China's rapid economic growth and the development of its domestic stock market have attracted considerable attention from foreign investors. China's economic financial expansion, however, has emerged from an environment of state planning and radical socialist ideology. With a view of providing investors with a better understanding of the risk and return relationship in the Chinese A-share market over the past decade, this thesis adapts several empirical models to the circumstances in China and conducts four empirical analyses. First, in order to rationalize foreign investors' entry into the A-share market, the thesis compares the diversification benefits in three China-related stock markets, namely the A-share, the B-share and the H-share markets in a mean-variance framework using daily, weekly and monthly data respectively. The results suggest that of the three stock markets, the B-share market generates the highest average annual returns while the A-share market has the most significant diversification benefits regardless of whether the analysis is undertaken implementing a traditional mean-variance framework or a downside risk framework. Next, an empirical analysis using the Fama and MacBeth two-pass procedure is undertaken to test the relationship between beta, firm factors and stock returns. Similar to the findings in other stock markets, the results of this analysis show that the static betas for individual stocks fail to capture variation in stock returns in the A-share market. In contrast, the effects of book-to-market and trading volume are significant in the sample period. However, the fact that none of these factors have a persistent role in explaining stock returns suggests a possible change in the investment philosophy of Chinese domestic investors over the past decade. In the third analysis, two global betas are incorporated into the cross-sectional regressions in a bid to examine the integration or segmentation of the A-share market with the world and Hong Kong stock markets. Specifically, both time-varying betas and static betas are used in the analysis. The results suggest that there is no beta effect and the A-share marke t is totally segmented from both the world and Hong Kong stock markets. Finally, when the segmentation and integration status of the A-share market is further examined using the Maximum Likelihood Estimation framework without beta estimation and the assumption of a linear relationship between beta and stock returns, the findings suggest that the A-share market is becoming increasing integrated with the B-share and the Hong Kong stock markets.

China's rapid economic growth and the development of its domestic stock market have attracted considerable attention from foreign investors. China's economic financial expansion, however, has emerged from an environment of state planning and radical socialist ideology. With a view of providing investors with a better understanding of the risk and return relationship in the Chinese A-share market over the past decade, this thesis adapts several empirical models to the circumstances in China and conducts four empirical analyses. First, in order to rationalize foreign investors' entry into the A-share market, the thesis compares the diversification benefits in three China-related stock markets, namely the A-share, the B-share and the H-share markets in a mean-variance framework using daily, weekly and monthly data respectively. The results suggest that of the three stock markets, the B-share market generates the highest average annual returns while the A-share market has the most significant diversification benefits regardless of whether the analysis is undertaken implementing a traditional mean-variance framework or a downside risk framework. Next, an empirical analysis using the Fama and MacBeth two-pass procedure is undertaken to test the relationship between beta, firm factors and stock returns. Similar to the findings in other stock markets, the results of this analysis show that the static betas for individual stocks fail to capture variation in stock returns in the A-share market. In contrast, the effects of book-to-market and trading volume are significant in the sample period. However, the fact that none of these factors have a persistent role in explaining stock returns suggests a possible change in the investment philosophy of Chinese domestic investors over the past decade. In the third analysis, two global betas are incorporated into the cross-sectional regressions in a bid to examine the integration or segmentation of the A-share market with the world and Hong Kong stock markets. Specifically, both time-varying betas and static betas are used in the analysis. The results suggest that there is no beta effect and the A-share marke t is totally segmented from both the world and Hong Kong stock markets. Finally, when the segmentation and integration status of the A-share market is further examined using the Maximum Likelihood Estimation framework without beta estimation and the assumption of a linear relationship between beta and stock returns, the findings suggest that the A-share market is becoming increasing integrated with the B-share and the Hong Kong stock markets.

<p>In today’s competitive environment, companies compete for the same customers. Therefore, it is important to be able to satisfy the ever changing needs of customers. Companies can satisfy customer demand by learning about the customer and by alternating offerings in accordance to changing needs. These are actions undertaken by market driven companies. Alternatively, market driving companies satisfy customer demand by being creative and by focusing on customers’ future needs, an action which implies educating customers. However, there are also companies which pursue both of these strategies simultaneously. The purpose of this dissertation is to examine how companies implement a dual-market strategy, and how the strategy is incorporated into the business. Based on literature on closely related research fields, a framework is developed. This framework suggests that certain components influence a dual-market strategy. A study is conducted on the luxury fashion company Burberry. Through semi-structured interviews with employees at Burberry, this study investigates how the company’s use of a dual-market strategy affects the organisational culture and vision. The results indicate that the phenomenon of duality is noticeable in the company’s culture and vision. Due to the lack of research on a dual-market strategy, this study attempts to provide a deeper understanding of the phenomenon of duality. Companies can use the conclusions drawn from this study, as guidelines for how to pursue a dual-market strategy. However, more research is necessary before any generalisations can be made.</p>

