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Abstract The purpose of this paper is to investigate the impact of foreign capital on the interrelationship between the stock markets and futures markets of Hong Kong, Malaysia and Taiwan. Malaysia stock market is under Exchange Control Mechanism, (ECM) while Taiwan futures market under foreign capital deregulation, both markets has extremely serious influence. The investment behavior of foreign capital, as superior informed investors, always imply their expectation to both stock and futures markets. Thus, this paper attempts to focus on three topics to analyze the investment behavior of the foreign capital. First, whether the degree of intervene of the foreign capital influences the lead-lag relationship. Second, whether after intervene of the foreign capital influence the lead-lag relationship, and third, whether the foreign capital net buying (selling) amount in the stock market influence the basis after deregulation of the Taiwan futures markets. This paper found that under over intervention on futures markets would restrained the stock index futures from price discovered, and after Taiwan futures markets deregulation, foreign capital net buying (selling) amount in the stock market does influence the basis. This study propose both Taiwan stock and futures markets exists foreign capital positive feedback trading.

The use of proxies in the CAPM model to determine assets expected return has implications for portfolio management. An inefficient proxy can result in the lowering of beta estimates due to a weak regression relationship resulting in the misallocation of capital. For the CAPM equation to be satisfied would require that the proxy should at least have an alpha that centred on zero over a period of time. This would allow the linearity of the model to hold and we would advocate a passive portfolio strategy. If the proxy were mean variance inefficient would indicate that alpha values are present in asset returns that can allow us to rebalance portfolios using optimisation techniques. We test the hypothesis that alpha averages around zero using the market model by regressing Industrial and Gold index excess returns on the market premium. When tested from the SA investor perspective we find that the alpha of the ALSI regression is not zero for the Gold Index but centred on zero for the Industrial Index. The implications are that SA investors would get a fair return holding the ALSI index instead of trade in industrial shares. The result warrants a passive strategy. However, portfolio optimisation demonstrates that a higher return can be achieved by rebalancing the portfolio The regression using the Gold index produced a negative alpha implying that investors should actively sell Gold shares from their portfolios. The ALSI was not an adequate proxy of risk to the SA investor for gold shares. Overall the ALSI is inefficient since it has a nonlinear relationship to one sector of the lSE. Portfolio analysis and rebalancing is required to attain an optimal return. The Markowitz model recommends that all SA investment capital should be fully weighted in the Industrial index only. Introducing an international investment proxied by the Dow Jones significantly improved the returns to SA investors. This is evident in the improved Sharpe ratio achieved by the rand adjusted Dow Jones available to the SA investor. In the absence of exchange restrictions the model recommends that 87% of local investors assets should be moved abroad under the present investment conditions. When tested from the US investor's perspective using dollar returns the data estimates achieved from the regression analysis were: The alpha value of the Industrial index is non-zero and the Gold index alpha centres on zero. The results are a reversal of the Rand tests of the SA investor. Gold shares priced fairly in dollar terms as opposed to Industrial shares. Currency effects of Rand depreciation priced into the dollar return of Industrial shares led to their non-participation in the US investors' portfolio. Due to trade of gold in dollars, the gold shares were priced to provide a fair return to the dollar-adjusted ALSI as opposed to the rand denominated test. Overall, the ALSI was inefficient due to the Industrial sector pricing in dollars resulting in abnormal alpha values over time. Currency depreciation resulted in the distortion ofthe CAPM relationship between the INDI and ALSI. The US investor's domestic index, the Dow Jones was found to lie on the efficiency frontier for tests using the ALSI and the INDI. There was no reason to invest in SA, but if the US investor did chose to invest in SA shares then gold had the lowest beta and the lowest correlation to the Dow Jones. The beta values of the SA indices were all significant and the alpha values were negative when regressed against the Dow Jones. The implication of this would be to invest as much as possible in the international index portfolio as possible. Regression Statistics ALSIXS I:\DIXS GOLDIXS P-values ntercept a 1.18E-05 0.001992 1.51 E-OS DOWJONES 9.87E-15 1.32E-11 5.27E-05. Coefficients intercept a -0.09833 -0.07281 -0.15206 DOWJONES 1.082276 0.985812 0.831916. The Dow Jones introduces a significant diversification benefit to the SA investor's portfolio by increasing returns significantly per unit of risk. The Markowitz model recommends that 87% of SA investor's portfolio should be in the Dow Jones and 13% in the Industrial index. Due to independent pricing of the gold and industrial sectors, the former by international markets in dollars and the latter in rands in SA, a dichotomy is created in the local market. From an SA investor's point of view the CAPM would not capture the correct return of gold shares. It would overstate the expected return since beta of the SA market premium will not include dollar returns. The ALSI is an incorrect proxy for the SA investor analysing gold shares. The Gold sector is only correctly priced from the US investor's perspective once the ALSI is dollar adjusted. The industrial index can use CAPM analysis reliably with the ALSI as market proxy but higher returns are achievable through portfolio rebalancing. Active portfolio management is recommended. Nevertheless, this will not produce results significantly different to the CAPM once standard errors of the mean are accounted for. The results found currency depreciation of the Rand as a major factor contributing to the exodus of SA capital. The dollar had an expected mean return of 12,6% p.a. This substantially increased the rand adjusted Sharpe ratio of the international portfolio compared to its dollar return. The increased Sharpe ratio of the rand denominated international portfolio resulted in a substantial shift of the optimal portfolios weighting away from the domestic portfolio and towards the Dow Jones. International investors optimal portfolios were similarly impeded due to the depreciating currency. / Thesis (MBA)-University of Natal, Durban, 2001.

