Credit Risk Modelling and Early Warning System: An Empirical Study of Listed SMEs in UK
Since subprime crisis started in 2007, credit risk has drawn great public attention. Considering the fundamental role played by small and medium sized enterprises (SMEs) in the economy of many countries, it has become increasing important for financial institutions to control risk of credit exposure...
| Main Author: | |
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| Format: | Dissertation (University of Nottingham only) |
| Language: | English |
| Published: |
2010
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| Online Access: | https://eprints.nottingham.ac.uk/23958/ |
| _version_ | 1848792668901998592 |
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| author | SUN, YU |
| author_facet | SUN, YU |
| author_sort | SUN, YU |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Since subprime crisis started in 2007, credit risk has drawn great public attention. Considering the fundamental role played by small and medium sized enterprises (SMEs) in the economy of many countries, it has become increasing important for financial institutions to control risk of credit exposure of the loans to SMEs. In this dissertation, it is going to adopt KMV model to predict financial health of UK listed SMEs. By comparing distance-to-default of 176 companies from FTSE SmallCap Index and FTSE Fledgling Index to 68 companies from FTSE 100, we find that the credit risk of listed SME in UK is relatively high and tends to increase during the chosen period from the year 2007 to 2009. Through statistic tests, it is found that the accuracy of KMV model on UK market is excellent. In addition, this dissertation concludes that the asset size has significant impact on credit risk in UK. Finally, we suggest two credit warning lines for both financial institutions and government to monitor the credit situation of listed SMEs. |
| first_indexed | 2025-11-14T18:48:04Z |
| format | Dissertation (University of Nottingham only) |
| id | nottingham-23958 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T18:48:04Z |
| publishDate | 2010 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-239582018-01-30T22:59:27Z https://eprints.nottingham.ac.uk/23958/ Credit Risk Modelling and Early Warning System: An Empirical Study of Listed SMEs in UK SUN, YU Since subprime crisis started in 2007, credit risk has drawn great public attention. Considering the fundamental role played by small and medium sized enterprises (SMEs) in the economy of many countries, it has become increasing important for financial institutions to control risk of credit exposure of the loans to SMEs. In this dissertation, it is going to adopt KMV model to predict financial health of UK listed SMEs. By comparing distance-to-default of 176 companies from FTSE SmallCap Index and FTSE Fledgling Index to 68 companies from FTSE 100, we find that the credit risk of listed SME in UK is relatively high and tends to increase during the chosen period from the year 2007 to 2009. Through statistic tests, it is found that the accuracy of KMV model on UK market is excellent. In addition, this dissertation concludes that the asset size has significant impact on credit risk in UK. Finally, we suggest two credit warning lines for both financial institutions and government to monitor the credit situation of listed SMEs. 2010-09-23 Dissertation (University of Nottingham only) NonPeerReviewed application/pdf en https://eprints.nottingham.ac.uk/23958/1/Final_YuSun.pdf SUN, YU (2010) Credit Risk Modelling and Early Warning System: An Empirical Study of Listed SMEs in UK. [Dissertation (University of Nottingham only)] (Unpublished) |
| spellingShingle | SUN, YU Credit Risk Modelling and Early Warning System: An Empirical Study of Listed SMEs in UK |
| title | Credit Risk Modelling and Early Warning System: An Empirical Study of Listed SMEs in UK |
| title_full | Credit Risk Modelling and Early Warning System: An Empirical Study of Listed SMEs in UK |
| title_fullStr | Credit Risk Modelling and Early Warning System: An Empirical Study of Listed SMEs in UK |
| title_full_unstemmed | Credit Risk Modelling and Early Warning System: An Empirical Study of Listed SMEs in UK |
| title_short | Credit Risk Modelling and Early Warning System: An Empirical Study of Listed SMEs in UK |
| title_sort | credit risk modelling and early warning system: an empirical study of listed smes in uk |
| url | https://eprints.nottingham.ac.uk/23958/ |