ETD Collection

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Now showing 1 - 10 of 12
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    Does idiosyncratic risk derive price momentum and long term reversal :evidence from the Johannesburg Stock Exchange
    (2019) Mahsayanyika, Rich
    This study examines if the idiosyncratic risk is the main source behind the persistence of price momentum and reversal effects. Idiosyncratic risk limits arbitrage, regardless of the arbitrageur’s diversification. Price momentum is prevalent only in high idiosyncratic risk stocks, highlighting that idiosyncratic risk limits arbitrage in price momentum mispricing. Long-term reversal is not related to idiosyncratic risk. Long term reversal stocks generates a smaller aggregate return than price momentum stocks, so the findings along with those in related studies suggest that underreaction and overreaction might be the main driving force behind long term reversal returns. The findings of this study are consistent with some of South African literature which suggest that momentum is a more persistent investing strategy than long term reversal on the Johannesburg Stock Exchange (JSE).
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    Ranking of Brownfield mining investment opportunities using the analytic hierarchy process
    (2018) Hamilton, Neil Eric
    As the shareholders of mining companies have become increasingly informed and active, the corporate values of companies have had to evolve to remain relevant and maintain shareholder confidence. It is no longer acceptable to deliver only good financial results, as such results must be obtained in an ethical and socially responsible manner. Traditional project valuation and ranking techniques, typically a discounted cash flow (DCF) styled approach, deliver traditional financial metrics such as net present value. A DCF approach however fails to account for changing shareholder values such as safety and social responsibility. This requires other approaches such as the Analytic Hierarchy Process (AHP) which has the potential to be a more inclusive tool in the ranking of mining projects. The ranking of Brownfield mining projects is complex, with varied and often competing priorities in the evaluation process. AHP is one of several multiple criteria decision making approaches that can be applied to such complex problems. AHP is a relatively simple process which breaks the complex decision into a hierarchal approach, with criteria given a weighting according to their relative importance while assessing several options or solutions to the overall goal. The aim of this research is to apply AHP to the ranking of Brownfield mining projects to provide an alternative and potentially more inclusive project ranking than that provided through a DCF approach. Three projects from a leading gold mining company were identified, analysed and ranked using the traditional metrics of NPV, IRR and Capital developed from project specific DCF models. The corporate values as presented in the vision / mission statements of the three largest gold mining companies were analysed for commonality. Common values within the mission statements were used to populate the AHP. The various criteria within the AHP were ranked against each other through the use of pairwise comparison. Data available through the DCF models as well as data available in public annual reports was used to populate the AHP. The outcomes of the study found that traditional DCF based metrics (values) are heavily favoured over the newer corporate values. As such the rankings of the AHP mirrored the ranking based on the DCF, however, the AHP is an inclusive process. As shown through the hypothetical scenarios presented, if there is a shift in the weighting of the corporate values, the AHP ranking will differ from the DCF rankings. With more inclusive corporate value systems as shareholder demands evolve, the traditional DCF approach to Brownfield project ranking is no longer inclusive of all corporate values. Additionally, the traditional DCF approach is unable to account for shifting priorities within established corporate values. An AHP approach not only allows the end user to include all corporate values but also allows the user to adapt to additional corporate values or a shift in the prioritisation of values. The research, through the scenarios considered, demonstrates the usefulness of using AHP under various conditions. AHP provides a viable and useful tool for the ranking of Brownfield projects.
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    Evaluating the diversification effects of direct real estate within a multi asset portfolio of shares and bonds
    (2018) Singh, Vijay
    This study examined the diversification benefits of including direct real to a multi asset portfolio of stocks and bonds. Modern Portfolio Theory provided the theoretical frame work for construction of thirty multi asset portfolios, over a twenty year time period from 1995 to 2014. The methodology included the calculation of optimal portfolios, efficient barriers, returns, risks and correlation of the asset classes. The results of this study indicate that direct real estate provides significant diversification benefits to multi asset portfolios and furthermore direct real estate proved to be a diversifier of risk and a return enhancer over the time period studied.
