Self-sovereign identity defines a system in which an entity can generate and maintain their own proof of identity. There are several solutions aimed at providing this service and storing the relevant information on a blockchain. We describe how to develop such a system using Ethereum’s smart contract platform and a browser-based application, and we demonstrate its use in a corporate that sells more than one funeral insurance product. Individuals and organizations should be able to create claims on their identities, however, only reputable organizations can verify these claims. These operations are executed by functions contained in the smart contracts and the transactions can be stored on a blockchain. A major benefit of this innovation is that an identity can be easily re-used and we show how an insurance department can do this using credentials already requested by another department. This method allows for much needed efficiency over the current system.

Includes bibliographical references (leaves 82-88). / This thesis will examine the administration of executive compensation in listed companies in South Africa in order to understand the background to the topical emotion expressed by the public about the quantum of executive earnings. The Thesis attempts to explain how approaches are made to these vast payments. It commences with the history of the management of executive compensation. Before the 1990s, disclosure of directors' emoluments was limited to one amount. Companies suffered losses due to the Agency Theory where executives dominated boards. With the introduction of remuneration committees and corporate governance, control was moved to a committee of the board of -non-executive directors (a remuneration committee). The purpose of this research was to ascertain whether such a committee is effective. Interviews were held with leading executives and an analyst. An electronic survey was dispatched to the chief executive officers and chief financial officers of a large selection of listed companies. The results of the research are summarised and conclusions expressed on all such views with the addition of limited input of the author's views. The question requires an examination of the effectiveness of remuneration committees. Some suggestions are also made as to future research and actions which may be conducted. This thesis shows that remuneration committees are not as effective as they should be and will explain why this is so.

Includes bibliographical references. / Within the private equity spectrum of investment stages, venture capital and early stage investments are heralded as critical where it has been shown that an increase in private equity early-stage investments of 0.1% of GDP is associated with an increase in real economic growth of 0.96% (Meyer, 2010). This dissertation suggests that within the South African private equity industry fund managers are preoccupied with competing for later stage investments. The study also proposes that the early stage private equity spectrum is severely under-represented in South Africa. Even though there is a healthy distribution between investors as well as the stage of investment they prefer within venture capital, the study suggests that the lack of total funds committed to early stage investments could be a limiting factor for job creation and economic growth.

Includes bibliographical references. / This study has a number of interrelated objectives that seek to understand and contextualize the Altman bankruptcy prediction model in the setting of the South African medical schemes over a ten year period (2002 to 2011). The main objective of this study is to validate the Altman Z₂ model amongst the medical schemes in South Africa; in terms of accurately classifying Z₂-scores of ≤ 1.23 and ≥ 2.9 into the a priori groups of failed and non-failed schemes. The average classification rates in the period 2002 to 2011 are as follows: 82% accuracy rate and 17.9% error rate. A linear trend line inserted in the graph shows the accuracy improving from 72% to 91% between the period 2003/2004 to 2011/2012. This outcome is consistent with the conclusion in previous studies (Aziz and Humayon, 2006: 27) that showed the accuracy rates in most failure prediction studies to be as follows: 84%, 88%, and 85% for statistical models, AEIS models and theoretical models respectively. Although this study validated the Altman model, further studies are required to test the rest of the study objectives under conditions where some of the assumptions are revised.

The management of market risk is an essential determinant of the stability of a financial institution, and by extension, of the overall financial system. There are various variables which impact on the accuracy of a market risk management system. For various reasons which are discussed in this study, Value at Risk (VaR) is used as a measure of market risk. VaR has certain key features which make it adaptable to several types of scenarios in order to provide a measure of market risk. In order to assess these features of VaR, this study evaluates VaR using a range of techniques. This study analyses the performance of some of the most popular VaR models using the JSE ALSI's total daily returns. The VaR estimates were calculated for each model using varying parameters for confidence level, risk horizon, distributional assumptions and other variables. The study evaluates the relative accuracy of each model analysed, over specific subsets of the data set under consideration, and performs five different backtests to determine the accuracy of each model. The aim of this analysis is to identify the model most suited to predicting VaR in the South African environment. A key feature of this study is that it includes data during and after the financial crisis, and can, therefore, model the respective volatility characteristics of the data during this period. The results of the analysis indicate that the asymmetric GARCH models outperform the other models over both the full sample period and the crisis and post-crisis subperiods, and that the t distribution assumption produces more accurate forecasts. This implies that such models are better suited to capturing the effects of volatility for data with these characteristics.

