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Copyright of NTU Management Review is the property of NTU Management Review and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Social Sciences & Philosophy is the property of Research Center for Humanities & Social Sciences, Academia Sinica and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Engineering Management / Gongcheng Guanli Xuebao is the property of Journal of Engineering Management Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Engineering Management / Gongcheng Guanli Xuebao is the property of Journal of Engineering Management Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

There are irrational phenomena related to investor sentiment in the stock market, and the quantitative study of investor sentiment and stock market is important for discovering stock market patterns and aiding investment forecasting. Based on the investor statements in forums, a CNN-TLDA hybrid model is innovatively built to quantify investor sentiment from multiple perspectives, and explore the interaction between investor sentiment and the stock market from both positive and topic. The roles of investor sentiment in forecasting are investigated based on LSTM（long short-term memory） network. It is shown that Chinese stock market investors are generally pessimistic, and both investor optimism and topics of interest are highly correlated with the stock market. The multi-perspective sentiment analysis reduces the prediction error to 41%. The results of the study can assist investors in their investment decisions and also provide a scientific reference for the analysis and utilization of individual investors′ sentiment in the stock market. [ABSTRACT FROM AUTHOR]

In our country's stock market, the subject of large stock dividends is highly sought after by small and medium investors, but there is also the market chaos which is hyped by the concept of high-send transfers. How to use the financial data of listed companies to mine potential stocks is undoubtedly of great significance. The seven-year financial index of 2 158 listed manufacturing companies is used as the research data, and the prediction model of large stock dividends of listed companies is built by sampling, feature selection and integrated learning algorithm, and the empirical research is carried out. The results show that both sampling and feature selection methods can effectively improve the performance of the integrated prediction model. Compared with the redundant information in the dataset, the data imbalance has a more significant influence on the accuracy of model prediction. The combination model of ADASYN+mRMR+XGBoost achieves the best results, and the classification accuracy rate of large stock dividends samples reaches 84.96%. Investors are recommended to give priority to this combination model to predict the implementation of high send-to stocks by listed companies. [ABSTRACT FROM AUTHOR]

Copyright of NTU Management Review is the property of NTU Management Review and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Taiwanese Sociology is the property of Taiwanese Sociology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of NTU Management Review is the property of NTU Management Review and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Commerce & Management Quarterly is the property of Chinese Association of Business & Management Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The impact of investment sentiment on asset prices is very important in the Chinese stock market, which is dominated by individual investors. The investor sentiment and macroeconomic variables are added to the conditional CAPM model, using two steps regression analysis framework of Avramov and Chordia (2006). We examine the explanatory power of the conditional asset pricing model including investor sentiment information and macroeconomic variables on Chinese stock market's anomalies. The empirical results show that the conditional CAPM model containing information about IPO first-day return as investor sentiment can explain the puzzle of the idiosyncratic volatility, the scale effect and value effect in China stock market significantly. Economic uncertainty index as an additional macroeconomic variable in conditional CAPM model can explain the illiquidity premium of the stock market in China stock market. The empirical results are robust for different measure of idiosyncratic volatility and illiquidity. The result confirms that the investor sentiment plays an important role in asset pricing. [ABSTRACT FROM AUTHOR]

Copyright of Wuhan University Journal (Philosophy & Social Sciences) / Wuhan Daxue Xuebao (Zhexue Shehui Kexue Ban) is the property of Wuhan University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Three compensation mechanisms, that is loss compensation, revenue compensation and fixed government revenue compensation, and their impacts on venture capital scale and efficiency are studied in the framework of incentive theory. The main conclusions include: loss compensation would undermine the efforts of venture capitalists, which is not conducive to enhancing efficiency and expanding scale of venture capital; revenue compensation and fixed government revenue compensation have the same incentive characteristics, they can promote the formation of venture capital partnerships, expand the scale and enhance the efficiency of venture capital at the same time. When government compensated venture capitalist with the same cost, revenue compensation will attract more private investment. Furthermore, due to the possibility of destructing venture capitalists and private investors' limited liability protection, the implementability of fixed government revenue compensation can not be guaranteed. [ABSTRACT FROM AUTHOR]

With the assumption that individual investors in Chinese stock market are irrational, this paper uses the experimental research method to study the effect on individual investors' behavior exerted by the listed companies' information disclosure. We find that individual investors in our country are overconfident, paying inadequate attention to information disclosure offered by the listed companies. They are more influenced by the financial information than the non-financial information; but they are not over-sensitive to the former while under-sensitive to the latter. This indicates that we should improve the system of listed companies' information disclosure so that it can be accepted by individual investors as soon as possible. [ABSTRACT FROM AUTHOR]