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    The relationship between stock market and the macroeconomy: evidence from Botswana
    (2017) Rapaeye, Tebogo
    This study investigates the relationship between macroeconomy and stock market. The specific objectives are to: (a) find out the macroeconomic determinant of stock returns, (b) establish long term relationship of macroeconomic and (c) find out if there are volatility spill overs between macroeconomic volatilities and stock returns volatility. Domestic Company Index (DCI) is used to represent stock returns and (a) Consumer Price Index to represent inflation, (b) USD/BWP as exchange rates, (c) Bank rates as interest rates and (d) M2 to represent money supply as macroeconomic variables. The relevance of Gross Domestic Product (GDP) is highly acknowledged but due to limited data, it was excluded from the study. The study used monthly data of the said variables from January 1994 to December 2014 to investigate the relationship. Classic Linear Regression model is applied to establish the explanatory power of macroeconomic variables on stock returns. Auto-Regressive Distributed Lag (ARDL) is used to find out the long term relationship and lastly GARCH (1,1) is applied to find out if there is volatility spill overs between macroeconomic volatilities and stock returns volatilities. This research established that exchange rates have a negative relationship with stock returns and money supply has a positive relationship with stock returns. It was also noted that there is no long term relationship between macroeconomic variables and stock returns. Lastly, it was noted that inflation volatility and money supply volatility have a spill over effect on stock returns volatility.
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    Communities, sustainability and corporate social investment projects: are they but white elephants?
    (2018) Stander, Jovita
    ABSTRACT Set against the backdrop of one of South Africa’s coal-fired power station construction projects, this study looks at the sustainability of corporate social investment (CSI) infrastructure projects and the means of the communities involved in such projects in maintaining the infrastructure. There has been much discussion in literature about the sustainability and sustainable development of CSI projects, yet the literature has offered very little to support the notion that CSI projects in general, and CSI infrastructure projects in particular, are indeed sustainable. Literature from the private sector suggests that there is no shortage of funding, as billions of rand are spent on CSI projects. However, if this money is spent on projects which are not sustainable, the funding will eventually go to waste and not have the desired long-term effect of benefiting the intended communities as well as generations to come. The study seeks to address the question of how sustainable infrastructure projects are in practice and whether the communities involved are equipped with the necessary skills, knowledge, financial resources and management acumen to sustain them. The study’s specific objectives are to ascertain how the various stakeholders understand the term ‘sustainability’, identify the types of CSI project that stakeholders are involved in, define the involvement of government in CSI infrastructure projects, and establish whether local communities have the means to maintain and sustain CSI infrastructure projects. The study has taken into consideration six CSI infrastructure projects among a rural community situated within the sphere of influence of a power station construction project. The research methodology took the form of a case study, as this approach allows for the investigation of a situation within real-life circumstances. Qualitative and quantitative data collection techniques were used to collect the research data from the three groups identified as playing a role in the CSI projects covered within the context of the case study. The results of the study show that companies donate second-hand materials, such as furniture, IT equipment and stationery, and make once-off financial contributions. They also fund and build infrastructure such as clinics, schools and community halls. In addition, companies are involved in the training of graduates and the funding of study bursaries for non-employees. Sustainable projects are projects that require no further external funding for the project, organisation and/or community involved once it has been completed. The most sustainable projects are education and health projects; infrastructure projects; and projects which entail job creation, revenue streams and empowerment. Government’s involvement in CSI projects is deemed not to be sufficient. This may be ascribed to the absence of controls and accountability, a lack of funding, and varying development strategies, with one strategy focusing on pro-poor development while another focuses on independent development. This scenario can be improved by aligning the CSI agendas of the government and the private sector towards a concerted effort. Although the communities indicated that they were able to maintain CSI projects by following an ad hoc approach rather than a sustainable one, the results suggest that recipient communities are unable to sustain CSI projects due to a lack of education and not having a basic understanding of the reasons why projects fail. Furthermore, the study shows that communities do not have the means to maintain and sustain CSI infrastructure projects without the assistance of donor companies. Without donations, infrastructure projects are bound to become white elephants in a state of disrepair until such time as a donor company is willing to commit funding for their maintenance. Due to the lack of participation by companies identified in the donor group, it is recommended that further research be done among this group in order to obtain data on how donor companies view their involvement within the communities after the donated infrastructure projects have been completed and handed over. The research did not explore the reasons why government’s involvement in CSI projects is perceived as being lacking, and further research into this matter is recommended.
