A classic statistical model developed towards predicting financial distress

dc.contributor.advisorMarks, Jonathan
dc.contributor.emailichelp@gibs.co.zaen_US
dc.contributor.postgraduateLe Roux, Marrelie
dc.date.accessioned2014-09-11T06:58:28Z
dc.date.available2014-09-11T06:58:28Z
dc.date.created2014-04-30
dc.date.issued2013en_US
dc.descriptionDissertation (MBA)--University of Pretoria, 2013.en_US
dc.description.abstractTo 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.availabilityUnrestricteden_US
dc.description.degreeMBA
dc.description.departmentGordon Institute of Business Science (GIBS)en
dc.description.librarianzkgibs2014en_US
dc.identifier.citationLe 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.urihttp://hdl.handle.net/2263/41983
dc.language.isoenen_US
dc.publisherUniversity of Pretoriaen_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.subjectUCTD
dc.subjectProcess control—Statistical methodsen_US
dc.titleA classic statistical model developed towards predicting financial distressen_US
dc.typeMini Dissertationen_US

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