A corporate failure prediction model for non-financial South African corporates incorporating best practices used by the credit industry

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dc.contributor.advisorCorreia, Carlosen_ZA
dc.contributor.authorRowlings, Douglasen_ZA
dc.date.accessioned2016-07-18T12:55:43Z
dc.date.available2016-07-18T12:55:43Z
dc.date.issued2016en_ZA
dc.description.abstractIn the context of the current macroeconomic environment there is an expectation of an increase in South African non-financial corporate failure, where advance prediction thereof will become even more important. A number of South African non-financial corporate failures have occurred following the financial crisis. In addition, South Africa experienced a watershed moment with the first default on a non-financial corporate bond in 2013. At the same time, with the adoption of the International Financial Reporting Standards (IFRS) framework there have been significant advances in the quality of financial information which should improve its usage in predicting corporate failure. This study used the latest sample to date of listed South African non-financial corporates that met the definition of failure but limited the universe of financial information to that which was prepared under IFRS. At the same time, adjustments were made to the financial data based upon pre-selection of independent credit statistic variables most commonly used in ranking relative credit risk for non-financial corporates. Additionally, equity market price data was introduced into the model to add a forward-looking information consideration. This resulted in an eleven variable model where differentiation of corporate failure was facilitated through the use of multiple discriminant analysis.en_ZA
dc.identifier.apacitationRowlings, D. (2016). <i>A corporate failure prediction model for non-financial South African corporates incorporating best practices used by the credit industry</i>. (Thesis). University of Cape Town ,Faculty of Commerce ,Department of Finance and Tax. Retrieved from http://hdl.handle.net/11427/20439en_ZA
dc.identifier.chicagocitationRowlings, Douglas. <i>"A corporate failure prediction model for non-financial South African corporates incorporating best practices used by the credit industry."</i> Thesis., University of Cape Town ,Faculty of Commerce ,Department of Finance and Tax, 2016. http://hdl.handle.net/11427/20439en_ZA
dc.identifier.citationRowlings, D. 2016. A corporate failure prediction model for non-financial South African corporates incorporating best practices used by the credit industry. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Rowlings, Douglas AB - In the context of the current macroeconomic environment there is an expectation of an increase in South African non-financial corporate failure, where advance prediction thereof will become even more important. A number of South African non-financial corporate failures have occurred following the financial crisis. In addition, South Africa experienced a watershed moment with the first default on a non-financial corporate bond in 2013. At the same time, with the adoption of the International Financial Reporting Standards (IFRS) framework there have been significant advances in the quality of financial information which should improve its usage in predicting corporate failure. This study used the latest sample to date of listed South African non-financial corporates that met the definition of failure but limited the universe of financial information to that which was prepared under IFRS. At the same time, adjustments were made to the financial data based upon pre-selection of independent credit statistic variables most commonly used in ranking relative credit risk for non-financial corporates. Additionally, equity market price data was introduced into the model to add a forward-looking information consideration. This resulted in an eleven variable model where differentiation of corporate failure was facilitated through the use of multiple discriminant analysis. DA - 2016 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2016 T1 - A corporate failure prediction model for non-financial South African corporates incorporating best practices used by the credit industry TI - A corporate failure prediction model for non-financial South African corporates incorporating best practices used by the credit industry UR - http://hdl.handle.net/11427/20439 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/20439
dc.identifier.vancouvercitationRowlings D. A corporate failure prediction model for non-financial South African corporates incorporating best practices used by the credit industry. [Thesis]. University of Cape Town ,Faculty of Commerce ,Department of Finance and Tax, 2016 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/20439en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentDepartment of Finance and Taxen_ZA
dc.publisher.facultyFaculty of Commerceen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherFinance and Taxen_ZA
dc.titleA corporate failure prediction model for non-financial South African corporates incorporating best practices used by the credit industryen_ZA
dc.typeMaster Thesis
dc.type.qualificationlevelMasters
dc.type.qualificationnameMComen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
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