This paper aims to investigate the change in corporate debt levels in South Africa from 1994 to 2016 as well as analyse certain factors that play a role in the decision making of corporates when it comes to the all important decision of capital structure. The study uses data from large capitalisation, retail and food producing firms listed on the Johannesburg Stock Exchange. Four different leverage measures are used to determine the change in capital structure over the period under review as well as six of the most common determinants of capital structure used in literature. The analysis shows that South African corporates have drastically increased their appetite for debt funding compared to equity funding over the last two decades. Large capitalisation stocks reflected the largest increase in the use of debt, whilst food producers showed the smallest yet still significant increase in debt. Analysis has also shown that firms have changed their maturity profile of their debt significantly since the 2008 financial crises. Results from the analysis on determinants varied with some determinants showing statistical significance.

Using a Principal Component Analysis (PCA) approach, we investigate the sovereign yield spread term structure of the BRICS economies against the U.S. We show that the term structure for these markets are primarily driven by three latent factors which can be classified as the spread level, slope and curvature factors. We further postulate that a country’s yield curve contains valuable information about its future economic state and as such the PCA derived spread factors, which are based on the differences between sovereign yield curves, encapsulates material macro-economic information between the countries. In light of this, we show that augmenting the traditional Uncovered Interest Rate Parity model (UIRP) with these factors improves the models predictive accuracy of exchange rate movements.

Includes bibliographical references (leaves 255-266). / The research objective of this study was to construct an empirical model for the prediction of corporate failure in South Africa through the application of machine learning techniques using information generally available to investors. The study began with a thorough review of the corporate failure literature, breaking the process of prediction model construction into the following steps: * Defining corporate failure * Sample selection * Feature selection * Data pre-processing * Feature Subset Selection * Classifier construction * Model evaluation These steps were applied to the construction of a model, using a sample of failed companies that were listed on the JSE Securities Exchange between 1 January 1996 and 30 June 2003. A paired sample of non-failed companies was selected. Pairing was performed on the basis of year of failure, industry and asset size (total assets per the company financial statements excluding intangible assets). A minimum of two years and a maximum of three years of financial data were collated for each company. Such data was mainly sourced from BFA McGregor RAID Station, although the BFA McGregor Handbook and JSE Handbook were also consulted for certain data items. A total of 75 financial and non-financial ratios were calculated for each year of data collected for every company in the final sample. Two databases of ratios were created - one for all companies with at least two years of data and another for those companies with three years of data. Missing and undefined data items were rectified before all the ratios were normalised. The set of normalised values was then imported into MatLab Version 6 and input into a Population-Based Incremental Learning (PBIL) algorithm. PBIL was then used to identify those subsets of features that best separated the failed and non-failed data clusters for a one, two and three year forward forecast period. Thornton's Separability Index (SI) was used to evaluate the degree of separation achieved by each feature subset.

In this study it was examined whether Pairs trading is a potentially profitable trading strategy on the Johannesburg Stock Exchange. Pairs trading is a quantitative based trading strategy, in which shares are paired up based on a historic price relationship and traded accordingly, in a contrarian manner, when they diverge from said historical relationship. The essence of Pairs trading is to take advantage of perceived market inefficiencies, which is a direct contradiction of the Efficient Markets Hypothesis (even in its weak form). This study tested Pairs trading on both an unrestricted (any two shares can be paired), as well as a sector-restricted (only pairs within the RESI and the FINDI sectors could be paired), sample of shares (the JSE Top80 - based on market capitalization). Furthermore, a number of different signals (which are based on standard deviations) to open and close pairs were tested, on both the unrestricted and sector-restricted samples. The aim of using different samples of shares, as well as different trading signals, was to determine whether or not different strategies could serve to bolster the performance of a Pairs trading strategy.

Most investors would want to know what is included in the price of a share and how far accounting data explain the share price. This study uses the most common measures of financial performance to measure what is explained by the share price. Most analyst briefings use these financial performance measures: book value per share, cash flow per share, earnings per share and most recently the market performance measure, the economic value added (EVA) in the share valuations. The objective of the study is to examine the relationship between the above measures of financial performance as presented in financial statements and the share prices and share returns. If there is a relationship, which measure is most closely related to both share prices and share returns? The study uses data obtained from a balanced sample of 87 companies listed on the Johannesburg Stock Exchange (JSE) during the ten-year period (2005-2014). Both the price and the returns models were used to analyse this financial data to find out which accounting measure has the greatest explanatory power on the share prices and share returns (measured by the R-squared or R 2metric). For the price model, share prices 3 months after the financial yearend were used to allow for the release of financial information. Using the price model, earnings have the highest overall R2 at 56.4%, with book values at 18.4%, EVA at 2.18% and lastly operating cash flows at 1.18%. This effectively means that earnings per share is more value relevant in determining firm value than either book value of equity, EVA and operating cash flows, respectively. Using incremental value relevance, equity book values and earnings explain 65% of the share prices. However, changes in EVA deflated by price have the greatest explanatory power (R 2 at 30%) using the returns model and none of the other measures(earnings and operating cash flows) have a significant relationship with share returns. Overall the results show that both accounting based (book value of equity and earnings) and market based measures (EVA) are value relevant in determining firm value. The results also show that a consideration of more than one variable in determining firm value is more informative than considering each variable separately. EVA should also be used in determining value as it has shown that it explains some of the share prices and returns.