Thesis (Ph. D.)--Northeastern University, 2008. / Title from title page (viewed Feb. 27, 2009). Graduate School of Arts and Sciences, Dept. of Chemistry and Chemical Biology. Includes bibliographical references (p. 156-158).

Thesis (Ph. D.)--Northeastern University, 2009. / Title from title page (viewed June 22, 2009). Graduate School of Arts and Sciences, Dept. of Chemistry and Chemical Biology. Includes bibliographical references (p. 199-204)

Thesis (M. Phil.)--University of Hong Kong, 1999.

No description available.

by Lee Yui. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1997. / Includes bibliographical references (leaves 70-72). / ACKNOWLEDGMENT --- p.i / ABSTRACT --- p.ii / LIST OF TABLES --- p.iii / LIST OF FIGURES --- p.iv / Chapter CHAPTER 1: --- INTRODUCTION --- p.1 / Chapter CHAPTER 2: --- BACKGROUND INFORMATION --- p.7 / Chapter 2.1 --- Stock Trading in Hong Kong --- p.7 / Chapter 2.1.1 --- History and Recent Trend --- p.8 / Chapter 2.1.2 --- Trading Mechanism of the Stock Exchange of Hong Kong --- p.11 / Chapter 2.1.3 --- Short Sale Restrictions --- p.12 / Chapter 2.1.4 --- Hang Seng Index --- p.14 / Chapter 2.2 --- Hang Seng Index Futures --- p.17 / Chapter 2.2.1 --- History and Recent Trend --- p.18 / Chapter 2.2.2 --- Trading and Settling Methods --- p.22 / Chapter CHAPTER 3: --- LITERATURE REVIEW --- p.24 / Chapter 3.1 --- Studies of Futures Market Efficiency based on Daily Data --- p.24 / Chapter 3.2 --- Studies of Futures Market Efficiency based on Intraday Data --- p.28 / Chapter CHAPTER 4: --- METHODOLOGY --- p.34 / Chapter 4.1 --- Index Futures Efficiency and Arbitrage Profitability --- p.34 / Chapter 4.2 --- Structure of Efficiency Tests --- p.36 / Chapter 4.2.1 --- Test based on Minute by Minute Reported Index --- p.36 / Chapter 4.2.2 --- Ex Post Test based on Transaction Prices of the Constitutent Stocks --- p.37 / Chapter 4.2.3 --- Ex Ante Test --- p.38 / Chapter 4.3 --- An Example for Illustration --- p.39 / Chapter 4.3.1 --- Results of the Efficiency Test based on Reported Index Quotations --- p.40 / Chapter 4.3.2 --- Results of the Ex Post Test based on Transaction Prices --- p.41 / Chapter 4.3.3 --- Results of Ex Ante Test --- p.42 / Chapter 4.4 --- Transaction Costs --- p.43 / Chapter CHAPTER 5: --- DATA AND PRELIMINARY STATISTICS --- p.46 / Chapter 5.1 --- Data from the Stock Market --- p.46 / Chapter 5.2 --- Data from the Futures Market and Money Market --- p.48 / Chapter CHAPTER 6: --- EMPIRICAL RESULTS --- p.49 / Chapter 6.1 --- Frequency of Ex Post Mispricings of Futures Prices --- p.49 / Chapter 6.2 --- Profitability of Hang Seng Index Arbitrage --- p.52 / Chapter 6.2.1 --- Results of Ex Ante Test with an Execution Lag of 30 Seconds --- p.52 / Chapter 6.2.2 --- Results of Ex Ante Test with an Execution Lag longer than 30 Seconds --- p.54 / Chapter 6.3 --- Comparison of Long Arbitrage Profitability and Short Arbitrage Profitability --- p.57 / Chapter 6.3.1 --- Comparison of Ex Post Violations between Long Arbitrage and Short Arbitrage --- p.58 / Chapter 6.3.2 --- Comparison of Ex Ante Profitability between Long Arbitrage and Short Arbitrage --- p.59 / Chapter CHAPTER 7: --- CONCLUSIONS --- p.65 / BIBLIOGRAPHY --- p.70

