Ahmad
building UUM Library
collection Institutional Repository
content_provider Universiti Utara Malaysia
content_source UUM Electronic Theses
continent Asia
country Malaysia
description This study examines two statistical tests which are discriminant analysis and the logit model to predict the probability of financially distress companies. In addition this study also utilizes the usage of financial ratios as a predictor of a company in a state of financial distressed. The findings show that the logit model shows better prediction accuracy than the discriminant analysis. The logit model correctly classified 91.5 percent of the companies in the estimation sample and 90 percent for the holdout sample. However for discriminant mode the overall accuracy rate fix the estimation and the holdout samples are 84.5 percent respectively. For discriminant analysis there are three factors found to have significant discriminating power current ratio net income to total assets and sales to current assets. Similarly logit model also identified three factors but two of the factors (shareholders' equity to total liabilities and cashflow from financing to total liabilities) are different from those found in discriminant analysis. The only factor which is identified in both models is net income to total assets. The findings give clear understanding of the relevant factors that can cause financial distress. Hence companies could take immediate actions to avoid failure to the company.
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spelling my.uum.etd-9432013-07-24T12:09:45Z https://etd.uum.edu.my/943/ Detecting Financial Distress : Discriminant Versus Logistic Regression Analysis Abd. Halim @ Hamilton, Ahmad HG Finance This study examines two statistical tests which are discriminant analysis and the logit model to predict the probability of financially distress companies. In addition this study also utilizes the usage of financial ratios as a predictor of a company in a state of financial distressed. The findings show that the logit model shows better prediction accuracy than the discriminant analysis. The logit model correctly classified 91.5 percent of the companies in the estimation sample and 90 percent for the holdout sample. However for discriminant mode the overall accuracy rate fix the estimation and the holdout samples are 84.5 percent respectively. For discriminant analysis there are three factors found to have significant discriminating power current ratio net income to total assets and sales to current assets. Similarly logit model also identified three factors but two of the factors (shareholders' equity to total liabilities and cashflow from financing to total liabilities) are different from those found in discriminant analysis. The only factor which is identified in both models is net income to total assets. The findings give clear understanding of the relevant factors that can cause financial distress. Hence companies could take immediate actions to avoid failure to the company. 2003-06-08 Thesis NonPeerReviewed application/pdf en https://etd.uum.edu.my/943/1/ABD._HALIM_%40_HAMILTON_B._AHMADXX.pdf application/pdf en https://etd.uum.edu.my/943/2/1.ABD._HALIM_%40_HAMILTON_B._AHMADXX.pdf Abd. Halim @ Hamilton, Ahmad (2003) Detecting Financial Distress : Discriminant Versus Logistic Regression Analysis. Masters thesis, Universiti Utara Malaysia.
spellingShingle HG Finance
Abd. Halim @ Hamilton, Ahmad
Detecting Financial Distress : Discriminant Versus Logistic Regression Analysis
title Detecting Financial Distress : Discriminant Versus Logistic Regression Analysis
title_full Detecting Financial Distress : Discriminant Versus Logistic Regression Analysis
title_fullStr Detecting Financial Distress : Discriminant Versus Logistic Regression Analysis
title_full_unstemmed Detecting Financial Distress : Discriminant Versus Logistic Regression Analysis
title_short Detecting Financial Distress : Discriminant Versus Logistic Regression Analysis
title_sort detecting financial distress : discriminant versus logistic regression analysis
topic HG Finance
url https://etd.uum.edu.my/943/1/ABD._HALIM_%40_HAMILTON_B._AHMADXX.pdf
https://etd.uum.edu.my/943/2/1.ABD._HALIM_%40_HAMILTON_B._AHMADXX.pdf
https://etd.uum.edu.my/943/
url_provider http://etd.uum.edu.my/