Abstract
The classification of firms into two dichotomous groups, which are bankrupt and non-bankrupt firms, provided results which showed equality between the two groups, where on the other hand, nonbankrupt firms can be further differentiated between financially distressed firms and healthy firms, of which either can be making a comeback in terms of profits or go bankrupt. The variable that differentiates between bankrupt and non-bankrupt as well as between financially distressed and healthy firms are different. As such, this study’s objective is to construct a logit bankruptcy model for all variable forms of firms that were involved in the sales and maintenance of motor vehicles. The sample for the study consists of UK based public firms that had submitted a full account to the Companies House. The data was then analysed through logit regression to predict the bankruptcy, using three different models. Based on the three models analysed, it was found that all three models recorded a significant value of below 0.05, which showed that the three models were able to predict bankruptcy. From the three models selected for analysis, the third model was found to be better compared to the other two models and was selected to be the base for the logit bankruptcy model for
all types of firms in this study.
Metadata
Item Type: | Conference or Workshop Item (Paper) |
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Creators: | Creators Email / ID Num. Nayan, Asmahani asmahanin@uitm.edu.my Abd Rahim, Amirah Hazwani amirah017@uitm.edu.my Ishak, Siti Shuhada shuhada58@gmail.com Ilias, Mohd Rijal mrijal@uitm.edu.my Ahmad, Abd Razak ara@uitm.edu.my |
Subjects: | H Social Sciences > HG Finance H Social Sciences > HG Finance > Financial engineering |
Divisions: | Universiti Teknologi MARA, Kedah > Sg Petani Campus |
Event Title: | e-Proceedings of the 5th International Conference on Computing, Mathematics and Statistics (iCMS 2021) |
Event Dates: | 4-5 August 2021 |
Page Range: | pp. 264-270 |
Keywords: | Logit regression, bankruptcy, distressed firms, public firms |
Date: | 2021 |
URI: | https://ir.uitm.edu.my/id/eprint/56211 |