Dissertations / Theses on the topic 'Stocks Prices Australia Econometric models'

This study deals with the estimation of the optimal hedge ratios using various econometric models. Most of the recent papers have demonstrated that the conventional ordinary least squares (OLS) method of estimating constant hedge ratios is inappropriate, other more complicated models however seem to produce no more efficient hedge ratios. Using daily AOIs and SPI futures on the Australian market, optimal hedge ratios are calculated from four different models: the OLS regression model, the bivariate vector autoaggressive model (BVAR), the error-correction model (ECM) and the multivariate diagonal Vcc GARCH Model. The performance of each hedge ratio is then compared. The hedging effectiveness is measured in terms of ex-post and ex-ante risk-return traHe-off at various forcasting horizons. It is generally found that the GARCH time varying hedge ratios provide the greatest portfolio risk reduction, particularly for longer hedging horizons, but hey so not generate the highest portfolio return.

Following the important work on unit roots and cointegration which started in the mid-1980s, a great deal of econometric works has been devoted to the study of the subtleties and varieties of near nonstationarity and persistence that characterize so many economic and financial time series. In recent years research activity has gained importance with outstanding contributions made on estimation and testing of a wide variety of long memory processes, together with many interesting and imaginative applications over a wide variety of different fields of economics and finance. For these reasons, this study provides empirical evidence to an aspect of fractional differencing and long memory processes, or the long memory of volatility. Evidence of long memory persistence is explored using stock price indices for eight emerging economies in both Asian and Latin American markets. The concern with the presence of long memory in higher moments of return series was first drawn by Ding, Granger and Engle (1993), using asset returns. Baillie, Bollerslev and Mikkelsen (1996) developed the fractionally integrated GARCH, or FIGARCH, process to represent long memory in volatility. The measure of long-memory persistence in the volatility is employed either using the original rescaled range statistic by Hurst (1951) and its modified version proposed by Lo (1991). Further analysis of the presence of long memory persistence is conducted using autocorrelation analysis. All the findings point in the same direction, that is, the existence of long memory in volatility irrespective of the measure chosen. Estimation of different models of volatility is undertaken beginning with the ARCH specification and until the FIGARCH model. The results show the effects to be higher in Latin American countries than in the Asian ones. This result seems consistent with the degree of intervention in the Latin American markets, known to be much higher.
Other possible explanations for the occurrence of long term persistence are also pursued such as the Regime Switching modelisation proposed first by Hamilton and Susnel (1994) with the SWARCH approach. Results show that this approach can bring another possible explanation for persistence, specially in economies like Brazil that, have very different regimes for the period covered in this study.

[Truncated abstract] This thesis examines competing asset-pricing models in Australia with the goal of establishing the model which best explains cross-sectional stock returns. The research employs Australian equity data over the period 1980-2001, with the major analyses covering the more recent period 1990-2001. The study first documents that existing asset-pricing models namely the capital asset pricing model (CAPM) and domestic Fama-French three-factor model fail to meet the widely applied Merton?s zero-intercept criterion for a well-specified pricing model. This study instead documents that the US three-factor model provides the best description of Australian stock returns. The three US Fama-French factors are statistically significant for the majority of portfolios consisting of large stocks. However, no significant coefficients are found for portfolios in the smallest size quintile. This result initially suggests that the largest firms in the Australian market are globally integrated with the US market while the smallest firms are not. Therefore, the evidence at this point implies domestic segmentation in the Australian market. This is an unsatisfying outcome, considering that the goal of this research is to establish the pricing model that best describes portfolio returns. Given pervasive evidence that liquidity is strongly related to stock returns, the second part of the major analyses derives and incorporates this potentially priced factor to the specified pricing models ... This study also introduces a methodology for individual security analysis, which implements the portfolio analysis, in this part of analyses. The technique makes use of visual impressions conveyed by the histogram plots of coefficients' p-values. A statistically significant coefficient will have its p-values concentrated at below a 5% level of significance; a histogram of p-values will not have a uniform distribution ... The final stage of this study employs daily return data as an examination of what is indeed the best pricing model as well as to provide a robustness check on monthly return results. The daily result indicates that all three US Fama-French factors, namely the US market, size and book-to-market factors as well as LIQT are statistically significant, while the Australian three-factor model only exhibits one significant market factor. This study has discovered that it is in fact the US three-factor model with LIQT and not the domestic model, which qualifies for the criterion of a well-specified asset-pricing model and that it best describes Australian stock returns.