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    Country risk analysis: an application of logistic regression and neural networks
    (2017) Ncube, Gugulethu
    Country risk evaluation is a crucial exercise when determining the ability of countries to repay their debts. The global environment is volatile and is filled with macro-economic, financial and political factors that may affect a country’s commercial environment, resulting in its inability to service its debt. This re search report compares the ability of conventional neural network models and traditional panel logistic regression models in assessing country risk. The mod els are developed using a set of economic, financial and political risk factors obtained from the World Bank for the years 1996 to 2013 for 214 economies. These variables are used to assess the debt servicing capacity of the economies as this has a direct impact on the return on investments for financial institu tions, investors, policy makers as well as researchers. The models developed may act as early warning systems to reduce exposure to country risk. Keywords: Country risk, Debt rescheduling, Panel logit model, Neural net work models
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    Comparative performance of socially responsible and conventional portfolios in South Africa
    (2014-07-29) Bondera, Shingirirai
    There is a widespread view amongst private investors and public investment corporations that socially responsible investing leads to substandard returns relative to Conventional investing. Conventional portfolios are portfolios with sin stocks or lowly ranked stocks in terms of the Environmental, Social and Governance (ESG) factors whilst Socially responsible Investments (SRI) are portfolios with stocks regarded as socially desirable with high ESG rankings. We constructed two portfolios using the JSE stocks and the Bloomberg rankings in accordance with the ESG rankings guidelines. As an additional analysis, we also assessed the performances of the JSE socially responsible index, JSE TOP 40 and the FTSE JSE ALL SHARE. Using different performance measures such as the CAPM, Fama French, Carhart 4 factor model, Sharpe ratio, and Treynor ratio; we found interesting evidence contrary to the beliefs of many investors. No statistically significant difference in performance is found between our self-constructed portfolios, and the different indexes such as JSE SRI, JSE TOP 40 and the FTSE JSE indexes. We have separated beliefs from reality/ facts in this paper that socially conscious investors can perform well in South Africa.
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    Commodities and the South African investment portfolio
    (2014-01-16) Rodrigues, Jason Ross
    This study aims to make a contribution to the better understanding of the role commodities play in a portfolio, specifically in a South African investment portfolio. It considers the interactions between a fully collateralised commodity index and South African equities, bonds, property and cash. The study uses historical data to asses if commodities provide addition benefits to an investment portfolio, namely, additional returns, diversification and as an inflation hedge. The analyses used in this study are performance analysis, correlation studies and portfolio optimisation. Based on the evidence presented in this study we show that there were some benefits to adding commodities to a South African investment portfolio, namely, using commodities to diversify a portfolio and as an inflation hedge. However, commodities did not provide sufficiently large enough returns to justify their high volatility and as such would not be an appropriate stand alone investment in the South African context.
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    Market derived capital asset pricing model: cost of equity capital in a South African context
    (2013-08-22) Chivaura, Samuel William
    The Capital Asset Pricing Model (CAPM) is widely used in estimating cost of equity capital. CAPM relies on historical data to estimate beta which is subsequently used to calculate ex-ante returns. Several authors have highlighted anomalies with CAPM and have proposed various models that capture these anomalies. This study investigates the Market Derived Capital Asset Pricing Model (MCPM), an ex-ante model that uses traded option premium prices and implied volatility to determine ex-ante equity risk premium used in estimating cost of equity capital. The implied volatility captures future market risk expectation of a firm. This is of importance to corporate managers who need to establish appropriate hurdle rates when making capital budgeting decisions. Additionally, investors need to determine expected returns based on future risk outlook of an investment. Using data from the South African Johannesburg Stock Exchange (JSE) listed firms’, a comparison of cost of equity capital estimates was done using CAPM, Fama and French Three-Factor Model and MCPM. The results show MCPM’s yields higher estimates compared to CAPM and Three-Factor Model.
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