In today’s competitive environment, companies compete for the same customers. Therefore, it is important to be able to satisfy the ever changing needs of customers. Companies can satisfy customer demand by learning about the customer and by alternating offerings in accordance to changing needs. These are actions undertaken by market driven companies. Alternatively, market driving companies satisfy customer demand by being creative and by focusing on customers’ future needs, an action which implies educating customers. However, there are also companies which pursue both of these strategies simultaneously. The purpose of this dissertation is to examine how companies implement a dual-market strategy, and how the strategy is incorporated into the business. Based on literature on closely related research fields, a framework is developed. This framework suggests that certain components influence a dual-market strategy. A study is conducted on the luxury fashion company Burberry. Through semi-structured interviews with employees at Burberry, this study investigates how the company’s use of a dual-market strategy affects the organisational culture and vision. The results indicate that the phenomenon of duality is noticeable in the company’s culture and vision. Due to the lack of research on a dual-market strategy, this study attempts to provide a deeper understanding of the phenomenon of duality. Companies can use the conclusions drawn from this study, as guidelines for how to pursue a dual-market strategy. However, more research is necessary before any generalisations can be made.

Under deregulated electric market, electricity price is no longer set by the monopoly utility company rather it responds to the market and operating conditions. Offering the right amount of electricity at the right time with the right bidding price has become the key for utility companies pursuing maximum profits under deregulated electricity market. Therefore, electricity market clearing price (MCP) forecasting became essential for decision making, scheduling and bidding strategy planning purposes. However, forecasting electricity MCP is a very difficult problem due to uncertainties associated with input variables.<p> Neural network based approach promises to be an effective forecasting tool in an environment with high degree of non-linearity and uncertainty. Although there are several techniques available for short-term MCP forecasting, very little has been done to do mid-term MCP forecasting. Two new artificial neural networks have been proposed and reported in this thesis that can be utilized to forecast mid-term daily peak and mid-term hourly electricity MCP. The proposed neural networks can simulate the electricity MCP with electricity hourly demand, electricity daily peak demand, natural gas price and precipitation as input variables. Two situations have been considered; electricity MCP forecasting under real deregulated electric market and electricity MCP forecasting under deregulated electric market with perfect competition. The PJM interconnect system has been utilized for numerical results. Techniques have been developed to overcome difficulties in training the neural network and improve the training results.

No description available.

Under deregulated electric market, electricity price is no longer set by the monopoly utility company rather it responds to the market and operating conditions. Offering the right amount of electricity at the right time with the right bidding price has become the key for utility companies pursuing maximum profits under deregulated electricity market. Therefore, electricity market clearing price (MCP) forecasting became essential for decision making, scheduling and bidding strategy planning purposes. However, forecasting electricity MCP is a very difficult problem due to uncertainties associated with input variables.<p> Neural network based approach promises to be an effective forecasting tool in an environment with high degree of non-linearity and uncertainty. Although there are several techniques available for short-term MCP forecasting, very little has been done to do mid-term MCP forecasting. Two new artificial neural networks have been proposed and reported in this thesis that can be utilized to forecast mid-term daily peak and mid-term hourly electricity MCP. The proposed neural networks can simulate the electricity MCP with electricity hourly demand, electricity daily peak demand, natural gas price and precipitation as input variables. Two situations have been considered; electricity MCP forecasting under real deregulated electric market and electricity MCP forecasting under deregulated electric market with perfect competition. The PJM interconnect system has been utilized for numerical results. Techniques have been developed to overcome difficulties in training the neural network and improve the training results.

As the two main components of household portfolios, stocks and real estate are likely to catch people¡¦s attention. Although the number of extant studies on the interaction between the stock and real estate markets is large, the views and empirical evidence in those studies show inconsistent results. This dissertation provides an explanation for the inconsistent results: market imperfection. Employing the threshold vector error correction model to examine the interaction between Taiwan¡¦s stock and real estate markets during the period from 1973Q2 to 2009Q4, the empirical results support this explanation. When the transaction benefit from the disequilibrium between the stock and real estate markets can cover the potential cost resulting from market imperfection, the relationship between the stock and real estate markets is integrated; but when there is slight disequilibrium, the price of real estate will not converge since the arbitrage benefit cannot cover the cost of transaction. As a result, the relationship is segmented. The empirical results of the study are very robust as similar conclusions result when different proxies for housing prices are used. The interactions between the stock and the sub-region housing markets also show similar results. Finally, when macroeconomic factors are considered, the asymmetric dynamic relationship is still significant.

Under digital convergence, the market structure has changed which cause the traditional market definition is no longer applicable. Many industries and firms have take action of cross-industry M&A and integration. In contrast, regulations and ¡§new¡¨ market definition has not appeared which cause antitrust authorities deal with the case of the M&A under digital convergence has no quantitative tools. Our study has found that the market structure under digital convergence almost is two-sided market and multi-sided market, so we use the modified Critical Loss Analysis which Evans and Noel (2008) proposed to be the market definition tool under digital convergence. Subsequently, we use the merger case of TFN media and Kbro to do empirical analysis. By the empirical results, we find out that the relevant market of cable TV has to expand. The IPTV and online play will be the competitive product that the market structure of cable TV will be changed radically. Under digital convergence, market definition may not precisely than traditional, but it still could provide antitrust authorities an effective quantitative evidence, and with the economic theory of qualitative analysis which could make policy analysis more integrity.

Thesis (Ph. D.)--University of California, San Diego, 2009. / Title from first page of PDF file (viewed October 22, 2009). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 161-170).