Includes bibliographical references (leaves 116-125). / This research was conducted to establish whether venture capital could reliably serve as a source of finance for SMEs given that there is a problem of access to finance in Namibia. This is important because SMEs in Namibia are generally in dire need of finance. Evidence therefore shows that venture capital as a source of finance serves as an ideal type of instrument for the development of SMEs internationally. The study assessed the importance of venture capital financing in the context of the SMEs in Namibia, specifically focusing on addressing the problem of lack of much needed capital and skills to the SME sector. The second objective was to assess whether venture capital financing can be effectively utilised to enhance managerial skills within SMEs in Namibia.

The Mineral and Petroleum Resources Development Amendment Bill has drawn criticism from industry experts and the press. There are a number of amendments that could be damaging to future investment in South Africa's upstream oil and gas industry. This study examines the key changes brought about by the Bill, South Africa's fiscal terms, how the fiscal terms are impacted by the Bill and current activity in South Africa's upstream oil and gas sector. The report then focuses on the most significant change made by the Bill, which is the level of State Participation. A fit for purpose economic model was built and the resulting cash flows were used to calculate the economic indicators presented in the results. The results from the model indicate how the increase in State Participation levels affects the ranking of South Africa's fiscal terms and the profitability of hypothetical investment opportunities. When ranked on fiscal terms, the country moves from having some of the best terms in Africa without the new Bill, to a position where the fiscal terms can be described as average or even onerous, depending on the interpretation of the State Participation clause. Accordingly, the result of the hypothetical investment opportunity has very positive economic indicators without the changes from the new Bill. If the most optimistic interpretation of the State Participation clause is modelled, the opportunity is less attractive but still viable and if the most pessimistic interpretation is modelled, the opportunity would not warrant investment. Even though South Africa has limited reserves, significant exploration activity is taking place under the existing legal and fiscal framework. If the Bill is implemented in its current format, it is likely that the country will see a significant decline in investment in the upstream oil and gas industry. Attracting new investment by international oil and gas companies in an environment governed by the terms of the proposed Bill will be challenging.

Purpose - The analysis of the South Africa property sector to provide an effective inflation hedge has not been researched to the same extent as other more developed countries. In addition, the South African property sector has been excluded from international studies owing to its underdevelopment and inconsistent legislative environment. However, post 2013 the new SA REIT legislation was promulgated putting it on par with its international counterparts. In addition from 2012-2013 the market capitalisation of the sector doubled. The study reviews inflation's relationship with direct and indirect property, and the study compares this relationship to other asset classes available to investors. It further reviews the difference between inflation hedging versus inflation protection, using different measures of inflation hedging and also reviews the various component parts of inflation being expected versus unexpected inflation. Design/methodology/approach - The methodology in this study is adopted from the extensive research previously applied to other more developed markets. Additionally, technical and fundamental analysis of returns, correlations, risks and returns were applied.

Financial advisors have long been considered a part of the financial market through the advice that they offer investors. Behavioural finance has demonstrated that individual investors do not always behave in a rational manner, unlike financial advisors who seem not be prone to the behavioural biases that individuals experience when investment decisions are made. Furthermore, financial advisors have greater access to information, financial analytical tools, as well as better education in financial markets compared to the average individual. Financial advisors are thus better equipped to assist individual investors and provide them with improved investment results. This study investigated the value added by financial advisors in the investment performance of advised individual investors as opposed to non-advised individuals. The study wanted to establish whether financially advised individuals showed greater return on investments than non-advised individuals. A sample of individual investors from a large South African investment house were analysed across the investment categories of an advised investor and a non-advised investor for a period of 10 years from 1 January 2005 to 31 December 2014. The data was analysed to draw conclusions on returns, trading behaviour, the risk profile of investors and the reasons for differences identified. The results indicated that there is no statistical difference between the returns generated between advised investors, non-advised investors and the fund invested over the period. There was a statistical difference between the number of trades entered into by advised and non-advised investors, with advised investors making statistically more trades than nonadvised investors. There was no significant difference between the risk profiles of the investors based on qualitative data. The results indicate that there is no significant additional benefit of utilising a financial advisor, after the initial decision of which fund to invest in has been made.

Bibliography: p. 111-114. / This thesis provides an investigation of the applicability of time series analysis to the process of economic model building. Chapter l explains the position of the Box-Jenkins approach to time series analysis in relation to other techniques of analysis. In Chapters 2 and 3 the theory of model building is discussed. In Chapter 4 an econometric model is analysed in detail from a time series approach.