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dc.contributor.advisor | Marks, Jonathan | |
dc.contributor.postgraduate | Le Roux, Marrelie | |
dc.date.accessioned | 2014-09-11T06:58:28Z | |
dc.date.available | 2014-09-11T06:58:28Z | |
dc.date.created | 2014-04-30 | |
dc.date.issued | 2013 | en_US |
dc.description | Dissertation (MBA)--University of Pretoria, 2013. | en_US |
dc.description.abstract | To date there has been significant research on the topic of financial distress prediction, due to its relevance to various stakeholders. Beaver (1966), Altman (1968) and Ohlson (1980) are generally regarded as the pioneers in this field of study, despite heavy criticism their models are widely accepted and used. Studies by Grice & Ingram (2001); Grice & Dugan (2001) and Sudarsanam & Taffler (1995) have shown that these models require to be updated regularly with new variables and coefficients due to various factors. This study proposes to add to the body of knowledge by developing a distress prediction model using a classic statistical method and financial ratios, calculated on published company data of organisations listed on the Johannesburg Stock Exchange. | en_US |
dc.description.availability | Unrestricted | en_US |
dc.description.degree | MBA | |
dc.description.department | Gordon Institute of Business Science (GIBS) | en |
dc.description.librarian | zkgibs2014 | en_US |
dc.identifier.citation | Le Roux, M 2013, A classic statistical model developed towards predicting financial distress, MBA Mini Dissertation, University of Pretoria, Pretoria, viewed yymmdd <http://hdl.handle.net/2263/41983> | en_US |
dc.identifier.uri | http://hdl.handle.net/2263/41983 | |
dc.language.iso | en | en_US |
dc.publisher | University of Pretoria | en_ZA |
dc.rights | © 2014 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. | en_US |
dc.subject | UCTD | |
dc.subject | Process control—Statistical methods | en_US |
dc.title | A classic statistical model developed towards predicting financial distress | en_US |
dc.type | Mini Dissertation | en_US |