This study attempts to determine the usefulness of Sharpe's Beta Coefficient in explaining the relationship between selected indices and individual securities. Basically, this involved doing a correlation-regression analysis on the returns of randomly selected securities against those of specific market indices. The returns for both variables were calculated traditionally, that is, by taking the price differential between the closing price at the end of the previous and present quarter and adding the quarterly dividend (where applicable) and dividing the total by the initial price. This was performed for six test periods. Generally, the tests yielded negative results. The amount of explained variation in individual security returns by the Beta Coefficient is negligible. This study concludes by providing some explanations and suggesting modifications. / Business, Sauder School of / Graduate

by Cheung Chan-Wah. / Thesis (M.B.A.)--Chinese University of Hong Kong, 2001. / Includes bibliographical references (leaves 80-86). / ABSTRACT --- p.ii / TABLF OF CONTENTS --- p.iii / LIST OF TABLES --- p.iv / ACKNOWLEDGMENTS --- p.v / Chapter / Chapter I --- INTRODUCTION l --- p.1 / Chapter II. --- REVIEW OF LITERATURE --- p.7 / Chapter III. --- METHODOLOGY。 --- p.16 / Summary Statistics --- p.16 / Correlation --- p.21 / GARCH Estimation --- p.22 / Chapter IV. --- NATIONAL MARKET INDEX AND DATA --- p.31 / National Stock Indices and Trading Mechanisms --- p.31 / Stock Return Data and Data Transformation --- p.34 / Chapter V. --- EMPIRICAL RESULTS --- p.37 / Summary Statistics --- p.37 / Cross-Correlation --- p.45 / GARCH Estimation --- p.51 / Chapter VI. --- SUMMARY AND CONCLUSION --- p.75 / BIBLIOGRAPHY --- p.80

Li Zimu. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2006. / Includes bibliographical references (leaves 65-68). / Abstracts in English and Chinese. / Abstract --- p.ii / 中文摘要 --- p.iii / Acknowledgements --- p.iv / Contents --- p.v / Chapter Chapter 1. --- Introduction --- p.1 / Chapter Chapter 2. --- Literature Review --- p.5 / Chapter 2.1 --- Duration Dependence in Business Cycles --- p.5 / Chapter 2.2 --- Duration Dependence in Stock Market Cycles --- p.7 / Chapter 2.3 --- Definition of Bull and Bear Markets --- p.10 / Chapter Chapter 3. --- Nonparametric Tests for Duration Dependence --- p.12 / Chapter 3.1 --- Duration Dependence --- p.12 / Chapter 3.2 --- Stock Market Cycle Periodicity --- p.15 / Chapter 3.3 --- W and W (t0 =a) Tests --- p.18 / Chapter 3.4 --- Z and Z (t0 =a) Tests --- p.20 / Chapter Chapter 4. --- Data Analysis --- p.21 / Chapter 4.1 --- Dow Jones Industrial Average Index --- p.23 / Chapter 4.2 --- NASDAQ Composite Index --- p.29 / Chapter 4.3 --- Shanghai A Share Index --- p.33 / Chapter 4.4 --- Shenzhen B Share Index --- p.38 / Chapter Chapter 5. --- Empirical Results --- p.42 / Chapter 5.1 --- Dow Jones Industrial Average Index --- p.45 / Chapter 5.2 --- NASDAQ Composite Index --- p.47 / Chapter 5.3 --- Shanghai A Share Index --- p.49 / Chapter 5.4 --- Shenzhen B Share Index --- p.51 / Chapter 5.5 --- Summary of Significant W and Z tests --- p.53 / Chapter Chapter 6. --- Sub-sample Analysis --- p.54 / Chapter 6.1 --- Sub-sample 1 of the Dow Jones Index´ؤ --- p.56 / Chapter 6.2 --- Sub-sample 2 of the Dow Jones Index´ؤ --- p.57 / Chapter 6.3 --- Comparison of Sub-samples of the Dow Jones Index --- p.58 / Chapter 6.4 --- Comparison of the Dow Jones Index and the NASDAQ Composite Index --- p.60 / Chapter Chapter 7. --- Conclusion --- p.62 / References --- p.65