A significant body of research exists in psychology pertaining to the various biases which influence human decision-making. A growing body of knowledge on the understanding of decision-making in an investment setting has been established over the last 30 or so years. The objective of this study is to understand the factors influencing investment decision-making, before and after an emotional intelligence intervention. This study places the focus on the most common cognitive psychological biases which may affect investment decisionmaking, by establishing these biases in behavioural finance under the theoretical literature review. The research is scoped in the form of a case study. Two survey questionnaires were deployed on a sample of investment professionals within the vicinity of the city of Cape Town. The questionnaires seek to establish whether participants exhibit common cognitive psychological biases by phrasing questions in both investment and non-investment scenarios. On completion of the first questionnaire, each participant read an informative article on the subject of emotional intelligence and the development thereof before proceeding to the second questionnaire. The objective of this article is to make participants aware of, and create an understanding of emotional intelligence and the development thereof. The results of both questionnaires were analysed to establish whether participants exhibit any change in their responses. The analysis confirmed varied results for the biases considered. Whilst participants appeared to exhibit higher prevalence of availability and anchoring bias post the emotional intelligence intervention, participants exhibited lower indications of herding, self-control & mental accounting bias post the emotional intelligence intervention. Participants appeared equally loss-averse in both questionnaires. Therefore, in summary, the results show that, at least to some extent, the participants exhibited the biases considered, and after the introduction of the construct of emotional intelligence and the development thereof, a change in most of the responses were noted. By design, the scope of this study and the sample size observed does not make it possible to extrapolate these results beyond the sample group. However, the results positively demonstrate a solid basis for future research on the measured impact of an emotional intelligence intervention on investment professionals and the role of emotional intelligence and consequent bearing thereof on investment decision-making.

This study investigates and concludes on thus the predictability of economic activity in South Africa through the use of share price indices and banking sector asset levels as leading indicators. This study investigates share price and banking sector information using both nominal and real quarterly and monthly time-series data for the period March 1998 to October 2017. For share prices analysis, it takes market segmentation on the JSE into account, and examines causality between the All-Share index, the Industrial index, the Resources index and the Financial index against GDP and the index of Industrial Production (IIP) using the test proposed by Granger (1969). For the banking sector development analysis, it takes the South African Reserve Bank’s disclosure of all banking institution assets and examines if changes in those asset levels Granger-cause the changes to GDP and IIP. This study builds on the work performed by previous studies, specifically on Sayed, Auret and Page (2017) and Har, Ee, and Tan (2009), which test the leading relationship of the stock market for economic activity. This study adopts a similar approach to these studies, while also making certain adjustments and additions to their methodology, aiming to produce more robust findings. This study not only tests for a new relationship between banking development and economic activity, but it also conducts several additional stationarity tests to provide more conclusive evidence of the data’s stationarity before Granger-causality testing is performed. The additional stationarity tests in this study establish that some time series data, which Sayed et al. (2017) concluded to be stationary, is in fact not stationary, and this contrary finding directly impacts the subsequent Granger-causality testing and results. This study also notes and corrects Sayed et al.'s(2017) methodology which fails to perform subsequent stationarity testing on its differenced time series data, and thus fails to prove that the transformed data is satisfactorily stationary and acceptable for Granger-causality testing. Another adjustment we make to the methodology is the interpretation of the Index for Industrial Production (IIP), which we view as a volume based index rather than a price based index that can be adjusted for inflation, which was the position of Sayed et al. (2017). The empirical investigation of this study reveals some positive evidence in favour of the JSE as a leading indicator of economic activity, where unidirectional causality is established between the four market segmentation proxies and the macroeconomic variables. This is however less conclusive than the findings of previous South African studies, which is explained. For the banking sector’s development analysis, the empirical tests produce inconsistent findings across monthly and quarterly data, leaving one unable to confirm a causal relationship existing between the banking sector’s development and economic activity.

Includes abstract. / Includes bibliographical references (leaves 114-116). / Although Fuzzy Logic is not new, it is however only since 2004 that an axiomatic theory has been created that has all the desirable effects of Fuzzy Logic. This theory, named Credibility theory was proposed by Dr. Liu. Within this thesis we aim to utilize credibility theory to model the psychological impacts of market participants on European options. Specifically this is done by modifying the approach that was originally taken by Black and Scholes. The Hew model, which is known as the fuzzy drift parameter model, begins by replacing the deterministic drift within Brownian motion with a fuzzy parameter. This fuzzy parameter models the psychological impacts of market participants. Naturally as we are dealing in Chance theory 1 the risk neutral dynamics change from that of Black and Scholes and thus so does the price of European call options.

Includes bibliographical references (leaves 110-111).

Includes bibliographical references (leaves 52-55). / As the title, "An Alternative Model for Multivariate Stable Distributions", depicts, this thesis draws from the methodology of [J36] and derives an alternative to the sub-Gaussian alpha-stable distribution as another model for multivariate stable data without using the spectral measure as a dependence structure. From our investigation, firstly, we echo that the assumption of "Gaussianity" must be rejected, as a model for, particularly, high frequency financial data based on evidence from the Johannesburg Stock Exchange (JSE). Secondly, the introduced technique adequately models bivariate return data far better than the Gaussian model. We argue that unlike the sub-Gaussian stable and the model involving a spectral measure this technique is not subject to estimation of a joint index of stability, as such it may remain a superior alternative in empirical stable distribution theory. Thirdly, we confirm that the Gaussian Value-at-Risk and Conditional Value-at-Risk measures are more optimistic and misleading while their stable counterparts are more informative and reasonable. Fourthly, our results confirm that stable distributions are more appropriate for portfolio optimization than the Gaussian framework.