Browsing by Author "Pitt, Lucian"

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    An assessment and comparison of bankruptcy prediction models in forecasting the financial distress of JSE-listed companies over a twenty-year period (2000 to 2020)
    (2023) Hendricks, Leon; Pitt, Lucian
    This study aimed to test the reliability of various models in predicting the failure of JSE-listed companies. Spanning a period of twenty years between the years 2000 and 2020, a sample of 156 companies was considered, with variables extending across financial information, non- financial information, as well as macroeconomic indicators. The timespan considered for the assessment is particularly significant considering that it encompasses two periods of catastrophic negative market downturns. This includes the 2008 financial crisis and the impacts of the Covid-19 pandemic in 2020. Furthermore, the introduction of new international accounting standards in the latter part of this period, implemented to address issues of risk and transparency in financial reporting, had a marked impact on accounting ratios. Accounting ratios have traditionally been used as inputs in distress prediction models. Considering this context, a study of the comparative performance of various models was undertaken, with the model set including multiple discriminant analysis, logit, probit, recursive partitioning and non-financial models. What was particularly noteworthy in this research was the inclusion of models developed by South African researchers in the model set. In respect of the multiple discriminant analysis, logit and probit models, the results demonstrated a predictive accuracy rate below those surfaced in previous studies, with accuracy rates averaging between 55% and 70%. These models were cumbered predominantly by Type I errors. The application of a model which included both financial and non-financial variables demonstrated more favourable results at an accuracy rate of 73%. The recursive partitioning model, however, which comprehended a high ratio of cashflow- related variables, yielded the highest accuracy, at 83%. The model, with its cash focus and its unique approach of considering the cumulative impact of variables instead of basing the predictive outcomes on the performance of a single financial year, tended not to fall prey to the error-types prevalent in the other models in the model set. The output of this research affirmed the importance of the traditional and rudimentary marker between distressed and non-distressed firms. That is, the abundance of cash or the lack thereof is the key differentiating mark between failure and success. The research also highlighted the importance of considering the cumulative impact of variables when forecasting the failure or success of companies, instead of basing predictive outcomes on the performance of a single period. Furthermore, this research confirmed what had been established in previous studies. That is, the size of the firm is a significant predictor of bankruptcy. This study also attempted to reassess the outcome of distress prediction models, by adjusting for the impact of changes in accounting. The impact on the predictive accuracy of the models by normalising for accounting changes, however, was inconclusive. This was mainly due to the extent of Type I errors across the multiple discriminant analysis, logit and probit models, in conjunction with the low prevalence of failed companies towards the latter part of the period considered in this research when changes in accounting standards were introduced. Further research is required in this area to understand the impact of accounting changes on traditional distress prediction models and potentially to revise these distress models, in order to yield higher predictive accuracies.
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    The relationship between VAICTM, company performance and market value of companies on the Johannesburg Securities Exchange
    (2022) Dullabh, Hitesh; Pitt, Lucian
    Purpose - The purpose of this paper was to examine the impact of Intellectual Capital (IC), using the VAICTM approach, against certain company performance indicators as well as market value on listed companies in South Africa. Design/Methodology/Approach - The study used secondary data of 50 listed companies from the Johannesburg Securities Exchange (JSE) over a period of five years (2016-2020), obtained from the IRESS Expert Database, as a basis for its analysis of the relationship between VAICTM (IC), company performance and market value. IC and its components are calculated using Pulic's (2000) VAICTM approach. Company performance is measured by Return on Assets (ROA) and Asset Turnover (ATO). Market value is measured by the Tobin's Q calculated as market to book ratio (TQ). The two-way Fixed Effects regression model is applied to statistically test the relationship between IC and company performance indicators , as well as the relationship between IC and market value. Findings - The results indicate that VAICTM and capital employed efficiency (CEE), are positively and significantly associated with market value of listed companies in South Africa. The relationship between the remaining components of VAICTM, Human Capital Efficiency (HCE) and Structural Capital Efficiency (SCE), and company performance and market value was not found to be statistically significant. Practical Implications - Within the South African context, physical and financial capital (represented by CEE) plays a dominant role in how market participants value the company, whilst HCE and SCE seem to have less of an influence on the market's perception of value. The recognition value by market participant, albeit confined to just one of the components of VAICTM, may be indicative of the market pre-empting such value in company performance going forward. These findings provide insight into the role that investment in IC can play in supporting company performance and market value of the company. v Originality/Value - This study provides a more recent analysis of the original work performed by Firer & Williams (2003) and Firer & Stainbank (2003). It also provides insight into progression and recognition of IC in the South African Market. Finally, this study contributes to the still limited body of academic literature on the relationship between the company's IC, its performance and its market value. The significance of this contribution is its focus on companies in an emerging market and the focus on South African companies in particular, given the dearth of such studies with this particular focus.