本論文的第一部分介紹一個帶基準約束的連續時間均值方差資產組合選擇問題。這個非凸優化問題將採用拉格朗日乘數來解決，並求出相應的答案及其存在準則。為了進行敏感性分析，相應的最佳投資組合及其一些導數將被明確求出。在第二部分中，我們採用標準的線性回歸技巧來檢定三個日曆效應是否在統計上顯著。其中最顯著的效應是四月及十二月的回報比全年平均為高。 / The first part of this thesis presents a benchmarked continuous-time mean-variance portfolio selection problem. The method of Lagrange multipliers is employed to solve this non-convex optimization problem, and the criterion for the existence of solution is derived accordingly. The corresponding efficient portfolio and its derivatives are explicitly derived for sensitivity analysis. The second part we employ the standard linear regression technique to test whether three calendar effects are statistically significant. The most significant effect is that the returns in April and December are higher than the average in the whole year. / Detailed summary in vernacular field only. / Yip, Fai Lung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 49-53). / Abstracts also in Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Mean Variance --- p.5 / Chapter 2.1 --- Model --- p.5 / Chapter 2.2 --- Portfolio Selection and the Solution --- p.9 / Chapter 2.3 --- Existence and Uniqueness of Lagrange Multipliers --- p.21 / Chapter 2.4 --- Optimal Trading Strategy --- p.29 / Chapter 2.5 --- Sensitivity Analysis --- p.34 / Chapter 3 --- Calendar Effect --- p.39 / Chapter 3.1 --- Data and Method --- p.39 / Chapter 3.2 --- Results --- p.42 / Chapter 4 --- Appendix --- p.47 / Chapter 4.1 --- Procedures Used to Obtain the Results in Chapter 4 --- p.47 / Bibliography --- p.49

published_or_final_version / abstract / Economics and Finance / Doctoral / Doctor of Philosophy

Cheung Hiu-Yan. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2001. / Includes bibliographical references (leaves 83-87). / Abstracts in English and Chinese. / ACKNOWLEGMENTS --- p.iii / LIST OF TABLES --- p.iv / LIST OF ILLUSTRATIONS --- p.vi / CHAPTER / Chapter ONE --- INTRODUCTION --- p.1 / Chapter TWO --- THE LITERATURE REVIEW --- p.6 / The Family of the ARFIMA Process / Parameter Estimation of the ARFIMA Process / Applications in Economic and Financial Time Series / Chapter THREE --- THEORETICAL MODELS AND METHODOLOGY --- p.16 / Theoretical Models of Long-memory Process / Parameter Estimation / Model Selection Criteria / Hypothesis Testing / Diagnostic Checking / Evaluating the Forecasting Performance / Chapter FOUR --- EMPIRICAL RESULTS OF SIMULATION EXPERIMENTS --- p.37 / Monte Carlo Simulation / Parameter Estimation / Results of Simulation Experiments / Chapter FIVE --- DATA AND EMPIRICAL RESULTS --- p.46 / Data Description / A Long-memory Model for the Return Series / Model Evaluation / Chapter SIX --- CONCLUSION --- p.55 / TABLES --- p.58 / ILLUSTRATIONS --- p.67 / APPENDICES --- p.79 / BIBLOGRAPHY --- p.83

