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A comparison of KMV-MERTON and KMV-EDF model in predicting default risk of companies / Ira Anissidma Shuhaimi, Siti Nurhuzalifah Mohamed Tahir and Siti Suhaila Safarim

This research implemented the KMV-Merton model and KMV-EDF model to predict the default risk of AA and C rated companies which are UEM Sunrise Berhad and Talam Corporation Berhad respectively. By using this model, the distance to default and probability to default of the companies are predicted....

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Main Authors: Shuhaimi, Ira Anissidma, Mohamed Tahir, Siti Nurhuzalifah, Safarim, Siti Suhaila
Format: Student Project
Language:English
Published: 2019
Subjects:
Mathematical statistics. Probabilities
Analytical methods used in the solution of physical problems
Online Access:http://ir.uitm.edu.my/id/eprint/37422/1/37422.pdf
http://ir.uitm.edu.my/id/eprint/37422/
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spelling my.uitm.ir.374222020-11-23T13:19:48Z http://ir.uitm.edu.my/id/eprint/37422/ A comparison of KMV-MERTON and KMV-EDF model in predicting default risk of companies / Ira Anissidma Shuhaimi, Siti Nurhuzalifah Mohamed Tahir and Siti Suhaila Safarim Shuhaimi, Ira Anissidma Mohamed Tahir, Siti Nurhuzalifah Safarim, Siti Suhaila Mathematical statistics. Probabilities Analytical methods used in the solution of physical problems This research implemented the KMV-Merton model and KMV-EDF model to predict the default risk of AA and C rated companies which are UEM Sunrise Berhad and Talam Corporation Berhad respectively. By using this model, the distance to default and probability to default of the companies are predicted. The comparison and validation of the predicted default risk of the two companies is also done by the actual rating of companies. In this study, the credit risk of the company is often discussed as the risk of the default of the company. Default of the company is usually associated with the bankruptcy of the company. We are interested in the credit event or default event which is defined as a failure to accomplish a predetermined liabilities or to meet requirements detailed in the agreement. KMV-Merton and KMV-EDF model will calculated distance to default and probability to default of the companies. Based on calculating the distance to default, the result shows that UEM Sunrise Berhad is better than Talam Corporation Berhad in managing their company from being bankrupt. As for the credit rating companies, the default probability is evaluated to get the predicted credit rating companies. From both models, it can be conclude KMV-EDF model is way more better for company to use since it give the better result for the companies than KMV-Merton model. For the recommendation, other companies can use this model to predict the probability of default. Besides, to make the lower credit ratings, the companies have to know how to manage their debt by reducing the expenses. As conclusion, KMV-Merton and KMV-EDF models are able to predict probability of default and distance to default for AA and C rated companies. There are slightly difference in value for distance to default and probability of default for both models. This is because both models are using difference formula in calculating distance to default. 2019 Student Project NonPeerReviewed text en http://ir.uitm.edu.my/id/eprint/37422/1/37422.pdf Shuhaimi, Ira Anissidma and Mohamed Tahir, Siti Nurhuzalifah and Safarim, Siti Suhaila (2019) A comparison of KMV-MERTON and KMV-EDF model in predicting default risk of companies / Ira Anissidma Shuhaimi, Siti Nurhuzalifah Mohamed Tahir and Siti Suhaila Safarim. [Student Project] (Unpublished)
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic Mathematical statistics. Probabilities
Analytical methods used in the solution of physical problems
spellingShingle Mathematical statistics. Probabilities
Analytical methods used in the solution of physical problems
Shuhaimi, Ira Anissidma
Mohamed Tahir, Siti Nurhuzalifah
Safarim, Siti Suhaila
A comparison of KMV-MERTON and KMV-EDF model in predicting default risk of companies / Ira Anissidma Shuhaimi, Siti Nurhuzalifah Mohamed Tahir and Siti Suhaila Safarim
description This research implemented the KMV-Merton model and KMV-EDF model to predict the default risk of AA and C rated companies which are UEM Sunrise Berhad and Talam Corporation Berhad respectively. By using this model, the distance to default and probability to default of the companies are predicted. The comparison and validation of the predicted default risk of the two companies is also done by the actual rating of companies. In this study, the credit risk of the company is often discussed as the risk of the default of the company. Default of the company is usually associated with the bankruptcy of the company. We are interested in the credit event or default event which is defined as a failure to accomplish a predetermined liabilities or to meet requirements detailed in the agreement. KMV-Merton and KMV-EDF model will calculated distance to default and probability to default of the companies. Based on calculating the distance to default, the result shows that UEM Sunrise Berhad is better than Talam Corporation Berhad in managing their company from being bankrupt. As for the credit rating companies, the default probability is evaluated to get the predicted credit rating companies. From both models, it can be conclude KMV-EDF model is way more better for company to use since it give the better result for the companies than KMV-Merton model. For the recommendation, other companies can use this model to predict the probability of default. Besides, to make the lower credit ratings, the companies have to know how to manage their debt by reducing the expenses. As conclusion, KMV-Merton and KMV-EDF models are able to predict probability of default and distance to default for AA and C rated companies. There are slightly difference in value for distance to default and probability of default for both models. This is because both models are using difference formula in calculating distance to default.
format Student Project
author Shuhaimi, Ira Anissidma
Mohamed Tahir, Siti Nurhuzalifah
Safarim, Siti Suhaila
author_facet Shuhaimi, Ira Anissidma
Mohamed Tahir, Siti Nurhuzalifah
Safarim, Siti Suhaila
author_sort Shuhaimi, Ira Anissidma
title A comparison of KMV-MERTON and KMV-EDF model in predicting default risk of companies / Ira Anissidma Shuhaimi, Siti Nurhuzalifah Mohamed Tahir and Siti Suhaila Safarim
title_short A comparison of KMV-MERTON and KMV-EDF model in predicting default risk of companies / Ira Anissidma Shuhaimi, Siti Nurhuzalifah Mohamed Tahir and Siti Suhaila Safarim
title_full A comparison of KMV-MERTON and KMV-EDF model in predicting default risk of companies / Ira Anissidma Shuhaimi, Siti Nurhuzalifah Mohamed Tahir and Siti Suhaila Safarim
title_fullStr A comparison of KMV-MERTON and KMV-EDF model in predicting default risk of companies / Ira Anissidma Shuhaimi, Siti Nurhuzalifah Mohamed Tahir and Siti Suhaila Safarim
title_full_unstemmed A comparison of KMV-MERTON and KMV-EDF model in predicting default risk of companies / Ira Anissidma Shuhaimi, Siti Nurhuzalifah Mohamed Tahir and Siti Suhaila Safarim
title_sort comparison of kmv-merton and kmv-edf model in predicting default risk of companies / ira anissidma shuhaimi, siti nurhuzalifah mohamed tahir and siti suhaila safarim
publishDate 2019
url http://ir.uitm.edu.my/id/eprint/37422/1/37422.pdf
http://ir.uitm.edu.my/id/eprint/37422/
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score 13.211869

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