基于隨機邊界模型的IPO抑價現(xiàn)象研究
[Abstract]:IPO underpricing refers to the economic phenomenon that the initial public offering price is higher than the initial public offering price. IPO underpricing is a difficult problem in the capital market in the world, which has been discussed and deeply studied by domestic and foreign scholars for a long time. This paper studies the phenomenon of IPO underpricing in China based on stochastic boundary analysis model and multivariate linear regression model in order to explain the causes of IPO underpricing in China. In this paper, the sample data is selected from 1993 to 2010 in Shanghai and Shenzhen main board public offering, and selected samples cover most of the industry plate. In this paper, the factors that affect IPO underpricing are classified as company performance factor, issue underwriting policy factor, market fluctuation, investor group psychological factor and other factors. How these factors affect IPO underpricing is analyzed comprehensively and deeply, and the correlation between these factors and IPO underpricing rate is analyzed theoretically. Then, in the following chapter, the stochastic boundary model is introduced, the stochastic boundary model is briefly introduced and derived, and the applicability of stochastic boundary model in the study of IPO pricing efficiency is analyzed. Then, we use stochastic boundary model and multivariate linear regression model for empirical analysis to determine that there is no obvious upper boundary in the sample data, and there is obvious stochastic lower boundary, which means that there is no obvious upper boundary in the sample data. The pricing of new shares in the primary issue market is efficient. The reason for the abnormal high price of new shares on the first day of trading comes from the irrational factors in the secondary market. The excessive demand and speculative speculation in the market lead to a high underpricing rate. In order to verify the influence of various factors on IPO underpricing, the correlation test is carried out by multi-variable linear regression model. Finally, according to these factors and the results of the analysis, the corresponding policy recommendations are put forward.
【學位授予單位】:哈爾濱工程大學
【學位級別】:碩士
【學位授予年份】:2012
【分類號】:F832.51;F224
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