Although widely used, both the Markowitz model and VAR (Value at Risk) model have some limitations in evaluating the risk and return of stock investment. By the analysis of the conceptions of risk and return, together...Although widely used, both the Markowitz model and VAR (Value at Risk) model have some limitations in evaluating the risk and return of stock investment. By the analysis of the conceptions of risk and return, together with the three hypotheses of technological analysis, a novelty model of metering and evaluating the risk and return of stock investment is established. The major indicator of this model , risk-return ratio K, combines the characteristic indicators of risk and return. Regardless of the form of the risk-return probability density functions, this indicator K can always reflect the risk-return performances of the invested stocks clearly and accurately. How to use the model to make optimum investment and how to make portfolio combined with clustering analysis is also explained.展开更多
This study investigates annual earnings analysis with ARIMA （Autoregressive Integrated Moving Average） for future earnings prediction. Earnings prediction is very important to be used in various aspect of decision m...This study investigates annual earnings analysis with ARIMA （Autoregressive Integrated Moving Average） for future earnings prediction. Earnings prediction is very important to be used in various aspect of decision making process, such as： investor, creditor, analyst, academicians, practitioners, etc.. Evidence supports the ARIMA model that it is more accurate. It also has a smaller size of error value.展开更多
China＇s outward FDI has been increasing recently, as the country＇s policies over industrialization and national security change. Using financial data of 244 Chinese enterprises, this study empirically investigates t...China＇s outward FDI has been increasing recently, as the country＇s policies over industrialization and national security change. Using financial data of 244 Chinese enterprises, this study empirically investigates the patterns and determinants of China＇s outward FDI from 2001 to 2008 for its seven major destinations. Tobit and multiple regression analyses indicate that early Chinese FDI in 2001 and 2002 is concentrated in the labor-intensive industries in Asia, like those of early Japanese FDI in the early 1970s as well as those of Korean FDI in 1990s. The results also indicate that non-production oriented manufacturers invested in North America, in order to seek for market cultivation, technological advance, R＆D skills, and name brands. We also found that the central state-owned enterprises are the key FDI players in the continents with locational disadvantages展开更多
China will set up a national carbon emissions trading market by the end of 2017, which is initially open to individual investors from the initial market for business and institutional investors. In this article, the m...China will set up a national carbon emissions trading market by the end of 2017, which is initially open to individual investors from the initial market for business and institutional investors. In this article, the main influencing factors and mechanism of individual participation in carbon trading market are studied by establishing multiple linear regression model. The study found that age,education level, length of account opening time, and risk attitude are the main factors influencing the participation of individual investors. Environmental awareness and environmental impact are less affected; information transparency and transaction risk also have an impact on the degree of individual investor participation; investment experience does not affect the participation of individual investors in the carbon trading market.展开更多
Free trade is beneficial for all nations. Pareto optimality can be reached by trade without barriers, leading to maximizing total welfare of nations involved. Yet there are clear cases of complaining at the World Trad...Free trade is beneficial for all nations. Pareto optimality can be reached by trade without barriers, leading to maximizing total welfare of nations involved. Yet there are clear cases of complaining at the World Trade Organization （WTO） in which home bias is plausibly the reason for complaining, rather than objective criteria of the rules of trade agreements. Next to home bias in individual cases induced home bias leading to complaining at WTO might also be a trend. Using correlation and stepwise regression analysis a dataset on 28 complaining countries is analysed. The number of complaints at the WTO is the dependent variable in exploratory modeling. Independent variables are various variables on economic structure. Structural unemployment （SUN）, agricultural import share, current account balance, international property rights （IPR）, and foreign direct investment （FDI） turned out to be significantly related to the number of complaints. This is a strong indicator that complaining at the WTO is at least partly induced by other than objective factors. One of these factors other than objective factors could be considered as an induced home bias which leads to disruptive trade. The established relationship with one of these factors indicates the existence of induced home bias as an actual trend based on the outcomes of the analysis presented.展开更多
Based on DEA - Ridge Regression two-step method, the paper tries to construct industrial cluster competitiveness research framework for empirical analysis, and by the Hunan automobile industry cluster as an example. T...Based on DEA - Ridge Regression two-step method, the paper tries to construct industrial cluster competitiveness research framework for empirical analysis, and by the Hunan automobile industry cluster as an example. The study found that Hunan automobile industry cluster competitiveness is relatively weak, full of the very big promotion space; further research shows that the human capital investment, fixed capital investment, land investment and policy support are the main factors influencing the efficiency of automobile industry cluster in Hunan province.展开更多
Under China's innovation-driven development strategy, venture capital has become an important driving force in urban agglomeration integration and collaborative innovation. This paper uses social network analysis ...Under China's innovation-driven development strategy, venture capital has become an important driving force in urban agglomeration integration and collaborative innovation. This paper uses social network analysis to analyze spatiotemporal differences of venture capital in the Beijing-Tianjin-Hebei urban agglomeration for the period 2005–2015. A gravity model and panel data regression model are used to reveal the influencing factors on spatiotemporal differences in venture capital in the region. This study finds that there is a certain cyclical fluctuation and uneven differentiation in the venture capital network in the Beijing-Tianjin-Hebei urban agglomeration in terms of total investment, and that the three centers of venture capital(Beijing, Shijiazhuang and Tangshan) have a stimulatory effect on surrounding cities; flows of venture capital between cities display certain networking rules, but they are slow to develop and strongly centripetal; there is a strong positive correlation between levels of information infrastructure development and economic development and venture capital investment; and places with relatively underdeveloped financial environments and service industries are less able to apply the fruits of innovation and entrepreneurship and to attract funds. This study can act as a reference for the Beijing-Tianjin-Hebei urban agglomeration in building a world-class super urban agglomeration with the best innovation capabilities in China.展开更多
文摘Although widely used, both the Markowitz model and VAR (Value at Risk) model have some limitations in evaluating the risk and return of stock investment. By the analysis of the conceptions of risk and return, together with the three hypotheses of technological analysis, a novelty model of metering and evaluating the risk and return of stock investment is established. The major indicator of this model , risk-return ratio K, combines the characteristic indicators of risk and return. Regardless of the form of the risk-return probability density functions, this indicator K can always reflect the risk-return performances of the invested stocks clearly and accurately. How to use the model to make optimum investment and how to make portfolio combined with clustering analysis is also explained.
