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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

中國大陸創業投資產業之研究 / The Study of Venture Capital Industry in China

張閔傑, Chang, Eric M. Unknown Date (has links)
The Study discusses the development of the venture capital (VC) industry in China, from its fundraising, investment to post investment, and comparisons on a global scale. We also analyzed the relationship between the innovative industries and economic growth, and discussed the VC’s exit route and stock market in China. The growth of China’s VC industry is still promising but there are still some challenges that it has to overcome. Furthermore, the VC development in China also implies the growth potential of the Chinese stock markets, and suggests that Taiwan should act as an active role and take advantage of its geographical position, strong relationship and regional stability with China to participate in the possible collaboration of the stock markets in the Asia-Pacific region.
2

Comparing CAPM and APT in the Chinese Stock Market

Zhang, Lina, Li, Qian January 2012 (has links)
As the stock market plays an important role in the global economy and Chinese economy become progressively significant part of the world economy, we are interested in the Chinese stock market. After we compared the methods on the stock market, we choose to use the CAPM and the APT model on Chinese stock market. As a lot papers study on the Main Board of Chinese stock market, we pay our attention on the SME Board and the ChiNext Board of Chinese stock market. We put the samples from the SME Board and the ChiNext Board into the regression models which are based on the CAPM and the APT model, and then we can use the regression models to forecast the long returns. Comparing the forecast ln returns with the true ln returns, we may find that the CAMP or the APT model can forecast better on the SME Board and the ChiNext Board. The systematic risk is the only factor we put the regression model based on the CAPM. For the regression model based on the APT model, we use three factors which are the systematic risk, daily exchange volume and the volatility. Our results show that the APT model can explain factors better than the CAPM for the samples from the SME Board and the ChiNext Board. On the other hand, we could not find evidence that the APT Model can forecast better than the CAPM for the SME Board and the ChiNext Board.

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