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

交易员通常在处理大单交易时会遇到困难，因为市场没有足够的流动性来消化这些买单或卖单。交易员想要在对市场产生冲击最小的情况下完成加仓或平仓，或者他们想设计一套程序来达成这个目的。 / 由于每次的交易结果都是一个随机变量，为了方便比较，我们可以设置一个比较基准，在本文中我们选用。 / 本文对之前存在的动态一致性风险测度模型的一大改进是引入了动量效应。在短时的股市中动量效应就有明显效应。 / 我们的最优策略是当市场朝我们不利的方向变动时我们加速仓位的增加或减少，而朝我们有利的方向变动时我们减缓我们的动作。我们的最优策略每期都会出请或买入一个预先设定的比例的股票，同时我们会在交易的初期加快我们的买卖处理，而在后期放缓动作。 / 我们的最优策略是时间一致的，并且是一个动态变化的策略。 / For an equity trader, one problem he faces is to execute large order of stocks for his clients. The trader seeks to optimize his performance for buying and selling stocks. Basically various costs incurred during the trading includes the commission fees, margin loans, bid-ask spread, price impacts, taxes and other occasional costs. But among the all, the price impact takes the largest part. / In a sell program, the implementation shortfall is the differience between the value of the trader’s initial equity position and the sum of the cash flow he receives from his trading process. Because of the randomness inherited in the stock price process, the resulting implementation shortfall is a random variable, and we should project the random variable into real number to compare. The measure we choose is the dynamic coherent risk measure. / One of the most significant improvements of our model is the inclusion of momentum effect. Momentum is a significant effect when considering stock price dynamics in a daily circle. Another main contribution is the approximation method used in solving our model, which helps reduce much computation burden. / Our strategy applies best to the high frequency trading problem due to the nature of our approximation method. The optimal strategy in our framework is to trade more when the current price drift is negative. This is mainly due to the prevention from future possible negative price drifts. Our strategy also shows that, in addition to liquidate a fixed proportion of inventory at each period, the trader has to trade faster at earlier periods.Our optimal strategy derived from dynamic programming is time consistent and is an adapted process. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / He, Mengfei. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2013. / Includes bibliographical references (leaves 132-134). / Abstracts also in Chinese. / Abstract --- p.i / Acknowledgement --- p.iv / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Literature Review --- p.10 / Chapter 2.1 --- Model Comparison --- p.10 / Chapter 2.1.1 --- Price dynamics --- p.10 / Chapter 2.1.2 --- Price impacts --- p.11 / Chapter 2.1.3 --- Inventory constraints --- p.14 / Chapter 2.1.4 --- Objective functions and risk measures --- p.15 / Chapter 2.1.5 --- Discrete or continuous framework --- p.17 / Chapter 2.2 --- Work by Bertsimas and Lo --- p.18 / Chapter 2.2.1 --- Formulation under Linear Price Impact --- p.21 / Chapter 2.2.2 --- Formulation under LPT Law --- p.22 / Chapter 2.2.3 --- Formulation under General Price Impact --- p.26 / Chapter 2.2.4 --- Portfolio Case --- p.28 / Chapter 2.3 --- A Series ofWorks by Almgren --- p.29 / Chapter 2.3.1 --- Adaptive Arrival Price --- p.29 / Chapter 2.3.2 --- Bayesian Adaptive Trading with a Daily Cycle --- p.32 / Chapter 2.3.3 --- Mean-Variance Optimal Adaptive Execution --- p.36 / Chapter 2.4 --- Work by Lin and Pena --- p.42 / Chapter 2.4.1 --- Multiple Assets --- p.46 / Chapter 2.5 --- A Series ofWorks by Forsyth --- p.48 / Chapter 2.5.1 --- A Hamilton-Jacobi-Bellman Approach to Optimal Trade Execution --- p.49 / Chapter 2.5.2 --- A Mean Quadratic Variation Approach --- p.55 / Chapter 2.6 --- A Series ofWorks by Schied --- p.58 / Chapter 2.6.1 --- Optimal Trade Execution in Limit Order BookModels --- p.58 / Chapter 2.6.2 --- Optimal Trade Execution under Geometric BrownianMotion --- p.66 / Chapter 2.7 --- Work byMoazeni --- p.69 / Chapter 3 --- Model Setting --- p.71 / Chapter 3.1 --- ExecutionModel --- p.71 / Chapter 3.2 --- Coherent Dynamic RiskMeasures --- p.81 / Chapter 3.3 --- Optimization Formulation --- p.84 / Chapter 4 --- Solution Methodologies --- p.89 / Chapter 4.1 --- BinomialModel --- p.89 / Chapter 4.2 --- Linear Approximation --- p.92 / Chapter 4.3 --- Numerical Results --- p.107 / Chapter 4.4 --- Simulation Results --- p.110 / Chapter 4.5 --- Efficient Frontier --- p.111 / Chapter 4.6 --- CVaR Case --- p.113 / Chapter 5 --- Conclusions and Future Research --- p.119 / Chapter 5.1 --- Conclusions --- p.119 / Chapter 5.2 --- Future Research --- p.121 / Chapter A --- Equation Derivation --- p.124 / Bibliography --- p.132

Leung Lok-yee. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2003. / Includes bibliographical references (leaves 70-71). / Abstracts in English and Chinese. / Chapter 1. --- Introduction and Literature Review --- p.1 / Chapter 2. --- Methodology --- p.4 / Chapter A. --- Momentum Strategies / Chapter B. --- Relative Strength Indexes / Chapter 3. --- Data --- p.13 / Chapter 4. --- Emirical Findings --- p.15 / Chapter A. --- Momentum Strategies / Chapter B. --- Relative Strength Indexes / Chapter 5. --- Conclusion --- p.37 / Chapter 6. --- Tables --- p.39 / Chapter 7. --- Bibliograhy --- p.70

Siu, Tsz Hang. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (leaves 59-61). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgement --- p.iii / Chapter 1 --- Introduction and Literature Review --- p.1 / Chapter 2 --- Data and Methodology --- p.5 / Chapter 2.1 --- Portfolio Formation --- p.8 / Chapter 2.2 --- Delisting --- p.11 / Chapter 2.3 --- Rebalancing --- p.11 / Chapter 2.4 --- Performance Measurement --- p.12 / Chapter 3 --- Results --- p.16 / Chapter 3.1 --- Daily Portfolio Returns --- p.16 / Chapter 3.2 --- CAPM and Fama French Model --- p.18 / Chapter 3.3 --- Cumulative Returns --- p.22 / Chapter 3.4 --- Over Different Time Periods --- p.22 / Chapter 3.5 --- Analysis on Capital Market Theory --- p.24 / Chapter 3.6 --- Explanations --- p.27 / Chapter 3.6.1 --- Overconfidence --- p.27 / Chapter 3.6.2 --- Anchoring --- p.28 / Chapter 3.6.3 --- A Simple Model and Smoothing Effect --- p.29 / Chapter 3.6.4 --- Securities Selection --- p.32 / Chapter 3.6.5 --- Transaction Costs --- p.32 / Chapter 4 --- Conclusions --- p.33 / Chapter A --- Proof --- p.36 / Chapter B --- Tables and Figures --- p.40 / Bibliography --- p.59