文摘This study investigates annual earnings analysis with ARIMA （Autoregressive Integrated Moving Average） for future earnings prediction. Earnings prediction is very important to be used in various aspect of decision making process, such as： investor, creditor, analyst, academicians, practitioners, etc.. Evidence supports the ARIMA model that it is more accurate. It also has a smaller size of error value.
文摘China＇s outward FDI has been increasing recently, as the country＇s policies over industrialization and national security change. Using financial data of 244 Chinese enterprises, this study empirically investigates the patterns and determinants of China＇s outward FDI from 2001 to 2008 for its seven major destinations. Tobit and multiple regression analyses indicate that early Chinese FDI in 2001 and 2002 is concentrated in the labor-intensive industries in Asia, like those of early Japanese FDI in the early 1970s as well as those of Korean FDI in 1990s. The results also indicate that non-production oriented manufacturers invested in North America, in order to seek for market cultivation, technological advance, R＆D skills, and name brands. We also found that the central state-owned enterprises are the key FDI players in the continents with locational disadvantages
文摘China will set up a national carbon emissions trading market by the end of 2017, which is initially open to individual investors from the initial market for business and institutional investors. In this article, the main influencing factors and mechanism of individual participation in carbon trading market are studied by establishing multiple linear regression model. The study found that age,education level, length of account opening time, and risk attitude are the main factors influencing the participation of individual investors. Environmental awareness and environmental impact are less affected; information transparency and transaction risk also have an impact on the degree of individual investor participation; investment experience does not affect the participation of individual investors in the carbon trading market.
文摘Free trade is beneficial for all nations. Pareto optimality can be reached by trade without barriers, leading to maximizing total welfare of nations involved. Yet there are clear cases of complaining at the World Trade Organization （WTO） in which home bias is plausibly the reason for complaining, rather than objective criteria of the rules of trade agreements. Next to home bias in individual cases induced home bias leading to complaining at WTO might also be a trend. Using correlation and stepwise regression analysis a dataset on 28 complaining countries is analysed. The number of complaints at the WTO is the dependent variable in exploratory modeling. Independent variables are various variables on economic structure. Structural unemployment （SUN）, agricultural import share, current account balance, international property rights （IPR）, and foreign direct investment （FDI） turned out to be significantly related to the number of complaints. This is a strong indicator that complaining at the WTO is at least partly induced by other than objective factors. One of these factors other than objective factors could be considered as an induced home bias which leads to disruptive trade. The established relationship with one of these factors indicates the existence of induced home bias as an actual trend based on the outcomes of the analysis presented.
文摘Based on DEA - Ridge Regression two-step method, the paper tries to construct industrial cluster competitiveness research framework for empirical analysis, and by the Hunan automobile industry cluster as an example. The study found that Hunan automobile industry cluster competitiveness is relatively weak, full of the very big promotion space; further research shows that the human capital investment, fixed capital investment, land investment and policy support are the main factors influencing the efficiency of automobile industry cluster in Hunan province.
基金Major Program of the National Natural Science Foundation of China,No.41590842
文摘Under China's innovation-driven development strategy, venture capital has become an important driving force in urban agglomeration integration and collaborative innovation. This paper uses social network analysis to analyze spatiotemporal differences of venture capital in the Beijing-Tianjin-Hebei urban agglomeration for the period 2005–2015. A gravity model and panel data regression model are used to reveal the influencing factors on spatiotemporal differences in venture capital in the region. This study finds that there is a certain cyclical fluctuation and uneven differentiation in the venture capital network in the Beijing-Tianjin-Hebei urban agglomeration in terms of total investment, and that the three centers of venture capital(Beijing, Shijiazhuang and Tangshan) have a stimulatory effect on surrounding cities; flows of venture capital between cities display certain networking rules, but they are slow to develop and strongly centripetal; there is a strong positive correlation between levels of information infrastructure development and economic development and venture capital investment; and places with relatively underdeveloped financial environments and service industries are less able to apply the fruits of innovation and entrepreneurship and to attract funds. This study can act as a reference for the Beijing-Tianjin-Hebei urban agglomeration in building a world-class super urban agglomeration with the best innovation capabilities in China.
