基于SPSS-17.0的上市公司财务报表分析

基于SPSS 17.0的上市公司财务报表分析l 问题描述：上市公司财务状况是上市公司经营状况的货币反映，也是评价上市公司股票质量的主要依据。因此，财务状况的分析是众多投资者关注的重点，掌握准确的上市公司的财务资料并进行科学合理的分析，关系到投资的合理规避和投资收益的有效保障。财务分析的对象是上市公司定期公布的财务报表，财务报表是公司营运和财务状况的定量描述，是公司经营状况的“晴雨表”。本文使用SPSS 17.0对185家上市公司的年报财务数据进行了分析，进而对上市公司的财务状况进行判断。分析步骤：样本及指标选取本文从深证网站上收集了185家上市公司的年报数据，选取的变量指标如下：X1股票代码；X2股票简称；X3-总资产；X4-所有者权益合计包含少数股东权益 ；X5-净资产收益率(营业利润）； X6-资产收益率；X7-净利润率；X8-存货周转率；X9-应收账款周转率；X10-资产周转率。由于X3X10这8个财务指标的单位不同，在进行数据处理前应对其进行标准化处理。图1 变量设置图2 新产生的变量图3 原始数据1.相关性分析对以上八个指标进行相关性分析，本例选用Pearson进行分析，分析结果如下表。表1 Descriptive Statistics（描述性统计量）NMinimumMaximumMeanStd. Deviation总资产1852.14E83.07E103.2376E94.34176E9所有者权益合计包含少数股东权益185.009.65E91.3724E91.76482E9净资产收益率(营业利润）185-7.19.59.0051.60593资产收益率185-.34.18.0237.06670净利润率185-3.341.09.0024.37871存货周转率185-97.00371.6210.598836.56376应收账款周转率185.69574.9922.564458.72599资产周转率185.041.65.5574.25099Valid N (listwise)185表2 Correlations（变量间相关系数矩阵）Zscore: 总资产Zscore: 所有者权益合计包含少数股东权益Zscore: 净资产收益率(营业利润）Zscore: 资产收益率Zscore: 净利润率Zscore: 存货周转率Zscore: 应收账款周转率Zscore: 资产周转率Zscore: 总资产Pearson Correlation1.777*.124.253*.118-.004.144.161*Sig. (2-tailed).000.094.001.109.953.050.029Sum of Squares and Cross-products184.000143.04022.74946.46221.723-.80526.50929.622Covariance1.000.777.124.253.118-.004.144.161N185185185185185185185185Zscore: 所有者权益合计包含少数股东权益Pearson Correlation.777*1.134.254*.155*.053.011.054Sig. (2-tailed).000.069.000.035.473.885.461Sum of Squares and Cross-products143.040184.00024.69946.78528.5239.7581.97810.028Covariance.7771.000.134.254.155.053.011.054N185185185185185185185185Zscore: 净资产收益率(营业利润）Pearson Correlation.124.1341.685*.677*.048.050.057Sig. (2-tailed).094.069.000.000.519.503.445Sum of Squares and Cross-products22.74924.699184.000125.986124.6208.7859.12510.402Covariance.124.1341.000.685.677.048.050.057N185185185185185185185185Zscore: 资产收益率Pearson Correlation.253*.254*.685*1.758*.139.085.089Sig. (2-tailed).001.000.000.000.060.249.228Sum of Squares and Cross-products46.46246.785125.986184.000139.54325.51015.67016.379Covariance.253.254.6851.000.758.139.085.089N185185185185185185185185Zscore: 净利润率Pearson Correlation.118.155*.677*.758*1.126.027.015Sig. (2-tailed).109.035.000.000.087.711.835Sum of Squares and Cross-products21.72328.523124.620139.543184.00023.1925.0532.833Covariance.118.155.677.7581.000.126.027.015N185185185185185185185185Zscore: 存货周转率Pearson Correlation-.004.053.048.139.1261.008-.218*Sig. (2-tailed).953.473.519.060.087.911.003Sum of Squares and Cross-products-.8059.7588.78525.51023.192184.0001.522-40.039Covariance-.004.053.048.139.1261.000.008-.218N185185185185185185185185Zscore: 应收账款周转率Pearson Correlation.144.011.050.085.027.0081-.035Sig. (2-tailed).050.885.503.249.711.911.634Sum of Squares and Cross-products26.5091.9789.12515.6705.0531.522184.000-6.488Covariance.144.011.050.085.027.0081.000-.035N185185185185185185185185Zscore: 资产周转率Pearson Correlation.161*.054.057.089.015-.218*-.0351Sig. (2-tailed).029.461.445.228.835.003.634Sum of Squares and Cross-products29.62210.02810.40216.3792.833-40.039-6.488184.000Covariance.161.054.057.089.015-.218-.0351.000N185185185185185185185185*. Correlation is significant at the 0.01 level (2-tailed).