Modeling SME credit ratings using non-homogenous backward semi-Markovian approach
dc.contributor.author | Magarita, Sara Muya | |
dc.date.accessioned | 2017-11-14T10:13:10Z | |
dc.date.available | 2017-11-14T10:13:10Z | |
dc.date.issued | 2017 | |
dc.description | A Dissertation submitted in partial fulfillment of the requirements for the Master of Science in Mathematical Finance (MSc.MF) at Strathmore University | en_US |
dc.description.abstract | Considering the growth in SME lending in Kenya and the obvious risks it posses to the banking sector, we establish a credit risk model that is responsive to the jumps in the economy. This is based on simulation of implied values of credit worthiness over a period of 12 months for 1000 SMEs, in which case we establish a case for the discrete time non-homogeneous semi-Markov approach as a proxy for internal rating model for a portfolio of SME loans. While viewing credit risk as a reliability issue, the model provides a credit indicator which gives a prospective measure of credit risk for an SME portfolio. Banks seeking to comply with the new IFRS9 guidelines can espouse this model to adequately measure impairment of financial instruments. | en_US |
dc.identifier.uri | http://hdl.handle.net/11071/5573 | |
dc.language.iso | en | en_US |
dc.publisher | Strathmore University | en_US |
dc.subject | Credit Risk Modeling | en_US |
dc.subject | IFRS9 | en_US |
dc.subject | Backward Semi-Markov Models | en_US |
dc.title | Modeling SME credit ratings using non-homogenous backward semi-Markovian approach | en_US |
dc.type | Thesis | en_US |
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