畢業(yè)論文外文翻譯--上市公司財務(wù)狀況的評價研究—創(chuàng)業(yè)板和中小企業(yè)板比較（適用于畢業(yè)論-全文預(yù)覽
【正文】 e nonparametric test results were in Table 3. Table 3 showed that there were 17 financial ratios passing the level of significance test. Because the other 11 financial ratios did not pass the test, accepting the null hypothesis H0, the paper suggested that there is no significant difference in the listed enterprises between on SME board and GME. These indicators are X9, X10, X12, X16, X17, X21, X22, X23, X25, X26, X27, and they should be removed. The remaining 17 primary indicators would go to next round of screening. D. Factor Analysis For the first 17 candidate indicators from difference analysis, the paper used CorrelateBivariate (MWW) for correlation analysis. The results showed in addition to X8, X19, X20, the majority of the financial indicators had significant correlation with each other. For fear of the loss of some important information if deleting indicators, the paper would not exclude relevant indicators. Instead, the paper carried out factor analysis to concentrate the 17 indicators. In this way, a small number of stable, weakrelated, and prehensive indicators can be extracted so as to include most of the financial information. Before the factor analysis, we must test the feasibility of factor analysis. With the paper chose principal ponent analysis to concentrate the 17 candidate indicators and the KMO value is , suitable for factor analysis. The factor extraction method used in this paper was: eigenvalue1 and the cumulative contribution rate80%.Besides, in order to make it easier to explain the factors, we selected the maximum variance method to plete the orthogonal rotation. After varimax orthogonal rotation, eigenvalues and cumulative contribution rate of the factors were in Table 4: As can be seen from Table 4, the eigenvalues of the first five principal ponents factor were all greater than 1, and covered % of the information the original variables contained. Generally, the lost information was little and the effect was desirable. Therefore, the first 5 factors can be used to replace and concentrate the original indicators. Then it was necessary to know the factor loadings of the 17 candidate indicators on the first 5 factors (. the correlation coefficient of each factor and original financial ratios). According to the result of factor analysis, factor F1 was loaded greater on the to X7 was related to the longterm liquidity of enterprises, F1 can be defined as longterm liquidity fact or。 SME board。 SMEs Board Yuan Shi Abstract: On the basis of parative analysis of the growth enterprise market’s position and financing function, this paper chose 28 panies of the first batch on the growth enterprise market (GEM) with their 2020 financial data, and correspondingly selected 28 panies in the same industry and accounting period on the small and mediumsize enterprise (SME) board as paired samples. The empirical results showed that: GEM listed panies were optimistic about the overall financial position, and most of them had the qualifications to list on the SME board. These results indicated the GEM was not an excellent financing platform for the potential small and mediumsize enterprises. It also revealed the reasons and provided policy remendation on development strategy to improve the market. Keywords: GME。 financing function I. INTRODUCTION Small and medium enterprises, accounting for 99% of total number of all the enterprises in China, provide the state with a large number of jobs and tax contributions. However, financing is the bottleneck restricting the development of SMEs for a long time. In order to share the benefits SMEs creating, the society must give a good financing system to make it more effectively. Although the Shenzhen Stock E
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