A research report submitted to the School of Economic and Business Sciences, Faculty of Commerce, Law and Management, University of the Witwatersrand, in partial fulfilment (50%) of the requirements for degree of Master of Commerce in Finance. Date of submission: April 2016 / International studies have widely documented the long-run underperformance of firms conducting secondary equity offerings (SEOs), a phenomenon commonly referred to as the ‘new issues puzzle’. Understanding the market’s reaction to SEOs is vital for managers who are commonly tasked with deciding on how to finance their firm’s operations. This study investigates the short-run and long-run performance of firms conducting SEOs on the Johannesburg Stock Exchange (JSE) over the period of 1998 to 2015, by exploring both rational and behavioural models in predicting SEO behaviour. Event-study analysis reveals that the market generally reacts negatively to the announcement of SEOs with a statistically significant average two-day cumulative abnormal return of -2.6%. Using a buy-and-hold abnormal return approach, as well as factor regression analysis to study the long-run share performance of issuing firms, there is no evidence that issuing firms significantly underperform relative to non-issuing firms over a five-year period when testing for abnormal share return performance with the Capital Asset Pricing Model. Furthermore, issuing firms exhibit no consistent signs of operating underperformance in comparison to non-issuing firms over a fiveyear period. Finally, in evidence contradicting the market timing theory, investor sentiment appears to bear no consistently significant influence on either a firm’s decision to issue equity, or on the short-run and long-run performance of SEOs. Overall, the results imply that the longrun performance of SEOs conducted in South Africa is best described by rational explanations centred on the risk-return framework. There is no consistent evidence of any ‘new issues puzzle’ on the JSE. / MT2017

A research report submitted to the Faculty of Commerce, Law and Management, University of the Witwatersrand, Johannesburg, in partial fulfillment of the requirements for the degree of Master of Management in Finance and Investment. Johannesburg, 2016 / The prediction of stock price and index level in a financial market is an interesting but highly complex and intricate topic. Advancements in prediction models leading to even a slight increase in performance can be very profitable. The number of studies investigating models in predicting actual levels of stocks and indices however, far exceed those predicting the direction of stocks and indices. This study evaluates the performance of ensemble prediction models in predicting the daily direction of the JSE All-Share index. The ensemble prediction models are benchmarked against three common prediction models in the domain of financial data prediction namely, support vector machines, logistic regression and k-nearest neighbour. The results indicate that the Boosted algorithm of the ensemble prediction model is able to predict the index direction the best, followed by k-nearest neighbour, logistic regression and support vector machines respectively. The study suggests that ensemble models be considered in all stock price and index prediction applications. / MT2017

Thesis submitted in fulfilment of the requirements for the degree of Masters of Management in Finance and Investments in the Faculty of Commerce, Law and Management Wits Business School at the University of the Witwatersrand , 2016 / We use a comprehensive HedgeNews Africa data set from January 2007 to October 2016 to examine the performance of South African Hedge Funds in relation to JSE All share Index and All Bond Composite Index. We do so using Capital Assets Pricing Model (CAPM), Fama and French three-factor model and four factor model. Research on South African hedge funds are scarce, which motivate this research and in the light of the new regulation that provide for two categories of hedge funds, namely Qualified Investor hedge funds and Retail Investors hedge funds, to see how ordinary investor can benefit from this unique industry. The results show that South African hedge fund have low correlation with the All Bond Composite Index, but do not outperform the JSE All Share Index. We also find that South African hedge fund outperforms the All Bond Composite Index. We further test whether South African hedge fund managers have market timing ability and find that they do not have any significant market timing ability. / MT2017

