A modified KMV-Merton model for predicting the levels of credit risk among Malaysian public listed companies / Norliza Muhamad Yusof
Measuring credit risk is always a primary matter, mainly in the institution of banking. Several efforts have been adopted by banks to ensure the security of their loans. Accordingly, three objectives are introduced in this study as an effort to complement banks’ current credit risk management tools....
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| Format: | Thesis |
| Language: | English |
| Published: |
2013
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| Online Access: | http://ir.uitm.edu.my/id/eprint/16395/ http://ir.uitm.edu.my/id/eprint/16395/1/TM_NORLIZA%20MUHAMAD%20YUSOF%20CS%2013_5.pdf |
| Summary: | Measuring credit risk is always a primary matter, mainly in the institution of banking. Several efforts have been adopted by banks to ensure the security of their loans. Accordingly, three objectives are introduced in this study as an effort to complement banks’ current credit risk management tools. The first objective is to modify the KMV-Merton model according to the assumptions and condition of companies’ extreme cases made in this study. The second objective is to adapt the modified KMV-Merton model to the cases of estimating the probability of default of Malaysian companies, and the results of the adaptation are validated through credit ratings and EBIT interest coverage ratios. It appears that the probability of default estimated by the modified KMV-Merton model is able to react significantly and coincides with the given credit ratings and EBIT interest coverage ratios in a way of measuring the credit risk of Malaysian companies. This study also focuses on the probability of default estimated by the modified KMV-Merton model for the PN17 Companies. The analysis shows that the modified KMV-Merton model is able to predict future default of the companies up to three years in advance. These conclude that the modified KMV-Merton model is a convincing default forecaster model for Malaysian companies. Consequently, a framework which is called the Loan Credit Risk Indicator (LCRI) is developed as the last objective of this study. The LCRI is developed to assist banks in the loan decision-making and the repayment process. |
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