This paper contrasts the dynamical behaviors of fixed and flexible price regimes for a monopolistically competitive manufacturing sector in which firms base decisions on expectations about product demands. (author's abstract) / Series: Department of Economics Working Paper Series

Thesis (M.M. (Finance & Investment)--University of the Witwatersrand, Faculty of Commerce, Law and Management, Wits Business School, 2017 / The study examined the relationship between oil price shocks, volatilities and stock indices in the African emerging markets. The ARDL and Bivariate BEKK GARCH models are used in this study. The countries examined are Botswana, Egypt, Mauritius, Morocco, Namibia, Nigeria, South Africa, Tanzania, Kenya, Ghana, Tunisia, and the MSCI’s World Index. The study shows a bidirectional relationship between oil price shocks for Nigeria and the MSCI, but unidirectional flow from oil price shocks to Botswana, Egypt, Mauritius, Morocco, Namibia, South Africa, Tanzania, Kenya, Ghana, and Tunisia. In addition, there is evidence of unidirectional volatility spill over from oil returns to Botswana, Namibia, Tanzania, Mauritius and Kenyan, Nigeria, Tanzania, Kenya and Ghana. Finally, the study found bidirectional volatility between oil and index returns in MSCI, South Africa, and Tunisia. / MT2017

by Lo Yat-keung & Ma Kwok-wa. / Bibliography: leaves 46-47 / Thesis (M.B.A.)--Chinese University of Hong Kong, 1986

Hao He. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2006. / Includes bibliographical references (leaves 84-86). / Abstracts in English and Chinese. / Abstract / Chapter Chapter 1. --- Introduction --- p.1 / Chapter Chapter 2. --- Literature Review --- p.3 / Chapter 2.1 --- Recent Work on Synchronicity --- p.3 / Chapter 2.2 --- Recent Work on Corporate Governance --- p.5 / Chapter 2.3 --- Motivation´ؤWhy Stock Return Synchronicity Matters --- p.6 / Chapter Chapter 3. --- Theory and Hypotheses --- p.9 / Chapter 3.1 --- Derivation of Dependent Variables --- p.9 / Chapter 3.1.1 --- Corporate Governance Mechanisms --- p.9 / Chapter 3.1.1.1 --- Static Corporate Governance Mechanisms --- p.9 / Chapter 3.1.1.2 --- Dynamic Corporate Governance Mechanisms --- p.11 / Chapter 3.1.2 --- Regional Governance Mechanisms --- p.12 / Chapter 3.2 --- Quantification of Dependent Variables --- p.14 / Chapter 3.2.1 --- Quantifying corporate Governance Mechanisms --- p.14 / Chapter 3.2.1.1 --- Quantifying Static Corporate Governance Mechanisms --- p.14 / Chapter 3.2.1.2 --- Quantifying Dynamic Corporate Governance Mechanisms --- p.15 / Chapter 3.2.2 --- Quantifying Regional Governance Mechanisms --- p.19 / Chapter 3.2.3 --- Quantifying Control Variables --- p.22 / Chapter Chapter 4. --- Data --- p.23 / Chapter 4.1 --- Sample --- p.23 / Chapter 4.2 --- Definitions of Main Synchronicity Measures --- p.25 / Chapter 4.3 --- Methdology --- p.26 / Chapter Chapter 5 --- Empirical Results --- p.27 / Chapter 5.1 --- Results on Corporate Governance Mechanisms --- p.27 / Chapter 5.1.1 --- Results on Static Corporate Governance Mechanisms --- p.27 / Chapter 5.1.2 --- Results on Dynamic Corporate Governance Mechanisms --- p.29 / Chapter 5.1.2.1 --- Results on President-Changing Variables --- p.29 / Chapter 5.1.2.2 --- Results on General manager-change Variables --- p.31 / Chapter 5.2 --- Results on Regional Governance Mechanisms --- p.34 / Chapter Chapter 6. --- Conclusion --- p.36 / Reference --- p.38 / Tables and Figures --- p.41