This three year indepth study was prompted after a decade of working as a corporate advisor for numerous stockbroking firms' corporate advisory and listing divisions. An overwhelming lack of discernible pricing methodology for IPOs on the JSE's Main Board and failed Venture Capital and Development Capital Markets was transferred to the new Alternative Exchange (AltX). This prompted lengthly discussions with former head of JSE's AltX Noah Greenhill. Such discussions are set out in this dissertation and relate to pricing methodologies and the lack of guidance or legislation as set out in the JSE's schedule 21 of Listing requirements. The focus of this dissertation is thus centred on whether the current adopted methodologies to establish a fair and reasonable pre-IPO share price is effective. To achieve this, global pricing methodologies were assessed within the framework of various valuation techniques used by South African Designated Advisors.

This thesis investigates implications of interdependence between stock market prices in the context of several financial applications including: portfolio selection, tests of market efficiency and measuring the extent of integration among national stock markets. In Chapter 2, I note that volatility spillovers (transmissions of risk) have been found in numerous empirical studies but that no one, to my knowledge, has evaluated their effects in the general portfolio framework. I dynamically forecast two multivariate GARCH models, one that accounts for volatility spillovers and one that does not, and construct optimal mean-variance portfolios using these two alternative models. I show that accounting for volatility spillovers lowers portfolio risk with statistical significance and that risk-averse investors would prefer realised returns from portfolios based on the volatility spillover model. In Chapter 3, I develop a structural MGARCH model that parsimoniously specifies the conditional covariance matrix and provides an identification framework. Using the model to investigate interdependencies between size-sorted portfolios from the Australian Stock Exchange, I gain new insights into the issue of asymmetric dependence. My findings not only confirm the observation that small stocks partially adjust to market-wide news embedded in the returns to large firms but also present evidence that suggests that small firms in Australia fail to even partially adjust (with statistical significance) to large firms??? shocks contemporaneously. All adjustments in small capitalisation stocks occur with a lag. Chapter 4 uses intra-daily data and develops a new method for measuring the extent of stock market integration that takes into account non-instantaneous adjustments to overnight news. This approach establishes the amounts of time that the New York, Tokyo and London stock markets take to fully adjust to overnight news and then uses this This thesis investigates implications of interdependence between stock market prices in the context of several financial applications including: portfolio selection, tests of market efficiency and measuring the extent of integration among national stock markets. In Chapter 2, I note that volatility spillovers (transmissions of risk) have been found in numerous empirical studies but that no one, to my knowledge, has evaluated their effects in the general portfolio framework. I dynamically forecast two multivariate GARCH models, one that accounts for volatility spillovers and one that does not, and construct optimal mean-variance portfolios using these two alternative models. I show that accounting for volatility spillovers lowers portfolio risk with statistical significance and that risk-averse investors would prefer realised returns from portfolios based on the volatility spillover model. In Chapter 3, I develop a structural MGARCH model that parsimoniously specifies the conditional covariance matrix and provides an identification framework. Using the model to investigate interdependencies between size-sorted portfolios from the Australian Stock Exchange, I gain new insights into the issue of asymmetric dependence. My findings not only confirm the observation that small stocks partially adjust to market-wide news embedded in the returns to large firms but also present evidence that suggests that small firms in Australia fail to even partially adjust (with statistical significance) to large firms??? shocks contemporaneously. All adjustments in small capitalisation stocks occur with a lag. Chapter 4 uses intra-daily data and develops a new method for measuring the extent of stock market integration that takes into account non-instantaneous adjustments to overnight news. This approach establishes the amounts of time that the New York, Tokyo and London stock markets take to fully adjust to overnight news and then uses this

Stock return volatility has been shown to occasionally exhibit discrete structural shifts. These shifts are particularly evident in the transition from ‘normal’ to crisis periods, and tend to be more pronounced in developing markets. This study aims to establish whether accounting for structural changes in the conditional variance process, through the use of Markov-switching models, improves estimates and forecasts of stock return volatility over those of the more conventional single-state (G)ARCH models, within and across selected African markets for the period 2002-2012. In the univariate portion of the study, the performances of various Markov-switching models are tested against a single-state benchmark model through the use of in-sample goodness-of-fit and predictive ability measures. In the multivariate context, the single-state and Markov-switching models are comparatively assessed according to their usefulness in constructing optimal stock portfolios. It is found that, even after accounting for structural breaks in the conditional variance process, conventional GARCH effects remain important to capturing the heteroscedasticity evident in the data. However, those univariate models which include a GARCH term are shown to perform comparatively poorly when used for forecasting purposes. Additionally, in the multivariate study, the use of Markov-switching variance-covariance estimates improves risk-adjusted portfolio returns when compared to portfolios that are constructed using the more conventional single-state models. While there is evidence that the use of some Markov-switching models can result in better forecasts and higher risk-adjusted returns than those models which include GARCH effects, the inability of the simpler Markov-switching models to fully capture the heteroscedasticity in the data remains problematic.

