Partial least squares based financial distressed classifying model of small construction firms / Amirah Hazwani Abdul Rahim ... [et al.]

The study on the classification of firms' financial distress was made popular by Altman (1968) . Up until today , banks use Altman's ratio to rate credit credibility of potential borrowers . Since then many works replicate , improvise or use different statistical and non-statistical method...

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Main Authors: Abdul Rahim, Amirah Hazwani, Mohd Nasir, Ida Normaya, Nayan, Asmahani
格式: Research Reports
語言:English
出版: 2014
主題:
在線閱讀:https://ir.uitm.edu.my/id/eprint/35056/1/35056.pdf
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author Abdul Rahim, Amirah Hazwani
Mohd Nasir, Ida Normaya
Nayan, Asmahani
author_facet Abdul Rahim, Amirah Hazwani
Mohd Nasir, Ida Normaya
Nayan, Asmahani
author_sort Abdul Rahim, Amirah Hazwani
collection UITM
description The study on the classification of firms' financial distress was made popular by Altman (1968) . Up until today , banks use Altman's ratio to rate credit credibility of potential borrowers . Since then many works replicate , improvise or use different statistical and non-statistical methods to improve the classification rate of financial distress. Most of these works dealt with information gathered from large companies as information on small companies are limited and not easily available. The aim of this research is to fill in the gap and extends the work done in Abd Razak and Wan Asma' (2012) by looking at the predictive ability of information gathered from Malaysian small firms .
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spelling oai:ir.uitm.edu.my:350562021-12-01T03:57:13Z https://ir.uitm.edu.my/id/eprint/35056/ Partial least squares based financial distressed classifying model of small construction firms / Amirah Hazwani Abdul Rahim ... [et al.] Abdul Rahim, Amirah Hazwani Mohd Nasir, Ida Normaya Nayan, Asmahani Credit. Debt. Loans Financial management. Business finance. Corporation finance The study on the classification of firms' financial distress was made popular by Altman (1968) . Up until today , banks use Altman's ratio to rate credit credibility of potential borrowers . Since then many works replicate , improvise or use different statistical and non-statistical methods to improve the classification rate of financial distress. Most of these works dealt with information gathered from large companies as information on small companies are limited and not easily available. The aim of this research is to fill in the gap and extends the work done in Abd Razak and Wan Asma' (2012) by looking at the predictive ability of information gathered from Malaysian small firms . 2014-11 Research Reports NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/35056/1/35056.pdf Partial least squares based financial distressed classifying model of small construction firms / Amirah Hazwani Abdul Rahim ... [et al.]. (2014) [Research Reports] (Unpublished)
spellingShingle Credit. Debt. Loans
Financial management. Business finance. Corporation finance
Abdul Rahim, Amirah Hazwani
Mohd Nasir, Ida Normaya
Nayan, Asmahani
Partial least squares based financial distressed classifying model of small construction firms / Amirah Hazwani Abdul Rahim ... [et al.]
title Partial least squares based financial distressed classifying model of small construction firms / Amirah Hazwani Abdul Rahim ... [et al.]
title_full Partial least squares based financial distressed classifying model of small construction firms / Amirah Hazwani Abdul Rahim ... [et al.]
title_fullStr Partial least squares based financial distressed classifying model of small construction firms / Amirah Hazwani Abdul Rahim ... [et al.]
title_full_unstemmed Partial least squares based financial distressed classifying model of small construction firms / Amirah Hazwani Abdul Rahim ... [et al.]
title_short Partial least squares based financial distressed classifying model of small construction firms / Amirah Hazwani Abdul Rahim ... [et al.]
title_sort partial least squares based financial distressed classifying model of small construction firms amirah hazwani abdul rahim et al
topic Credit. Debt. Loans
Financial management. Business finance. Corporation finance
url https://ir.uitm.edu.my/id/eprint/35056/1/35056.pdf
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