Thesis (M.Com. (Accounting))--University of the Witwatersrand, Faculty of Commerce, Law and Management, School of Accountancy, 2017 / Research into corporate governance has shown that there are a number of factors that influence company performance, one of them being ownership structure. The objective of this study is to determine how ownership structure affects the performance of companies listed on the Johannesburg Stock Exchange (JSE). Five categories of shareholders were identified namely, managerial shareholders, institutional investors, family shareholders, government shareholders and foreign shareholders. Some shareholders of a company may be entirely passive whereas others may play a more active role in the company or perform an important monitoring service. The various motivations and abilities of the different types of shareholders may directly impact their ability to influence the major corporate decisions of the company that will ultimately impact the performance of the company. Using return on assets (ROA) and return on equity (ROE) as performance measures this study investigates the effect of ownership structure on the performance of 143 companies from the year 2004 to 2014. The results of the study reveal that of the five different categories of shareholders identified it was only managerial shareholders and institutional shareholders that had a significant impact on a company’s performance / GR2018

A Dissertation submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Master of Science, 2012. / The purpose of this study is to investigate if the International Comparison Program (ICP) methodology could be used to examine the different buying power (worth) of the currency on the same products or goods amongst South African provinces. The method will be tested on the Consumer Price Index (CPI) food data collected from January 2006 to December 2006 from the main cities in the provinces. The food basket is obtained via the Income and Expenditure Survey (IES), which is generally updated every 5 years. South Africa (SA) has disparities and differentials in economic indicators such as the CPI, Gross Domestic Product and employment, amongst the provinces which are caused by among other things geographic set-up, urbanisation, inflation rates, and expenditure patterns. We use the monthly data to do an inter-provincial comparison of food prices by deriving annual purchasing power parities (PPPs) for each of the provinces, using the Country Product Dummy (CPD) method recommended as best practice by the World Bank. The CPI data is validated using the SEMPER software developed by the African Development Bank (AfDB). The validated data is examined for variability over the months and between the provinces using Analysis of Variance. Significant price differences are found for various products over the months and between provinces. The validated data was used to compute PPPs at the group and basic heading level. PPPs were investigated for differences in the provinces on grouped level of food products using Analysis of Variance. The reliability of PPPs between provinces is investigated both at grouped and basic heading level of products using the Cronbach-alpha statistic. The results show that there are no significant variations in PPPs across provinces. This could be due to the similar business opportunities or developments in the provinces or due to the aggregation of prices from the individual product (basic heading) to the main product group level. This implies that the cost of the food basket is the same across provinces.

A 50% research report to be submitted in partial fulfilment for the degree of: MASTER OF COMMERCE (FINANCE) UNIVERSITY OF THE WITWATERSRAND / Several studies have assessed the forward-looking characteristic of share prices and confirmed their resultant capability as leading indicators of economic activity, especially in advanced economies. Contention however exists when evaluating the role of stock markets as leading indicators for less developed countries. This study examines the validity of the stock market as a leading indicator of economic activity in South Africa using quarterly time-series data for the period January 1992 to June 2014. Causality and cointegration between the JSE All Share Index against Real GDP and Real Industrial Production is evaluated by employing Granger-causality tests and the Johansen cointegration procedure. The empirical investigation indicates that unidirectional causality exists between the nominal and real stock indices and economic activity in South Africa, and confirms a long-run relationship between the JSE and GDP and Industrial Production. Therefore, similar to the study by Auret and Golding (2012), in a South African context, the stock market is in fact a leading indicator of economic activity. / MT2017

