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A predictive model of the states of financial health in South African businesses

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dc.contributor.advisor Du Toit, G. S. (Gawie S.) en
dc.contributor.author Naidoo, Surendra Ramoorthee en
dc.date.accessioned 2009-08-25T10:52:39Z
dc.date.available 2009-08-25T10:52:39Z
dc.date.issued 2009-08-25T10:52:39Z
dc.date.submitted 2006-11 en
dc.identifier.citation Naidoo, Surendra Ramoorthee (2009) A predictive model of the states of financial health in South African businesses, University of South Africa, Pretoria, <http://hdl.handle.net/10500/1405> en
dc.identifier.uri http://hdl.handle.net/10500/1405
dc.description.abstract The prediction of a company's financial health is of critical importance to a variety of stakeholders ranging from auditors, creditors, customers, employees, financial institutions and investors through to management. There has been considerable research in this field, ranging from the univariate dichotomous approach of Beaver (1966) to the multivariate multi-state approaches of Lau (1987) and Ward (1994). All of the South African studies namely, Strebel and Andrews (1977), Daya (1977), De La Rey (1981), Clarke et al (1991) and Court et al (1999), and even, Lukhwareni's (2005) four separate models, were dichotomous in nature providing either a "Healthy" or a "Failed" state; or a "Winner" or "Loser" as in the latter case. Notwithstanding, all of these models would be classified as first stage, initial screening models. This study has focused on following a two stage approach to identifying (first stage) and analysing (second stage) the States of Health in a company. It has not adopted the rigid "Healthy" or "Failed" dichotomous methodology. For the first stage, three-state models were developed classifying a company as Healthy, Intermittent or Distressed. Both three year and five year Profit after Tax (PAT) averages for Real Earnings Growth (REG) calculations were used to determine the superior definition for the Intermittent state; with the latter coming out as superior. Models were developed for the current year (Yn), one (Yn-1), two (Yn-2) and three years (Yn-3) forward using a Test sample of twenty companies and their predictive accuracy determined by using a Holdout sample of twenty-two companies and all their data points or years of information. The statistical methods employed were a Naïve model using the simple Shareholder Value Added (SVA) ratio, CHAID and MDA, with the latter providing very disappointing results - for the Yn year (five year average), the Test sample results were 100%, 95% and 95%, respectively; with the Holdout sample results being 81.3%, 83.8% and 52.5%, respectively. The Yn-1 to Yn-3 models produced very good results for the Test sample but somewhat disappointing Holdout sample results. The best two Yn models namely, the Naïve and the CHAID models, were modified so as to enable a comparison with the notable, dichotomous De La Rey (1981) model. As such, three different approaches were adopted and in all cases, both the modified Naïve (100%, 81.3%, 100%) and the modified CHAID (100%, 85.9%, 98%) produced superior results to the De La Rey model (84.8%, 62.6%, 75.3%). For the second stage, a Financial Risk Analysis Model (FRAM) using ratios in the categories of Growth, Performance Analysis, Investment Analysis and Financial Status were used to provide underlying information or clues, independent of the first stage model, so as to enable the stakeholder to establish a more meaningful picture of the company. This would pave the way for the appropriate strategy and course of action to be followed, to take the company to the next level; whether it be taking the company out of a Distressed State (D) or further improving on its Healthy status (H). en
dc.language.iso en en
dc.subject CHAID en
dc.subject Dichotomous
dc.subject Distressed
dc.subject Healthy
dc.subject Holdout sample
dc.subject Intermediate
dc.subject Multiple discriminant analysis
dc.subject Multivariate
dc.subject ordinal logistic regression
dc.subject Paired sample
dc.subject Severely distressed
dc.subject State of health
dc.subject.ddc 332.750968
dc.subject.lcsh Business enterprises -- South Africa -- Finance
dc.subject.lcsh Corporations -- South Africa -- Finance
dc.subject.lcsh Business failures -- South Africa -- Forecasting -- Mathematical models
dc.subject.lcsh Bankruptcy -- South Africa -- Forecasting -- Mathematical models
dc.title A predictive model of the states of financial health in South African businesses en
dc.type Thesis en
dc.description.department Business Management en
dc.description.degree D. BL. en


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