published_or_final_version / Business Administration / Master / Master of Business Administration

published_or_final_version / Management Studies / Master / Master of Business Administration

published_or_final_version / Real Estate and Construction / Doctoral / Doctor of Philosophy

published_or_final_version / Statistics / Master / Master of Philosophy

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 in partial fulfilment of the requirements for the degree M.Com. Masters (Finance) in the School of Economic and Business Sciences at the University of the Witwatersrand, Johannesburg / This study empirically investigates the existence of the Samuelson Hypothesis in South African markets. The Samuelson Hypothesis states that the volatility of futures contracts increase as the expiration of the contracts approaches. It is an important phenomenon to account for when setting margins, creating hedging strategies and valuing options on futures. The study utilizes daily closing prices of agricultural and non-agricultural futures contracts for a period varying from 2002 to 2015. In total, eleven contracts were examined over this period, yet only one (White Maize) consistently shows support for the Samuelson Hypothesis. The Negative Covariance and State Variable Hypothesis were tested, but could not provide an alternative explanation for the lack of relationship between the time to maturity and volatility of futures contracts. / 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

A thesis submitted to the School of Economic and Business Sciences, Faculty of Commerce, Law and Management, University of the Witwatersrand in fulfilment of the requirements for the degree of Doctor of Philosophy (Ph/D). Johannesburg, South Africa June 2016 / In recent years, the debate on market efficiency has shifted to providing alternate forms of the hypothesis, some of which are testable and can be proven false. This thesis examines one such alternative, the Adaptive Market Hypothesis (AMH), with a focus on providing a framework for testing the dynamic (cyclical) notion of market efficiency using South African equity data (44 shares and six indices) over the period 1997 to 2014. By application of this framework, stylised facts emerged. First, the examination of market efficiency is dependent on the frequency of data. If one were to only use a single frequency of data, one might obtain conflicting conclusions. Second, by binning data into smaller sub-samples, one can obtain a pattern of whether the equity market is efficient or not. In other words, one might get a conclusion of, say, randomess, over the entire sample period of daily data, but there may be pockets of non-randomness with the daily data. Third, by running a variety of tests, one provides robustness to the results. This is a somewhat debateable issue as one could either run a variety of tests (each being an improvement over the other) or argue the theoretical merits of each test befoe selecting the more appropriate one. Fourth, analysis according to industries also adds to the result of efficiency, if markets have high concentration sectors (such as the JSE), one might be tempted to conclude that the entire JSE exhibits, say, randomness, where it could be driven by the resources sector as opposed to any other sector. Last, the use of neural networks as approximators is of benefit when examining data with less than ideal sample sizes. Examining five frequencies of data, 86% of the shares and indices exhibited a random walk under daily data, 78% under weekly data, 56% under monthly data, 22% under quarterly data and 24% under semi-annual data. The results over the entire sample period and non-overlapping sub-samples showed that this model's accuracy varied over time. Coupled with the results of the trading strategies, one can conclude that the nature of market efficiency in South Africa can be seen as time dependent, in line with the implication of the AMH. / MT2017

by Wai Chi-kin. / Abstract also in Chinese / Bibliography: leaves 174-175 / Thesis (M.B.A.)--Chinese University of Hong Kong, 1982

by Chan Man Kam, Chung Kwai Ying, Fung Po Hei. / Thesis (M.B.A.)--Chinese University of Hong Kong, 1990. / Bibliography: leaf 52. / ABSTRACT --- p.ii / TABLE OF CONTENTS --- p.iv / LIST OF TABLES --- p.vi / ACKNOWLEDGEMENT --- p.vii / Chapter / Chapter I. --- INTRODUCTION --- p.1 / Justification of the research --- p.1 / Research Objectives --- p.3 / Chapter II. --- METHODOLOGY --- p.5 / Data Source --- p.5 / Models --- p.7 / Model 1-Simplified Kassouf Model --- p.8 / Model 2 -Shelton Model --- p.10 / Model 3-Black-Scholes Model --- p.13 / Testing Methods --- p.16 / Objectives --- p.16 / Test of accuracy --- p.17 / Rank Test --- p.19 / Chapter III. --- RESULTS & FINDINGS --- p.22 / Estimating the Shelton Model --- p.22 / Estimation of Shelton Model --- p.22 / The validity of model --- p.26 / Overestimation or underestimation --- p.31 / Mean Error vs. Mean Absolute Error --- p.32 / Ranking of the models --- p.33 / Sensitivity Analysis --- p.37 / Simplified Kassouf Model --- p.38 / Shelton Model --- p.39 / Black-Scholes Model --- p.42 / Elasticity of warrant price --- p.43 / Warrants issued by the same company --- p.44 / Chapter IV. --- CONCLUSION --- p.46 / Chapter V. --- LIMITATION OF MODELS & FUTURE RESEARCH --- p.48 / APPENDICES --- p.50 / BIBLIOGRAPHY --- p.52