A thesis submitted to the Faculty of Commerce, Law and Management, University of the Witwatersrand, in fulfilment of the requirements for the degree of Doctor of Philosophy (Ph.D), September 2016 / This study considers momentum in share prices, per Jegadeesh and Titman (1993, 2001), on the cross-section of shares listed on the JSE. The key research objective is to define whether momentum is significant, independent and priced. ‘Significant’ implies that momentum produces significantly positive nominal and risk-adjusted profits, ‘independent’ means that momentum is independent of other non-momentum stylistic factor premiums and finally, ‘priced’ suggests that momentum is a priced factor on the JSE and thereby contributes to the cross-sectional variation in share returns. In order to determine the significance of the momentum premium on the JSE, univariate momentum sorts are conducted that consider variation in portfolio estimation and holding periods, weighting methodologies as well as liquidity constraints, price impact and microstructure effects. The results of the univariate sorts clearly indicate that momentum on the JSE is both significant and profitable assuming estimation and holding periods between three and twelve months. Furthermore, consistent with international and local literature, momentum profits reverse assuming holding periods in excess of 24 months. In order to determine whether momentum is independent, bivariate sorts and time-series attribution regressions are conducted using momentum and six non-momentum factors, namely: Size, Value, Liquidity, Market Beta, Idiosyncratic Risk and Currency Risk. The results of the bivariate sorts and time-series attribution regressions clearly indicate that momentum on the JSE is largely independent of the nonmomentum stylistic factors considered. Lastly, cross-sectional panel regressions are conducted where momentum is applied, in conjunction with the considered non-momentum factors, as an independent variable in order assess the relationship between the factors and expected returns on a share-by-share basis. The results of the panel data cross-sectional regressions clearly indicate that momentum produces a consistently significant and independent premium, conclusively proving that momentum is a priced factor that contributes to the cross-sectional variation in share returns listed on the JSE. / XL2018

Thesis (M.Com. (Finance))--University of the Witwatersrand, Faculty of Commerce, Law and Management, School of Economic and Business Sciences, 2016 / The purpose of the study is to investigate the effects of relaxing the assumption of multivariate normality typically utilised within the traditional asset pricing framework. This is achieved in two ways. The first involves the introduction of higher moments into the linear Capital Asset Pricing Model while the second involves a Monte Carlo experiment to determine the impact of skewness and kurtosis on test statistics traditionally employed to assess the validity of asset pricing models. We commence by establishing non-normality for the majority of sample portfolios. A cross-sectional regression approach is employed to estimate factor risk premia and test higher moment Capital Asset Pricing Models. Unconditional coskewness and unconditional cokurtosis are found to be priced within the market equity (size) sorted and book equity/market equity (value) sorted portfolio sets over the period January 1993 to December 2013. Conditional coskewness and conditional cokurtosis are found to be priced for only the size sorted portfolios over the period January 1997 to December 2013. Factor risk premia estimated for coskewness are generally positive while risk premia estimated for cokurtosis are negative. This suggests a positive relationship between coskewness and expected return and a negative relationship between cokurtosis and expected return. The results of the asset pricing model tests are mixed. The pricing errors for higher moment Capital Asset Pricing Models are shown to be significantly different from zero for size sorted portfolios while pricing errors on the value sorted, dual size-value sorted and industry portfolios are found to be statistically insignificant. This suggest that none of the asset pricing models tested are the true model as it would explain variation in expected returns regardless of the data generating process. Finally we show that the Ordinary Least Square Wald test statistic has the most desirable size characteristics while the Generalised Least Squares J-test statistic has the most desirable power characteristics when dealing with non-normal data.

Submitted as a Requirement of the Master of Management (Finance and Investment Management) University of the Witwatersrand Business School Johannesburg / The mid 2000’s saw the materialization of research into the financial engineering field of high frequency trading. It is arguable that the most prominent model to emerge from the research has been pairs trading. This idea can be extended to allow for more than two assets in a modelling method now known as statistical arbitrage. The research identifies a collection of assets with a deterministic component; it then follows a multiple linear regression to exploit persistent mispricings among these assets. Further, multiple linear regression metrics are used to identify the analytic form of the trading rule and to validate the performance of the model. The first part of model constructs combinations of assets which contain a significant predictable component by co-integration, the second part builds a predictive models for the dynamics of the mispricing using statistical model. The success of the model is demonstrated with reference to a statistical analysis of 5-minute closing prices on the Johannesburg Stock Exchange (JSE) TOP40 Index and the constituent shares of the JSE TOP40 Index. / MT2017

This paper aims to investigate the apparent existence of two anomalies in the South African stock market based on regular strike action, namely the month of the year effect and seasonality across specific sectors of the Johannesburg Stock Exchange.