This research questions whether technical trading rules can help predict stock price movements for a sample of stocks selected from four equity markets from the Asia-Pacific region: Australia, Malaysia, Hong Kong and Thailand for the period 1989-2008. The research is split into two stages. Stage-1 of the research tests the predictability of technical trading rules against a buyand- hold strategy. The variable moving average (VMA), fixed moving average (FMA) and the trading range break (TRB) trading rules are applied to this research. Economic predictability of these rules is examined by comparing returns conditional on a trading rule buy (sell) signal against an unconditional buy-and-hold return. Any existence of excess returns can thus be established. This follows with a statistical analysis of returns using a traditional t-test methodology. Traditional statistical tests assume normally distributed returns with independent observations and a non-changing distribution across time. In Stage-2 of this research a bootstrap checks whether features such as non-normality, time-varying moments and serial correlation bias test statistics. The bootstrap involves assumptions regarding the underlying returns generating process (RGP) and allows returns conditional on a trading rule buy (sell) signal from the original stock price series to be compared with conditional returns simulated from four common null models: RW, AR (1), GARCH-M and E-GARCH models. Simulated p-values are calculated in conjunction with simulated distributions and are applied in lieu of the theoretical normal distribution. Given this process it is possible to infer as to whether non-linear dependencies in returns can be captured by any of the three trading rules. Given the null model output standard t-test outcomes of predictability of technical trading rules may be diminished and/or eliminated. Conclusions are drawn as to the predictability and profitability of the VMA, FMA and TRB trading rules when applied to the chosen stock samples. Findings of this research indicate returns conditional on technical trading rules exceed unconditional buy-and-hold returns for all stocks. Thai sample output indicates strong support in favour of the predictability of standard test results supporting the use of technical trading rules. Output for Australia, Hong Kong and Malaysia indicates that previous standard t-test outcomes of predictability may be diminished and/or eliminated. This implies that the underlying RGP may be characterised by underlying features of some/all of the stochastic models.

In 1993, Kenya liberalised its trade policy and allowed the Kenyan Shillings to freely float. This openness has left Kenya's domestic prices vulnerable to the effects of exchange rate fluctuations. One of the objectives of the Central Bank of Kenya is to maintain inflation levels at sustainable levels. Thus it has become necessary to determine the influence that exchange rate changes have on domestic prices given that one of the major determinants of inflation is exchange rate movements. For this reason, this thesis examines the magnitude and speed of exchange rate pass-through (ERPT) to domestic prices in Kenya. In addition, it takes into account the direction and size of changes in the exchange rates to determine whether the exchange rate fluctuations are symmetric or asymmetric. The thesis uses quarterly data ranging from 1993:Ql - 2008:Q4 as it takes into account the period when the process of liberalization occurred. The empirical estimation was done in two stages. The first stage was estimated using the Johansen (1991) and (1995) co integration techniques and a vector error correction model (VECM). The second stage entailed estimating the impulse response and variance decomposition functions as well as conducting block exogeneity Wald tests. In determining the asymmetric aspect of the analysis, the study followed Pollard and Coughlin (2004) and Webber (2000) frameworks in analysing asymmetry with respect to appreciation and depreciation and large and small changes in the exchange rate to import prices. The results obtained showed that ERPT to Kenya is incomplete but relatively low at about 36 percent in the long run. In terms of asymmetry, the results showed that ERPT is found to be higher in periods of appreciation than depreciation. This is in support of market share and binding quantity constraints theory. In relation to size changes, the results show that size changes have no significant impact on ERPT in Kenya.