by Ho Man Shing, William. / Thesis (M.B.A.)--Chinese University of Hong Kong, 1996. / Includes bibliographical references (leaves 41-42). / ABSTRACT --- p.i / TABLE OF CONTENTS --- p.iii / LIST OF FIGURE --- p.v / LIST OF TABLES --- p.v / Chapter / Chapter I. --- INTRODUCTION --- p.1 / Objectives of Research Project --- p.2 / Chapter II. --- LITERATURE REVIEW --- p.4 / Research work in the U. S --- p.4 / Research work in Japan and H. K --- p.5 / Chapter III. --- METHODOLOGY --- p.7 / Research design --- p.9 / Formation of portfolios --- p.10 / Univariate Analysis --- p.11 / Regression Analysis --- p.11 / Data collection --- p.12 / Chapter IV. --- RESULTS --- p.13 / Univariate analysis of returns and fundamental variables --- p.13 / Regression analysis of returns and fimdamental variables --- p.17 / Security level regression analysis of returns and fimdamental variables --- p.17 / Portfolio level regression analysis of returns and fundamental variables (ranked by different fundamental variables) --- p.21 / Portfolio level regression analysis of returns and fundamental variables (ranked by two different fundamental variables) --- p.27 / Effects of order of agglomeration and different combinations --- p.30 / Chapter V. --- SUMMARY AND CONCLUDING REMARKS --- p.37 / BIBLIOGRAPHY --- p.41 / APPENDICES / Chapter A --- List of Hang Seng Index Constituent Stocks during 1989 to1994 / Chapter B --- Print-out of the Regression Results at Security Level / Chapter C --- Print-out of the Regression Results at Portfolio Level (E/P then LS) / Chapter D --- Print-out of the Regression Results at Portfolio Level (LS then E/P)

by Chau Wing Hang, Amy, Tsang Tsz Hung. / Thesis (M.B.A.)--Chinese University of Hong Kong, 1996. / Includes bibliographical references (leaf 83). / ABSTRACT --- p.i / TABLE OF CONTENTS --- p.v / ACKNOWLEDGMENTS --- p.viii / Chapter / Chapter 1. --- INTRODUCTION --- p.1 / Chapter 1.1 --- Objective of Study --- p.1 / Chapter 1.2 --- Scope of Study --- p.1 / Chapter 1.3 --- Background on Warrant and Covered Warrant --- p.2 / Chapter 1.3.1 --- What is Warrant and Covered Warrant? --- p.2 / Chapter 1.3.2 --- Convertible Concept --- p.3 / Chapter 1.3.3 --- Purposes of Issue --- p.4 / Chapter 1.3.4 --- Dilution Effect --- p.6 / Chapter 1.3.5 --- Valuation of Warrant/Covered Warrant --- p.7 / Chapter 1.4 --- Warrant/Covered Warrant Market in Hong Kong --- p.8 / Chapter 1.4.1 --- Expiry --- p.9 / Chapter 1.4.2 --- Forms of Issue --- p.10 / Chapter 1.4.3 --- Trading Forums --- p.11 / Chapter 1.4.4 --- Underlying Securities --- p.12 / Chapter 2. --- LITERATURE REVIEW --- p.13 / Chapter 2.1 --- Binomial Tree Model --- p.13 / Chapter 2.2 --- Black-Scholes Model --- p.16 / Chapter 3. --- METHODOLOGY --- p.18 / Chapter 3.1 --- Working Procedures --- p.19 / Chapter 3.2 --- Samples --- p.20 / Chapter 3.3 --- Data Collection --- p.22 / Chapter 3.4 --- Computation of Theoretical Prices --- p.24 / Chapter 3.5 --- Black's Approximation --- p.25 / Chapter 3.6 --- Fair Value --- p.27 / Chapter 3.6.1 --- Option Pricing Models --- p.27 / Chapter 3.6.2 --- Comparison between P tw bt and P tw ba --- p.28 / Chapter 3.6.3 --- Result of Comparison --- p.29 / Chapter 3.6.3.1 --- Results on Hypothesis Testing --- p.29 / Chapter 3.6.3.2 --- Results on Regressional Analysis --- p.30 / Chapter 3.6.4 --- Justification --- p.32 / Chapter 3.7 --- Hypothesis Testing --- p.34 / Chapter 3.8 --- Assumptions In Our Study --- p.34 / Chapter 4. --- FINDINGS --- p.36 / Chapter 4.1 --- Calculation with 250-day Historical Volatility --- p.36 / Chapter 4.1.1 --- First Sub-period (Sep 1，94 - Feb 28，95) --- p.36 / Chapter 4.1.2 --- "Second Sub-period (Mar 1,95-Aug 31,95)" --- p.37 / Chapter 4.1.3 --- "Whole Study Period (Sep 1, 94-Aug 31,95)" --- p.37 / Chapter 4.2 --- Calculation with 63-day Historical Volatility --- p.39 / Chapter 4.2.1 --- "First Sub-period (Sep 1, 94 - Feb 28，95)" --- p.39 / Chapter 4.2.2 --- "Second Sub-period (Mar 1, 95 - Aug 31,95)" --- p.39 / Chapter 4.2.3 --- "Whole Study Period (Sep 1,94-Aug 31，95)" --- p.40 / Chapter 5. --- CONCLUSION AND COMMENTS --- p.41 / Chapter 5.1 --- General Comments --- p.41 / Chapter 5.2 --- Volatility --- p.42 / Chapter 5.3 --- Expectations --- p.44 / Chapter 5.4 --- Transaction Costs --- p.45 / Chapter 6. --- LIMITATIONS OF STUDY --- p.46 / APPENDIX --- p.47 / Chapter 1 --- List of Covered Warrants / Chapter 2 --- Historical Volatility Calculation of Ordinary Stock Example : New World Development Co. Ltd “017´ح / Chapter 3 --- "Black's Approximation Calculation and Hypothesis Testing Example : Morgan S - NWD War 96 ""1036""" / Chapter 4 --- "Comparison between P tw bt and P twBA Example : SG War - HKTEL War 95 ""1098"" Morgan S- NWD War 96 ""1036"" Swiss B - HLAMD War 95 “344""" / Chapter 5 --- Results on 250-Day Historical Volatility / Chapter 6 --- Results on 63-Day Historical Volatility / Chapter 7 --- "Chart - Pw vs Ptw BA Example : Morgan S - NWD War 96 “1036´ح Swiss B - HLAND War 95 ""344""" / Chapter 8 --- "Chart - Historical Volatility Example : New World Development Co. Ltd. “017´ح HSBC Holdings plc. ""005""" / BIBLIOGRAPHY --- p.83

