毕业论文外文翻译--上市公司财务状况的评价研究—创业板和中小企业板比较适用于毕业论

毕业论文外文翻译--上市公司财务状况的评价研究—创业板和中小企业板比较适用于毕业论内容摘要：

ore 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。 factor F2 was loaded greater on the financial ratios X1, X2 and X3. Because they all reflected the shortterm liquidity of enterprises, F2 can be named as shortterm liquidity factor。 factor F3 had a greater load on the X13, X14 and X15, reflecting the pany39。 s profitability, can be defined as the profitability factor。 factor F4 had a greater load on the X18 and X19. These indicators are related to the ability to grow, so F4 can be named as business growth factor。 factor F5 was loaded greater on X28, therefore can be defined as the cash factor. E. Factor Scores and Composite Score According to factor loading matrix after varimax orthogonal rotation, through regression we can calculate the factor score coefficient matrix, which multiplied the standardized data matrix of financial indicators was the factor scores of 56 listed enterprises samples. Then using the contribution of each factor eigenvalue as the weight, the posite score of each listed pany can be calculated as follows: (Fi1, Fi2, Fi3 ..., Fi6 meant the factor scores of listed panies“i”) Fi=%Fi1 + %Fi2 + %Fi3 +%Fi4 + %Fi5 Calculated in the above method, each factor score and posite score of listed panies on SME board and GEM can be calculated. III. RESULTS ANALYSIS AND DISCUSSION A. Listed enterprises on GEM had a stronger cash acquisition capacity. Table showed that in the 28 selected samples, the cash fact or scores of 24 listed panies on GEM were significantly higher than the paired samples in the SME board, indicating that the listed panies on GEM had a stronger ability to obtain cash flow on the whole. The reasons why listed panies on GEM had an advantage on the ability of cash acquisition were mainly attributed to the following two reasons: on the one hand, this first batch of 28 listed enterprises on GEM successfully issued in 2020, and the pany got sufficient cash flow through financing。 on the other hand, listed panies on GEM characterized by hightech and servicebased industries were lightasset operation so that it was easier for listed enterprises to keep sufficient cash. Furthermore, it was an important method to manage and control cash that the level of cash flow can keep pace with the profit. B. Listed enterprises on GEM had a stronger liquidity capacity. By paring longterm and shortterm liquidity factor scores on Table 5, it can be easily found that listed enterprises on GEM had a stronger liquidity capacity, not only in the shortterm。