The aim of this thesis is to estimate the volatility function of continuoustime stochastic models. The estimation of the volatility of the following wellknown international stock market indexes is presented as an application: Dow Jones Industrial Average, Standard and Poor’s 500, NIKKEI 225, CAC 40, DAX 30, FTSE 100 and IBEX 35. This estimation is studied from two different perspectives: a) assuming that the volatility of the stock market indexes displays shortrange dependence (SRD), and b) extending the previous model for processes with longrange dependence (LRD), intermediaterange dependence (IRD) or SRD. Under the efficient market hypothesis (EMH), the compatibility of the Vasicek, the CIR, the Anh and Gao, and the CKLS models with the stock market indexes is being tested. Nonparametric techniques are presented to test the affinity of these parametric volatility functions with the volatility observed from the data. Under the assumption of possible statistical patterns in the volatility process, a new estimation procedure based on the Whittle estimation is proposed. This procedure is theoretically and empirically proven. In addition, its application to the stock market indexes provides interesting results.

Thesis (MBA) -- University of New Brunswick, Faculty of Administration, 2003.
Typescript. Bibliography: leaves 83-84. Also available online through University of New Brunswick, UNB Electronic Theses & Dissertations.

This dissertation explores different aspects of the interaction between money and asset prices. The first chapter investigates how a firm’s financing affects its decision to update prices: does linking interest rates to inflation alter the firm’s optimal price updating strategy? Building on the state dependent pricing models of Willis (2000) and the price indexing literature of Azariadis and Cooper (1985) and Freeman and Tabellini (1998), this model investigates the financing and price updating decisions of a representative firm facing state-dependent pricing and a cash-in-advance constraint. The model shows the circumstances under which a firm’s financing decision affects its price updating decision, and how the likelihood of changing prices affects the amount borrowed. It also illustrates how the use of nominal (as opposed to inflation-linked) interest rates leads to a lower frequency of price updating and higher profits overall for a firm facing menu costs and sticky prices. The second chapter extends the bank run literature to present a theoretical mechanism that explains how money supply can affect asset prices and asset price volatility. In a two period asset allocation model, agents faced with uncertainty cannot perfectly allocate assets ex-ante. After income shocks are revealed, they will be willing to pay a premium over the future fundamental value for an asset in order to consume in the current period. The size of this premium is directly affected by the supply of money relative to the asset. This paper explores the relationship between economy-wide monetary liquidity on the mean and variance of equity returns and in relation to market liquidity. At an index level, I test the impact of money-based liquidity measures against existing measures of market liquidity. I proceed to do a stock level analysis of liquidity following Pastor and Stambaugh (2003). The results indicated that measures of aggregate money supply are able to match several of the observed relationships in stock return data much better than market liquidity. At an individual stock level, monetary liquidity is a priced factor for individual stocks. Taken together, these papers support the idea that changes in the money supply have consequences for the real economy.
text

Cheung Ho Sang.
Thesis (M.Phil.)--Chinese University of Hong Kong, 2004.
Includes bibliographical references (leaves 185-187).
Abstracts in English and Chinese.
Curriculum Vitae --- p.ii
Acknowledgments --- p.iii
Abstract --- p.v
Table of Contents --- p.viii
Chapter Chapter 1. --- Introduction --- p.1
Chapter Chapter 2. --- The behavior of income velocity of money --- p.3
Chapter 2.1 --- Introduction --- p.3
Chapter 2.2 --- Literature Review --- p.4
Chapter 2.3 --- Data Description --- p.9
Chapter 2.4 --- Methodology --- p.9
Chapter 2.5 --- Empirical Result --- p.16
Chapter 2.6 --- Conclusion --- p.26
Chapter Chapter 3. --- The behavior of equity premium --- p.106
Chapter 3.1 --- Introduction --- p.106
Chapter 3.1 --- Literature Review --- p.106
Chapter 3.2 --- Data Description --- p.112
Chapter 3.3 --- Methodology --- p.112
Chapter 3.4 --- Empirical Result --- p.120
Chapter 3.5 --- Conclusion --- p.130
Data Appendices --- p.182
Bibliography --- p.185

