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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.

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

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

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

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

This thesis is an investigation into the relationship that exists between macroeconomic variables and the pricing of common stock under trending market conditions. By introducing a dichotomous independent variable as a way of distinguishing between periods of rising and falling thereby attaching an additional expected premium to each of five accepted sources of macroeconomic risk for participation in ‘Bear’ markets. 228 observations of the fourteen industry sub-groupings of former TSE 300 were examined separately. The ultimate results were obtained using the Arbitrage Pricing Theory (APT) as the model to obtain factor exposures. The results show that there is no significant relationship between market trend and the pricing of common stock when the APT is applied. The final recommendation is that more research is needed.

In this thesis, extensive research regarding the relationship between macroeconomic variables and the stock market is carried out. For this purpose the two largest stock markets in the world, namely the US and Japan, are chosen. As a proxy for the US stock market we use the S&P500 and for Japan the Nikkei225. Although there are many empirical investigations of the US stock market, Japan has lagged behind. Especially the severe boom and bust sequence in Japan is unique in the developed world in recent economic history and it is important to shed more light on the causes of this development. First, we investigate the long-run relationship between selected macroeconomic variables and the stock market in a cointegration framework. As expected, we can support existing findings in the US, whereas Japan does not follow the same relationships as the US. Further econometric analysis reveals a structural break in Japan in the early 1990s. Before that break, the long-run relationship is comparable to the US, whereas after the break this relationship breaks down. We believe that a liquidity trap in a deflationary environment might have caused the normal relationship to break down. Secondly, we increase the variable set and apply a non-linear estimation technique to investigate non-linear behaviour between macroeconomic variables and the stock market. We find the non-linear models to have better in and out of sample performance than the appropriate linear models. Thirdly, we test a particular non-linear model of noise traders that interact with arbitrage traders in the dividend yield for the US and Japanese stock market. A two-regime switching model is supported with an inner random or momentum regime and an outer mean reversion regime. Overall, we recommend investors and policymakers to be aware that a liquidity trap in a deflationary environment could also cause severe downturn in the US if appropriate measures are not implemented accordingly.

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