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dc.contributor.authorMagarita, Sara Muya
dc.date.accessioned2017-11-14T10:13:10Z
dc.date.available2017-11-14T10:13:10Z
dc.date.issued2017
dc.identifier.urihttp://hdl.handle.net/11071/5573
dc.descriptionA Dissertation submitted in partial fulfillment of the requirements for the Master of Science in Mathematical Finance (MSc.MF) at Strathmore Universityen_US
dc.description.abstractConsidering 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.language.isoenen_US
dc.publisherStrathmore Universityen_US
dc.subjectCredit Risk Modelingen_US
dc.subjectIFRS9en_US
dc.subjectBackward Semi-Markov Modelsen_US
dc.titleModeling SME credit ratings using non-homogenous backward semi-Markovian approachen_US
dc.typeThesisen_US


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