Loss distributions in consumer credit risk : macroeconomic models for expected and unexpected loss

 

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dc.contributor.advisor Rajaratnam, Kanshukan en_ZA
dc.contributor.advisor Clark, Allan en_ZA
dc.contributor.author Malwandla, Musa en_ZA
dc.date.accessioned 2016-07-18T12:47:05Z
dc.date.available 2016-07-18T12:47:05Z
dc.date.issued 2016 en_ZA
dc.identifier.citation Malwandla, M. 2016. Loss distributions in consumer credit risk : macroeconomic models for expected and unexpected loss. University of Cape Town. en_ZA
dc.identifier.uri http://hdl.handle.net/11427/20414
dc.description.abstract This thesis focuses on modelling the distributions of loss in consumer credit arrangements, both at an individual level and at a portfolio level, and how these might be influenced by loan-specific factors and economic factors. The thesis primarily aims to examine how these factors can be incorporated into a credit risk model through logistic regression models and threshold regression models. Considering the fact that the specification of a credit risk model is influenced by its purpose, the thesis considers the IFRS 7 and IFRS 9 accounting requirements for impairment disclosure as well as Basel II regulatory prescriptions for capital requirements. The thesis presents a critique of the unexpected loss calculation under Basel II by considering the different ways in which loans can correlate within a portfolio. Two distributions of portfolio losses are derived. The Vašíček distribution, which is the assumed in Basel II requirements, was originally derived for corporate loans and was never adapted for application in consumer credit. This makes it difficult to interpret and validate the correlation parameters prescribed under Basel II. The thesis re-derives the Vašíček distribution under a threshold regression model that is specific to consumer credit risk, thus providing a way to estimate the model parameters from observed experience. The thesis also discusses how, if the probability of default is modelled through logistic regression, the portfolio loss distribution can be modelled as a log-log-normal distribution. en_ZA
dc.language.iso eng en_ZA
dc.subject.other Mathematical Statistics en_ZA
dc.title Loss distributions in consumer credit risk : macroeconomic models for expected and unexpected loss en_ZA
dc.type Master Thesis
uct.type.publication Research en_ZA
uct.type.resource Thesis en_ZA
dc.publisher.institution University of Cape Town
dc.publisher.faculty Faculty of Science en_ZA
dc.publisher.department Department of Statistical Sciences en_ZA
dc.type.qualificationlevel Masters
dc.type.qualificationname MCom en_ZA
uct.type.filetype Text
uct.type.filetype Image
dc.identifier.apacitation Malwandla, M. (2016). <i>Loss distributions in consumer credit risk : macroeconomic models for expected and unexpected loss</i>. (Thesis). University of Cape Town ,Faculty of Science ,Department of Statistical Sciences. Retrieved from http://hdl.handle.net/11427/20414 en_ZA
dc.identifier.chicagocitation Malwandla, Musa. <i>"Loss distributions in consumer credit risk : macroeconomic models for expected and unexpected loss."</i> Thesis., University of Cape Town ,Faculty of Science ,Department of Statistical Sciences, 2016. http://hdl.handle.net/11427/20414 en_ZA
dc.identifier.vancouvercitation Malwandla M. Loss distributions in consumer credit risk : macroeconomic models for expected and unexpected loss. [Thesis]. University of Cape Town ,Faculty of Science ,Department of Statistical Sciences, 2016 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/20414 en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Malwandla, Musa AB - This thesis focuses on modelling the distributions of loss in consumer credit arrangements, both at an individual level and at a portfolio level, and how these might be influenced by loan-specific factors and economic factors. The thesis primarily aims to examine how these factors can be incorporated into a credit risk model through logistic regression models and threshold regression models. Considering the fact that the specification of a credit risk model is influenced by its purpose, the thesis considers the IFRS 7 and IFRS 9 accounting requirements for impairment disclosure as well as Basel II regulatory prescriptions for capital requirements. The thesis presents a critique of the unexpected loss calculation under Basel II by considering the different ways in which loans can correlate within a portfolio. Two distributions of portfolio losses are derived. The Vašíček distribution, which is the assumed in Basel II requirements, was originally derived for corporate loans and was never adapted for application in consumer credit. This makes it difficult to interpret and validate the correlation parameters prescribed under Basel II. The thesis re-derives the Vašíček distribution under a threshold regression model that is specific to consumer credit risk, thus providing a way to estimate the model parameters from observed experience. The thesis also discusses how, if the probability of default is modelled through logistic regression, the portfolio loss distribution can be modelled as a log-log-normal distribution. DA - 2016 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2016 T1 - Loss distributions in consumer credit risk : macroeconomic models for expected and unexpected loss TI - Loss distributions in consumer credit risk : macroeconomic models for expected and unexpected loss UR - http://hdl.handle.net/11427/20414 ER - en_ZA


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