Chen Haiqiang.
Thesis (M.Phil.)--Chinese University of Hong Kong, 2005.
Includes bibliographical references (leaves 33-35).
Abstracts in English and Chinese.
Chapter 1. --- Introduction --- p.1
Chapter 2. --- The Model --- p.4
Chapter 3. --- Least Squares Estimations --- p.6
Chapter 4. --- Inference --- p.7
Chapter 4.1 --- Asymptotic Joint Distribution of the Threshold Estimators --- p.7
Chapter 4.2 --- Testing Threshold Effect: Model Selection Followed by Testing --- p.13
Chapter 5. --- Modeling --- p.16
Chapter 5.1 --- Generic Consistency of the Threshold Estimators under specification errors --- p.17
Chapter 5.2 --- Modeling Procedure --- p.20
Chapter 6. --- Monte Carlo Simulations --- p.21
Chapter 7. --- Empirical Application in the Financial Market --- p.24
Chapter 7.1 --- Data Description --- p.26
Chapter 7.2 --- Estimated Results --- p.26
Chapter 8. --- Conclusion --- p.30
References --- p.33
Appendix 1: Proof of theorem1 --- p.36
Appendix 2: Proof of theorem2 --- p.39
Appendix 3: Proof of theorem3 --- p.43
List of Graph --- p.49

Su Qian.
Thesis (M.Phil.)--Chinese University of Hong Kong, 2005.
Includes bibliographical references (leaves 66-70).
Abstracts in English and Chinese.
Abstract --- p."i,ii"
Acknowledgements --- p.iii
Table of Content --- p.iv
List of Tables and Figures --- p.v
List of Abbreviation --- p.vi
Chapter Chapter 1. --- Introduction --- p.1
Chapter Chapter 2. --- Literature Review --- p.4
Chapter 2.1 --- Benefits of Cross-listing --- p.4
Chapter 2.2 --- The Price-discovery process of cross-listed stocks --- p.8
Chapter 2.3 --- Previous studies on Chinese cross-listed stocks --- p.2
Chapter Chapter 3. --- China Overseas Listing --- p.15
Chapter 3.1 --- The history of overseas listing --- p.15
Chapter 3.2 --- Methods of overseas listing --- p.17
Chapter 3.3 --- The motivation for Chinese firms to list overseas --- p.18
Chapter 3.4 --- The prospects of China Overseas listing --- p.21
Chapter Chapter 4. --- Price-discovery contributions to China-backed stocks cross-listed on SEHK and NYSE --- p.23
Chapter 4.1 --- Data --- p.23
Chapter 4.2 --- Methodology --- p.25
Chapter 4.3 --- Empirical Results and Interpretation --- p.31
Chapter 4.4 --- Cross-Sectional analysis of NYSE contributions to the price-discovery process --- p.40
Chapter Chapter 5. --- Price-discovery contributions to the cross-listed H share and A share --- p.45
Chapter 5.1 --- Data and Sample details --- p.46
Chapter 5.2 --- Methodology --- p.49
Chapter 5.3 --- Empirical results and interpretation --- p.54
Chapter 5.4 --- A brief analysis of cointegration determinants --- p.57
Chapter 5.5 --- The cointegration between H share and A share- Daily analysis --- p.61
Chapter Chapter 6. --- Conclusion --- p.64
Reference --- p.66
Tables --- p.71

This Paper empirically investigates the behavior of Africa’s stock price volatility over time in ten African equity markets. It also attempts to establish the existence of a relationship between volatility and expected returns in the chosen equity markets. The effect of volatility on the stock prices is also investigated, together with establishing variations in the stock return volatility risk premia. Lastly, an investigation of whether volatility is transmitted from international markets to African markets is also undertaken. The sample period starts from November 1998 until December 2016. The preliminary empirical results show a mixed finding in the mean-variance tradeoff theory. Based on the GARCH-type models, the empirical results show that volatility of stock returns show the characteristics of volatility clustering, leptokurtic distribution and leverage effects over time for all the Africa equity markets. A weak relationship between volatility and expected returns is also found in all the African equity markets studied. The results also showed that as volatility increases, the returns correspondingly decrease by a factor of the coefficient for most of the equity markets. These results negate the theory of a positive risk premium on stock indices. It was also observed that stock return volatility risk premia have variations over time. The study also established that there was volatility transmission from the international markets into Africa equity markets.
MT2017

