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

by Au Wai Shan, Christine, Choi Wing Kam. / Thesis (M.B.A.)--Chinese University of Hong Kong, 2000. / Includes bibliographical references (leaves 86-90). / ABSTRACT --- p.ii / ACKNOWLEDGEMENT --- p.iv / TABLE OF CONTENTS --- p.v / LIST OF TABLES --- p.vii / CHAPTER / Chapter I. --- INTRODUCTION --- p.1 / Chapter II. --- LITERATURE REVIEW --- p.3 / Chapter III. --- METHODOLOGY --- p.9 / Chapter 1 --- Source of Data and Company Information --- p.9 / Chapter 1.1 --- Data on Security Prices and Macroeconomic Variables --- p.9 / Chapter 1.2 --- Company Annual Reports --- p.9 / Chapter 1.3 --- "Journals, Newspapers and Related Magazines" --- p.10 / Chapter 2. --- Selection of Company --- p.10 / Chapter 3. --- "Whatts PanEL,Data?" --- p.10 / Chapter 3.1 --- Benefits of using Panel Data --- p.11 / Chapter 3.2 --- Limitations of using Panel Data --- p.12 / Chapter 4. --- Multiple regression analysts --- p.13 / Chapter 4.1 --- What is multiple regression model? --- p.13 / Chapter 4.2 --- Assumptions of multiple regression --- p.15 / Chapter 5. --- FtnanctaL RatIo Analysts --- p.16 / Chapter 6. --- Economic Factor Analysis --- p.19 / Chapter IV. --- FINDINGS --- p.20 / Chapter 1. --- ResuLts of MULttpte Regression (By Individual Company) of the Stock Price and MacRoeconomtc factors --- p.20 / Chapter 1.1 --- "R2, Coefficients of variables and F-statistic" --- p.20 / Chapter 1.2 --- Correlation Among the Macroeconomic Factors --- p.23 / Chapter 2. --- Results of MULTIpLe REgREssIons (By Sectors) of thE Stock Prtce and Financial Statement RatIos --- p.24 / Chapter 2.1 --- "R2, Coefficients of variables and F-statistic" --- p.24 / Chapter 2.2 --- Correlation among the Micro-economic Factors --- p.25 / Chapter V. --- DISCUSSIONS --- p.27 / Chapter 1. --- Summary of findings --- p.27 / Chapter 2. --- Discusston of the impact of economic factors on the stock price --- p.28 / Chapter 3. --- "Dtscusston the impacts of ftnancial, statement ratios on the stock price" --- p.29 / Chapter 4. --- LImItattons on our model --- p.31 / Chapter 4.1 --- Outlier Problems --- p.31 / Chapter 4.2 --- Average stock price in the month of announcing annual reports --- p.31 / Chapter 4.3 --- Using of annual data --- p.32 / Chapter VI. --- FURTHER DISCUSSION ON NOWADAYS PHENOMENA --- p.33 / Chapter 1. --- Greenspan's Theory --- p.33 / Chapter 2. --- ThE FEvER of Internet/ TEchnoLOgy/ConcEPt Stock --- p.34 / Chapter VII. --- RECOMMENDATIONS --- p.35 / Chapter 1. --- Other mEthodoLogIEs --- p.35 / Chapter 2. --- Other Ratios with same or similar meanings --- p.36 / Chapter 3. --- Other indices --- p.37 / Chapter 4. --- A new standard： sustatnaBILIty --- p.37 / Chapter VIII. --- CONCLUSION --- p.39 / APPENDIX --- p.40 / BIBLIOGRAPHY --- p.86

