Identification of Loss-Given-Default (LGD) Effective Factors by Using Tobit Regression Model (Case Study: Bank of Industry and Mine Corporate Clients)
This research aims to identify the influential components on LGD by using Tobit regression on institutional customers of the bank of Industry and Mine. In order to achieve this goal, LGD can be used to calculate the probability of default on the basis of the Basel II agreement. LGD is the amount of...
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| Format: | Article |
| Language: | fas |
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Iran Banking Institute
2017-11-01
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| Series: | مطالعات مالی و بانکداری اسلامی |
| Subjects: | |
| Online Access: | http://jifb.ibi.ac.ir/article_54856_cb5713f21ce396da307fd29df94dc855.pdf |
| _version_ | 1818043423303663616 |
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| author | Mohsen Khoshtinat Seyedeh Nasim Alavi |
| author_facet | Mohsen Khoshtinat Seyedeh Nasim Alavi |
| author_sort | Mohsen Khoshtinat |
| collection | DOAJ |
| description | This research aims to identify the influential components on LGD by using Tobit regression on institutional customers of the bank of Industry and Mine. In order to achieve this goal, LGD can be used to calculate the probability of default on the basis of the Basel II agreement. LGD is the amount of loss a bank faces when the borrowers default on loan repayment. To accomplish this goal, 204 of institutional customers of bank for an 8 years period (2007-2014) have been chosen as a sample. The results show a significant relation between loan amount, collaterals (excepted promissory notes), industry type and LGD, and no significant relation between loan maturities and LGD. |
| first_indexed | 2024-12-10T09:01:58Z |
| format | Article |
| id | doaj.art-5f45360f69d64ec1b6d125cad05c95f0 |
| institution | Directory Open Access Journal |
| issn | 2588-3569 2588-4433 |
| language | fas |
| last_indexed | 2024-12-10T09:01:58Z |
| publishDate | 2017-11-01 |
| publisher | Iran Banking Institute |
| record_format | Article |
| series | مطالعات مالی و بانکداری اسلامی |
| spelling | doaj.art-5f45360f69d64ec1b6d125cad05c95f02022-12-22T01:55:16ZfasIran Banking Instituteمطالعات مالی و بانکداری اسلامی2588-35692588-44332017-11-013بهار و تابستان12954856Identification of Loss-Given-Default (LGD) Effective Factors by Using Tobit Regression Model (Case Study: Bank of Industry and Mine Corporate Clients)Mohsen Khoshtinat0Seyedeh Nasim Alavi1Faculty Member, College of Management and Finance, Khatam UniversityM. A. in Financial ManagementThis research aims to identify the influential components on LGD by using Tobit regression on institutional customers of the bank of Industry and Mine. In order to achieve this goal, LGD can be used to calculate the probability of default on the basis of the Basel II agreement. LGD is the amount of loss a bank faces when the borrowers default on loan repayment. To accomplish this goal, 204 of institutional customers of bank for an 8 years period (2007-2014) have been chosen as a sample. The results show a significant relation between loan amount, collaterals (excepted promissory notes), industry type and LGD, and no significant relation between loan maturities and LGD.http://jifb.ibi.ac.ir/article_54856_cb5713f21ce396da307fd29df94dc855.pdfBasel II AgreementDefaultfacilitiesLoss-Given-Default (LGD)Tobit Regression |
| spellingShingle | Mohsen Khoshtinat Seyedeh Nasim Alavi Identification of Loss-Given-Default (LGD) Effective Factors by Using Tobit Regression Model (Case Study: Bank of Industry and Mine Corporate Clients) مطالعات مالی و بانکداری اسلامی Basel II Agreement Default facilities Loss-Given-Default (LGD) Tobit Regression |
| title | Identification of Loss-Given-Default (LGD) Effective Factors by Using Tobit Regression Model (Case Study: Bank of Industry and Mine Corporate Clients) |
| title_full | Identification of Loss-Given-Default (LGD) Effective Factors by Using Tobit Regression Model (Case Study: Bank of Industry and Mine Corporate Clients) |
| title_fullStr | Identification of Loss-Given-Default (LGD) Effective Factors by Using Tobit Regression Model (Case Study: Bank of Industry and Mine Corporate Clients) |
| title_full_unstemmed | Identification of Loss-Given-Default (LGD) Effective Factors by Using Tobit Regression Model (Case Study: Bank of Industry and Mine Corporate Clients) |
| title_short | Identification of Loss-Given-Default (LGD) Effective Factors by Using Tobit Regression Model (Case Study: Bank of Industry and Mine Corporate Clients) |
| title_sort | identification of loss given default lgd effective factors by using tobit regression model case study bank of industry and mine corporate clients |
| topic | Basel II Agreement Default facilities Loss-Given-Default (LGD) Tobit Regression |
| url | http://jifb.ibi.ac.ir/article_54856_cb5713f21ce396da307fd29df94dc855.pdf |
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