by Wan Chi-Keung. / Thesis (M.B.A.)--Chinese University of Hong Kong, 1997. / Includes bibliographical references (leaves 33-34). / TABLE OF CONTENTS / ABSTRACT --- p.ii / TABLE OF CONTENTS --- p.iii / LIST OF FIGURES --- p.iv / LIST OF TABLE --- p.v / ACKNOWLEDGEMENT --- p.vi / Chapter / Chapter I. --- INTRODUCTION --- p.1 / Chapter II. --- VOLATILITY SMILE --- p.4 / The Black- Scholes Model --- p.6 / The Implied Tree --- p.7 / The Implied Probability Distribution --- p.10 / Chapter III. --- LITERATURE REVIEW --- p.12 / Chapter IV. --- RECOVERING PROBABILITY DISTRIBUTIONS OF HSI --- p.18 / Shimko's Method --- p.19 / Data Selection --- p.22 / Probability Distributions of HSI --- p.23 / Chapter V. --- CONLUDING REMARKS --- p.27 / APPENDIX --- p.30 / BIBLIOGRAPHY --- p.33

This study examines the effect of the introduction of CSI300 Index Futures on the volatility of the stock market. Taking into account of the existence of the long term trend of diminishing volatility of the Chinese stock market, the difference-in-difference method was used instead of the simple before-and-after method to investigate how the volatility of the constituent stocks changes relative to the non-constituent stocks after the introduction of CSI300 Index Futures. Empirical results revealed that the volatility of the constituent stocks increased as compared with that of non-constituent stocks before and after the inception of the CSI300 Index Futures. The temporal-self comparison for the stocks entered or removed from the CSI300 Index List showed that that the introduction of index futures has a long-term destabilizing effect. / 本文研究滬深300股票指數期貨的推出對我國股票市場波動率的影響。考慮到中國股市長期波動率下降的趨勢的存在,我們用差上差的方法取代了傳統的簡單事前事後比較方法來研究成分股相對于非成分股波動率在滬深300股票指數期貨推出前後是如何變化的。實證結果顯示成分股股票相對于非成分股股票,波動率在滬深300股票指數期貨推出前後實際上是上升的。對於進入或者剔除出滬深300指數名單的股票的實證研究顯示,這種股票不同狀態的自我比較說明對於滬深300股票指數期貨的推出在長期有失穩作用。 / Luo, Shengjie. / Thesis M.Phil. Chinese University of Hong Kong 2014. / Includes bibliographical references (leaves 40-42). / Abstracts also in Chinese. / Title from PDF title page (viewed on 12, October, 2016). / Detailed summary in vernacular field only.