by Ho Ka-Hon, Lai Chun-Yin Antony. / Thesis (M.B.A.)--Chinese University of Hong Kong, 1998. / Includes bibliographical references (leaves 48-50). / ABSTRACT --- p.II / TABLE OF CONTENT --- p.IV / LIST OF TABLES --- p.VI / ACKNOWLEGEMENT --- p.VII / Chapter 1. --- INTRODUCTION --- p.1 / Chapter 2. --- WARRANT MARKET IN HONG KONG --- p.2 / Chapter 2.1 --- Features of Options --- p.2 / Chapter 2.2 --- Derivative Securities Listed on the Hong Kong Stock Exchange --- p.3 / Chapter 2.3 --- Discussion on Covered Warrants in SEHK --- p.4 / Chapter 2.4 --- Hedging Strategies of Covered Warrants Issuers --- p.6 / Chapter 2.5 --- Regulatory Environment of Derivative Warrants --- p.6 / Chapter 3. --- WARRANT VALUATION --- p.9 / Chapter 3.1 --- Factors Affecting Warrant Price --- p.9 / Chapter 3.2 --- Put-Call Parity --- p.10 / Chapter 3.3 --- Black-Scholes Model --- p.11 / Chapter 3.4 --- Absolute Diffusion Model --- p.12 / Chapter 1.5 --- Square-Root CEV Model --- p.13 / Chapter 4. --- LITERATURE REVIEW --- p.15 / Chapter 5. --- DATA AND METHODOLOGY --- p.19 / Chapter 5.1 --- Sample Data --- p.19 / Chapter 5.2 --- Measure the Performance of Warrant Pricing Models --- p.21 / Chapter 5.3 --- Data Enhancement --- p.23 / Chapter 5.4 --- Explanatory Factors of the Pricing Errors --- p.25 / Chapter 6. --- DATA ANALYSIS --- p.27 / Chapter 6.1 --- Performance of Black-Scholes Model --- p.27 / Chapter 6.1.1 --- Data Enhancement --- p.28 / Chapter 6.1.2 --- Other Observations --- p.30 / Chapter 6.2 --- Performance of Absolute Diffusion Model --- p.31 / Chapter 6.2.1 --- Data Enhancement --- p.32 / Chapter 6.2.2 --- Other Observations --- p.34 / Chapter 6.3 --- Performance of Square Root CEV Model --- p.35 / Chapter 6.3.1 --- Data Enhancement --- p.35 / Chapter 6.3.2 --- Other Observations --- p.37 / Chapter 6.4 --- Comparison between the Warrant Pricing Models --- p.38 / Chapter 6.5 --- The Performance in Blue Chip Warrants and Red Chip Warrants --- p.40 / Chapter 6.6 --- Factors Affecting the Pricing Errors --- p.41 / Chapter 6.7 --- Comparison with Other Studies --- p.43 / Chapter 7. --- CONCLUSION --- p.46 / REFERENCE --- p.48