by Poon Yeuk Wan, Tsang Fei.
Thesis (M.B.A.)--Chinese University of Hong Kong, 1998.
Includes bibliographical references (leaves 54-55).
Acknowledgements --- p.i
Abstract --- p.iii
Table of Contents --- p.iv
List of Tables --- p.vi
List of Appendix --- p.vii
Chapter Chapter1 --- Introduction --- p.1
Chapter 1.1 --- Project Objective --- p.1
Chapter 1.2 --- Project Structure --- p.2
Chapter 1.3 --- Data --- p.3
Chapter Chapter 2 --- Emerging Markets´ؤ-An Overview --- p.5
Chapter 2.1 --- Latin America --- p.5
Argentina --- p.5
Brazil --- p.7
Chile --- p.7
Colombia --- p.8
Mexico --- p.8
Peru --- p.9
Venezuela --- p.9
Chapter 2.2 --- Eastern Europe --- p.10
Czech Republic --- p.10
Poland --- p.10
Slovakia --- p.11
Hungary --- p.11
Russia --- p.11
Chapter 2.3 --- Middle East --- p.12
Israel --- p.12
Jordan --- p.12
Chapter 2.4 --- Implication For Further Analysis --- p.13
Chapter Chapter 3 --- Analysis and Findings I: Descriptive Statistics Analysis --- p.14
Chapter 3.1 --- Objective of Descriptive Statistic Analysis --- p.14
Chapter 3.2 --- Findings --- p.16
Eastern Europe --- p.16
Latin America --- p.16
Middle East --- p.17
Chapter 3.3 --- Conclusion --- p.18
Chapter Chapter 4 --- Analysis and Findings II: Day-of-the- Week (Monday effect) Test --- p.19
Chapter 4.1 --- Objective --- p.19
Chapter 4.2 --- Literature Review --- p.19
Chapter 4.3 --- Methodology --- p.21
Chapter 4.4 --- Data --- p.23
Chapter 4.5 --- Analysis --- p.24
Chapter 4.6 --- Empirical findings --- p.25
Chapter I. --- The equality of return test --- p.25
Eastern Europe --- p.26
Latin America --- p.26
Middle East --- p.26
Overall --- p.27
Local currency versus US currency --- p.27
Chapter II. --- Comparison of Monday return with returns of other days within the week --- p.27
Chapter l. --- Without exchange rate effect --- p.28
Chapter 4.7 --- Monday effect一-an overview --- p.31
Comparison by region --- p.31
Eastern Europe --- p.31
Latin America --- p.31
Middle East --- p.32
The effect of exchange rate --- p.32
Chapter Chapter 5 --- Analysis And Findings III: Correlation Analysis --- p.33
Chapter 5.1 --- Literature Review --- p.33
Chapter 5.2 --- Objective --- p.35
Chapter 5.3 --- Methodology --- p.35
Chapter 5.4 --- Findings --- p.38
Chapter I --- Correlations Within Regions --- p.38
Eastern Europe --- p.33
Latin America --- p.40
Middle East --- p.42
Chapter II. --- Correlation Among Regions --- p.43
Eastern Europe vs. Latin America --- p.43
Latin America vs. Middle East --- p.44
Eastern Europe vs. Middle East --- p.45
Chapter III. --- Correlations with the United States --- p.46
US vs. Eastern Europe --- p.46
US vs. Latin America --- p.46
US vs. Middle East --- p.47
Chapter 5.5 --- Conclusion --- p.43
Chapter Chapter 6 --- Conclusions and Implications --- p.49
Implications on market integration --- p.52
BIBLIOGRAPHY --- p.54
APPENDIX --- p.56

by Chiu Mei-Yee, Pamela, Pong Kwok-Hung, Patrick.
Thesis (M.B.A.)--Chinese University of Hong Kong, 1998.
Includes bibliographical references (leaf 52).
ABSTRACT --- p.ii
TABLE OF CONTENT --- p.iii
LIST OF ILLUSTRATIONS --- p.iv
LIST OF TABLES --- p.v
ACKNOWLEGEMENTS --- p.vi
Chapter
Chapter I. --- INTRODUCTION --- p.1
Chapter II. --- OBJECTIVES --- p.3
Chapter III. --- LITERATURE REVIEW --- p.4
Chapter IV. --- THE SAMPLE --- p.9
Chapter V. --- METHODOLOGY --- p.14
The Market Model --- p.15
Methods to Estimate the Excess Returns --- p.16
Chapter VI. --- RESULTS AND ANALYSIS --- p.19
Price Effects on Inclusion in HSI --- p.19
Price Effects on Exclusion from HSI --- p.33
Comparison between Inclusion and Exclusion --- p.41
Chapter VII. --- IMPLICATIONS --- p.42
Chapter VIII. --- CONCLUSION --- p.45
APPENDIX --- p.47
BIBLIOGRAPHY --- p.52