Predicting financial distress in Malaysian market: a logit analysis
<p>This study was carried out to apply logit analysis in the prediction of financial distress in Malaysia. Its focus is to appraise whether the factors of firm's performance, risks, age, size and industrial grouping sector can be a good forecast for financial distress in Malaysia....
Saved in:
| Main Author: | |
|---|---|
| Format: | thesis |
| Language: | eng |
| Published: |
2003
|
| Subjects: | |
| Online Access: | https://ir.upsi.edu.my/detailsg.php?det=9977 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| id |
oai:ir.upsi.edu.my:9977 |
|---|---|
| record_format |
uketd_dc |
| spelling |
oai:ir.upsi.edu.my:99772024-04-02 Predicting financial distress in Malaysian market: a logit analysis 2003 Rusliza Yahaya <p>This study was carried out to apply logit analysis in the prediction of financial distress in Malaysia. Its focus is to appraise whether the factors of firm's performance, risks, age, size and industrial grouping sector can be a good forecast for financial distress in Malaysia. In this study, financial distress is defined as companies placed under PN 4 sector on the Kuala Lumpur Stock Exchange (KLSE). There are 86 companies from the main board of KLSE designated as samples in this study. Amongst these, 43 companies are classified as PN4 and the other 43 companies are considered as 'healthy' ones. When the gathered data are analysed, only total debt ratio (TOR), earning per share (EPS) and construction sector proved to be significant in classifying the firms into the correct group (distressed vs 'healthy'), based on logit analysis. Among these three variables, TDR is the most influential one as it can predict financial distress cent up to three years prior to it. The model is accurate in classifying 75.73 per accurate of the total sample. The logit analysis also shows that, higher level of prediction is achieved when the data are analyzed separately according to years. We observe excellent and accurate classification based on data from the first two years and it can also correctly classify 92.59 per cent and 90.48 per cent for the first and second yearpreceding to financial distress respectively.</p> 2003 thesis https://ir.upsi.edu.my/detailsg.php?det=9977 https://ir.upsi.edu.my/detailsg.php?det=9977 text eng closedAccess Masters Universiti Pendidikan Sultan Idris Fakulti Pengurusan dan Ekonomi N/A |
| institution |
Universiti Pendidikan Sultan Idris |
| collection |
UPSI Digital Repository |
| language |
eng |
| topic |
|
| spellingShingle |
Rusliza Yahaya Predicting financial distress in Malaysian market: a logit analysis |
| description |
<p>This study was carried out to apply logit analysis in the prediction of financial distress in Malaysia. Its focus is to appraise whether the factors of firm's performance, risks, age, size and industrial grouping sector can be a good forecast for financial distress in Malaysia. In this study, financial distress is defined as companies placed under PN 4 sector on the Kuala Lumpur Stock Exchange (KLSE). There are 86 companies from the main board of KLSE designated as samples in this study. Amongst these, 43 companies are classified as PN4 and the other 43 companies are considered as 'healthy' ones. When the gathered data are analysed, only total debt ratio (TOR), earning per share (EPS) and construction sector proved to be significant in classifying the firms into the correct group (distressed vs 'healthy'), based on logit analysis. Among these three variables, TDR is the most influential one as it can predict financial distress cent up to three years prior to it. The model is accurate in classifying 75.73 per accurate of the total sample. The logit analysis also shows that, higher level of prediction is achieved when the data are analyzed separately according to years. We observe excellent and accurate classification based on data from the first two years and it can also correctly classify 92.59 per cent and 90.48 per cent for the first and second yearpreceding to financial distress respectively.</p> |
| format |
thesis |
| qualification_name |
|
| qualification_level |
Master's degree |
| author |
Rusliza Yahaya |
| author_facet |
Rusliza Yahaya |
| author_sort |
Rusliza Yahaya |
| title |
Predicting financial distress in Malaysian market: a logit analysis |
| title_short |
Predicting financial distress in Malaysian market: a logit analysis |
| title_full |
Predicting financial distress in Malaysian market: a logit analysis |
| title_fullStr |
Predicting financial distress in Malaysian market: a logit analysis |
| title_full_unstemmed |
Predicting financial distress in Malaysian market: a logit analysis |
| title_sort |
predicting financial distress in malaysian market: a logit analysis |
| granting_institution |
Universiti Pendidikan Sultan Idris |
| granting_department |
Fakulti Pengurusan dan Ekonomi |
| publishDate |
2003 |
| url |
https://ir.upsi.edu.my/detailsg.php?det=9977 |
| _version_ |
1804890531489120256 |