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Ouantile Regression Method Research On Influencing Factors Of Financial Performance For Chinese Manufacturing Industry Listed Corporation

Posted on:2016-05-05Degree:MasterType:Thesis
Country:ChinaCandidate:M TongFull Text:PDF
GTID:2309330461457510Subject:Applied statistics
Abstract/Summary:PDF Full Text Request
The company is the basic organization of modern business, while the performance evaluation is an important content of the business strategic management. In recent years, the development of China’s financial, securities market is becoming more and more mature, an increasing number of listed Corporation. The enterprise managers, investors and relevant government departments pay more and more attention to research of the listed company’s financial performance.Based on this, first, this paper summarized on the significance of performance evaluation and current situation of the development of researches on the financial performance evaluation at home and abroad, analyzed several present evaluation methods, and combined with the characteristics of listed companies in China, then rebuild the financial performance evaluation index system, which including the listed company profit ability, debt paying ability, operation ability, growth ability four aspects. Second, using factor analysis method, focusing on the total value of the selecting 22 manufacturing industry listed Corporation to give the comprehensive score of financial performance in 2014, and as a measure of financial performance indicators of manufacturing industry listed Corporation. Third, based on the analysis results of the front chapter, establish the index system of influencing factors of manufacturing industry listed Corporation’s financial performance, and then using the quantile regression model to analysis the correlation between variables. Finally, summarize the research results of the front several chapters, based on this; give some suggestions to the following deep research.
Keywords/Search Tags:cluster analysis, factor analysis, quantile regression, least square method
PDF Full Text Request
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