Wu Haijun. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2000. / Includes bibliographical references (leaves 45-48). / Abstracts in English and Chinese. / Abstract --- p.ii / Acknowledgement --- p.iv / Chapter Chapter 1. --- Introduction --- p.1 / Chapter Chapter 2. --- Literature Review --- p.4 / Chapter 2.1. --- The Fisher Hypothesis --- p.4 / Chapter 2.2. --- International Fisher Equation --- p.11 / Chapter Chapter 3. --- Theoretical Basis on The Link Between Stock Return Differential and Inflation Rate Differential --- p.15 / Chapter Chapter 4. --- Data Description --- p.19 / Chapter Chapter 5. --- Results --- p.23 / Chapter 5.1. --- Does The Generalized Fisher Hypothesis Hold In The Long Horizons --- p.24 / Chapter 5.2. --- Does International Fisher Equation Hold --- p.29 / Chapter 5.3. --- Can International Elements Account For The Failure of Fisher Hypothesis --- p.36 / Chapter Chapter 6. --- Conclusion --- p.43 / Bibliography --- p.45 / Appendix A --- p.49 / Chapter A.1. --- The link between interest rate differential and inflation rate differential --- p.49 / Chapter A.2. --- Instrumental Variable Estimation --- p.53 / Appendix B --- p.59 / Chapter B.1. --- Hong Kong CPI(A) Source --- p.59 / Chapter B.2. --- Taiwan CPI Source --- p.61 / LIST OF TABLES / Table 4.1: Data Description --- p.21 / Table 4.2: Means and Standard Deviations of Inflation and Stock Returns --- p.22 / Table 5.1: Short-term (One Year) Test on Fisher Hypothesis on Stock Returns --- p.26 / Table 5.2: Long-term (Five Years) Test on Fisher Hypothesis on Stock Returns --- p.27 / Table 5.3: Long-term (Ten Years) Test on Fisher Hypothesis on Stock Returns --- p.30 / Table 5.4: Short-term (One Year) Test For International Fisher Equation on Stock Returns --- p.33 / Table 5.5: Long-term (Five Years) Test For International Fisher Equation on Stock Returns --- p.34 / Table 5.6: Long-term (Ten Years) Test For International Fisher Equation on Stock Returns --- p.35 / Table 5.7: Testing Effects of International Elements on The Fisher Hypothesis --- p.39 / Table 5.8: Regression Results For The Coefficients of Domestic Inflation With and Without International Elements --- p.40

Mak Wing Hei. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2006. / Includes bibliographical references (leaves 50-52). / Abstracts in English and Chinese. / ABSTRACT --- p.1 / 摘要 --- p.2 / ACKNOWLEDGEMENTS --- p.3 / TABLE OF CONTENTS --- p.4 / Chapter CHAPTER 1 --- INTRODUCTION & LITERATURE REVIEW --- p.6 / Chapter CHAPTER 2 --- DATA DESCRIPTION --- p.12 / Chapter 2.1 - --- Coverage and Sources --- p.12 / Chapter 2.2 - --- Match Accounting Data with Stock Returns --- p.12 / Chapter 2.3 - --- Selection Rule --- p.13 / Chapter 2.4 - --- Choice of the Threshold Variables Z --- p.14 / Chapter CHAPTER 3 --- THE MODEL --- p.15 / Chapter 3.1 - --- Estimating excess returns & Betas --- p.15 / Chapter 3.2- --- Estimating Threshold Effects --- p.17 / Chapter 3.3 - --- Testing the Number of Threshold Variables --- p.19 / Chapter 3.4 - --- Estimating Threshold values --- p.21 / Chapter CHAPTER 4 --- PRELIMINARY OBSERVATIONS --- p.21 / Chapter 4.1 - --- Excess Returns --- p.21 / Chapter 4.2 - --- "Relationship between Beta, Market Size and Book-to-Market Equity" --- p.24 / Chapter CHAPTER 5 --- ESTIMATION RESULTS OF THE THRESHOLD MODEL --- p.35 / Chapter 5.1 - --- Number of Threshold Variables --- p.35 / Chapter 5.2- --- Threshold Value Estimates --- p.39 / Chapter 5.3- --- The “and´ح case and “or´حcase --- p.40 / Chapter 5.4 - --- Comparison with OLS --- p.45 / Chapter CHAPTER 6 --- CONCLUSION --- p.48 / REFERENCES --- p.50

Chan Chi-fai Quincy. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2003. / Includes bibliographical references (leaves 52-55). / Abstracts in English and Chinese. / ACKNOWLEDGMENTS --- p.iv / LIST OF TABLES --- p.v / LIST OF ILLUSTRATIONS --- p.vi / CHAPTER / Chapter ONE --- INTRODUCTION --- p.1 / Chapter TWO --- LITERATURE REVIEW --- p.4 / Chapter THREE --- DATA AND METHODOLOGY --- p.8 / Moving Averages (MA) / Relative Strength Index (RSI) / Buy-and-Hold (B & H) and the Annual Return / Transaction Costs and the Adjusted Return / Chapter FOUR --- EMPIRICAL RESULTS --- p.13 / Hong Kong-HSI / Results Without Short Selling / Results With Short Selling / Results / Singapore - STII / Results Without Short Selling / Results With Short Selling / Results / Taiwan-TWSE / Results Without Short Selling / Results With Short Selling / Results / Korea-KSP / Results Without Short Selling / Results With Short Selling / Results / Chapter FIVE --- CONCLUSION --- p.30 / TABLES --- p.32 / ILLUSTRATIONS --- p.45 / BIBOGRAPHY --- p.52

published_or_final_version / Business / Doctoral / Doctor of Philosophy

published_or_final_version / Statistics / Master / Master of Philosophy