實證證據顯示商品價格有均值回歸和跳躍的特性。由於一些商品期權收益涉及歷史商品價格的算術平均，因此我們求出算術亞式期權在均值回歸跳躍擴散過程下的分析解。比分析解是對資產價格最終值和實際平均值的聯合特徽函數進行快速傅立葉變換獲得。我們通過數值模擬研究來檢驗此建議方法的準確度和計算效率。 / Empirical evidence indicates that commodity prices are mean reverting and exhibit jumps. As some commodity option payoff involves the arithmetic average of historical commodity prices, we derive an analytical solution to arithmetic Asian options under a mean reverting jump diffusion process. The analytical solution is implemented with the fast Fourier transform based on the joint characteristic function of the terminal asset price and the realized average value. We also examine the accuracy and computational efficiency of the proposed method through numerical studies. / Detailed summary in vernacular field only. / Chung, Shing Fung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2013. / Includes bibliographical references (leaves 40-42). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts also in Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Model with constant parameters --- p.5 / Chapter 2.1 --- Model specification --- p.6 / Chapter 2.2 --- Joint characteristic function --- p.8 / Chapter 3 --- Model with time-dependent parameters --- p.12 / Chapter 3.1 --- Model specification --- p.13 / Chapter 3.2 --- Joint characteristic function --- p.13 / Chapter 4 --- Fast Fourier transform on Asian option prices --- p.18 / Chapter 5 --- Numerical results --- p.20 / Chapter 5.1 --- Comparison of the analytical solution and Monte Carlo simulation . --- p.20 / Chapter 5.2 --- Price sensitivity and model parameters --- p.26 / Chapter 5.3 --- Price sensitivity and payoff structure --- p.26 / Chapter 6 --- Conclusion --- p.33 / Chapter A --- Normally distributed jump size --- p.34 / Bibliography --- p.40

Lai, Kwok Tung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (leaves 64-66). / Abstracts in English and Chinese. / Abstract --- p.i / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Literature Review --- p.9 / Chapter 3 --- Preliminary Analysis of Data --- p.17 / Chapter 3.1 --- Data --- p.17 / Chapter 3.2 --- Preliminary Analysis of Unspanned Stochastic Volatility --- p.20 / Chapter 4 --- A Jump-Diffusion Model for Federal Funds Target Rate --- p.23 / Chapter 4.1 --- Model Specification --- p.23 / Chapter 4.2 --- Estimation Result --- p.31 / Chapter 5 --- Pricing and Hedging Performance of Interest Rate Derivatives --- p.34 / Chapter 5.1 --- Pricing Performance of Interest Rate Cap --- p.34 / Chapter 5.2 --- Hedging Performance of Interest Rate Caplet --- p.38 / Chapter 5.3 --- Hedging Performance of Interest Rate Straddle --- p.42 / Chapter 6 --- Conclusion --- p.49 / Figures --- p.51 / Tables --- p.55 / Bibliography --- p.64

Of the many analytical methods collectively referred to as Modern Portfolio Theory (MPT), the Capital Asset Pricing Model (CAPM) is the most familiar to today’s generation of students of finance. The popularity of the CAPM arises from its success in expressing a powerful theoretical insight in a simple, usable form. The primary use of the CAPM is to determine minimum required rates of return from investment in risky assets. The variable in the CAPM is called ‘beta’, a statistical measure of risk which has become familiar to all finance professionals. Over the past decade, beta has become the most widely recognised and applied measure of risk in the investment community. The model has been extensively tested in the developed capital markets, mainly in the United States of America. But the model has not been extensively tested in other developed and developing countries, often due to the size of the capital market and the lack of the data in these countries. This study attempts to fill this vacuum and tries to update the earlier tests done on the Stock Exchange of Singapore. On addition, a review of the validity of the CAPM over time, as proxied by the stationarity of the beta, is performed. Also, tests regarding heteroskedasticity and its implications have been undertaken. / Master of Commerce (Hons)