Analysing the stability of bankruptcy prediction models
The aim of this study is to assess the predictive power of logit model and hazard model in predicting bankruptcy and to analyse the stability of the models. Using Malaysian listed companies and a sample span from 1998 to 2014, this study found that, for the hazard model, all variables were significa...
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my.uum.repo.281992021-02-18T02:19:43Z http://repo.uum.edu.my/28199/ Analysing the stability of bankruptcy prediction models Md Rus, Rohani Taufil Mohd, Kamarun Nisham Abdul Latif, Rohaida HJ Public Finance The aim of this study is to assess the predictive power of logit model and hazard model in predicting bankruptcy and to analyse the stability of the models. Using Malaysian listed companies and a sample span from 1998 to 2014, this study found that, for the hazard model, all variables were significant while for the logit model only five variables were significant. The results also show that the logistic and hazard models both had predictive accuracies of more than 90%. However, the hazard model had a predictive accuracy of 99.4% while logit model had a predictive accuracy of 91.8%. The hazard model was more stable than logit model as the predictive accuracy of the hazard only changed a little when a smaller sample was chosen. Lastly, the study showed that, even though both models were good in predicting distress, the hazard model is better than logit model. Inderscience Publishers 2020 Article PeerReviewed Md Rus, Rohani and Taufil Mohd, Kamarun Nisham and Abdul Latif, Rohaida (2020) Analysing the stability of bankruptcy prediction models. Afro-Asian J. of Finance and Accounting, 10 (4). ISSN 1751-6447 http://doi.org/10.1504/AAJFA.2020.110493 doi:10.1504/AAJFA.2020.110493 |
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HJ Public Finance Md Rus, Rohani Taufil Mohd, Kamarun Nisham Abdul Latif, Rohaida Analysing the stability of bankruptcy prediction models |
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The aim of this study is to assess the predictive power of logit model and hazard model in predicting bankruptcy and to analyse the stability of the models. Using Malaysian listed companies and a sample span from 1998 to 2014, this study found that, for the hazard model, all variables were significant while for the logit model only five variables were significant. The results also show that the logistic and hazard models both had predictive accuracies of more than 90%. However, the hazard model had a predictive accuracy of 99.4% while logit model had a predictive accuracy of 91.8%. The hazard model was more stable than logit model as the predictive accuracy of the hazard only changed a little when a smaller sample was chosen. Lastly, the study showed that, even though both models were good in predicting distress, the hazard model is better than logit model. |
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Article |
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Md Rus, Rohani Taufil Mohd, Kamarun Nisham Abdul Latif, Rohaida |
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Md Rus, Rohani Taufil Mohd, Kamarun Nisham Abdul Latif, Rohaida |
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Md Rus, Rohani |
title |
Analysing the stability of bankruptcy prediction models |
title_short |
Analysing the stability of bankruptcy prediction models |
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Analysing the stability of bankruptcy prediction models |
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Analysing the stability of bankruptcy prediction models |
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Analysing the stability of bankruptcy prediction models |
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analysing the stability of bankruptcy prediction models |
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Inderscience Publishers |
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2020 |
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http://repo.uum.edu.my/28199/ http://doi.org/10.1504/AAJFA.2020.110493 |
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