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 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 [Student Project] (Unpublished)

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Abstract

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.

Metadata

Item Type: Student Project
Creators:
Creators
Email
Shuhaimi, Ira Anissidma
UNSPECIFIED
Mohamed Tahir, Siti Nurhuzalifah
UNSPECIFIED
Safarim, Siti Suhaila
UNSPECIFIED
Subjects: Q Science > QA Mathematics > Mathematical statistics. Probabilities
Q Science > QA Mathematics > Analysis > Analytical methods used in the solution of physical problems
Divisions: Universiti Teknologi MARA, Negeri Sembilan > Seremban Campus > Faculty of Computer and Mathematical Sciences
Programme: Bachelor of Science (Hons.) Mathematics
Item ID: 37422
Uncontrolled Keywords: comparison, KMV-MERTON, KMV-EDF, predicting default risk, companies
URI: https://ir.uitm.edu.my/id/eprint/37422

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