Predicting Financial Failure of Yemeni Banks
From year to year, strong attention has been paid to the study of the problems of predicting and preventing bank bankruptcy. Bank failures are usually followed by unfavorable consequences on stakeholders outside the failed banks themselves. Sometimes the consequences are felt by non-banking system...
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| Main Author: | |
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| Format: | Thesis |
| Language: | eng eng |
| Published: |
2008
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| Subjects: | |
| Online Access: | https://etd.uum.edu.my/214/1/Maisarh_Yaseen_Omar.pdf https://etd.uum.edu.my/214/2/Maisarh_Yaseen_Omar.pdf |
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| Summary: | From year to year, strong attention has been paid to the study of the problems of predicting and preventing bank bankruptcy. Bank failures are usually followed by
unfavorable consequences on stakeholders outside the failed banks themselves. Sometimes the consequences are felt by non-banking system as a whole. A failure can
result in much harm to employment, earnings, financial development and other associated public interests.
Based on the logistic regression (LR) model, Earlier Warning System (EWS) is employed for Yemeni banks during 2002-2006 using micro-level data to identify a set of indicators that best explain the probability of an individual bank in Yemen to fail (become bankrupt) or remain sound across time. In the finding, capital adequacy, management quality and profitability found to be able to identify problem banks in Yemen. Bank's size has the opposite effect of failure probability. It is hoped that the financial ratios and result of the model will be useful to bankers and regulators in identifying problem banks in Yemen. |
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