*. Correlation is significant at the 0.05 level (2-tailed).从表2中可以看出，以上8个财务指标之间具有较强的相关关系。在建立模型时采用因子分析进行降维处理。1. 因子分析：1) 选择KMO and Bartletts Test输出因子初试得分和巴特利检验；2) 因子抽取个数选择4，因为从因子贡献率上发现前4个总贡献为81.020% ？3) 因子旋转采用最大正交化旋转；4) 将因子得分以变量形式存储，因子得分采用回归计算法，并输出因子得分系数矩阵。经过以上步骤得到以下分析结果（省略部分结果）：表3 KMO and Bartletts TestKaiser-Meyer-Olkin Measure of Sampling Adequacy.642Bartletts Test of SphericityApprox. Chi-Square508.677df28Sig.000表4 Communalities（共度量表）InitialExtractionZscore: 总资产1.000.898Zscore: 所有者权益合计包含少数股东权益1.000.890Zscore: 净资产收益率(营业利润）1.000.770Zscore: 资产收益率1.000.836Zscore: 净利润率1.000.825Zscore: 存货周转率1.000.645Zscore: 应收账款周转率1.000.985Zscore: 资产周转率1.000.633Extraction Method: Principal Component Analysis.表5 Total Variance Explained（主成分表）ComponentInitial EigenvaluesExtraction Sums of Squared LoadingsRotation Sums of Squared LoadingsTotal% of VarianceCumulative %Total% of VarianceCumulative %Total% of VarianceCumulative %12.66833.35533.3552.66833.35533.3552.42930.36830.36821.60920.11553.4691.60920.11553.4691.80822.59652.96431.20615.07368.5421.20615.07368.5421.22915.36668.3304.99812.47881.020.99812.47881.0201.01512.69081.0205.7559.43590.4556.3354.18994.6447.2292.86697.5098.1992.491100.000Extraction Method: Principal Component Analysis.表6 Rotated Component Matrixa （旋转后的因子负荷矩阵）Component1234Zscore: 总资产.090.932-.092.116Zscore: 所有者权益合计包含少数股东权益.108.935.036-.049Zscore: 净资产收益率(营业利润）.876.026-.040.026Zscore: 资产收益率.893.190.022.045Zscore: 净利润率.905.045.066-.015Zscore: 存货周转率.127.082.784-.079Zscore: 应收账款周转率.040.052.019.990Zscore: 资产周转率.095.131-.773-.100Extraction Method: Principal Component Analysis.Rotation Method: Varimax with Kaiser Normalization.a. Rotation converged in 4 iterations.表7 Component Score Coefficient Matrix（因子得分系数矩阵）Component1234Zscore: 总资产-.060.524-.038.066Zscore: 所有者权益合计包含少数股东权益-.053.539.070-.100Zscore: 净资产收益率(营业利润）.377-.081-.059.007Zscore: 资产收益率.364.015-.001.016Zscore: 净利润率.385-.066.029-.037Zscore: 存货周转率.024.074.643-.100Zscore: 应收账款周转率-.009-.025-.002.978Zscore: 资产周转率.052.037-.628-.093Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. Component Scores.表8 Component Score Covariance Matrix（因子得分协方差矩阵）Component123411.000.000.000.0002.0001.000.000.0003.000.0001.000.0004.000.000.0001.000Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. Component Scores. 因子分析结果如下：（）从“KMO and Bartletts Test”表及共同度表判断数据能够进行因子分析；（2）从表5中可以看出第一主成分的特征根是2.668，解释了总变异的33.355%，第二三四个特征根分别是1.609、1.206、0.998，分别解释了总变异的20.115%、15.073%、12.478%，以上四个主成分合计解释了总变量的81%，能够解释绝大部分变量；（3）从表6的旋转结果可以看出：第一主成分在净资产收益率（X5）、资产收益率（X6）、净利润率（X7）上有较大的负荷，说明第一主成分反映了上市公司的资本获利能力；第二主成分在总资产（X3）、所有者权益合计包含少数股东权益（X4）上具有较大的负荷，说明第二主成分反映了上市公司的综合财务实力和投资者利益。第三主成分在存货周转率（X8）和资产周转率（X10）上具有较大的负荷，说明第三主成分反映了上市公司的运营效率，第四主成分在应收账款周转率（X9）上具有较大的负荷，说明第四主成分在某种程度上反映了上市公司的收账政策。2. 结果分析根据以上4个主成分的含义，对主成分进行进一步分析，参照因子得分系数矩阵（表7）建立因子得分模型：FAC1 = -.060*X3-0.053*X4+ 0.377*X5+ 0.364*X6+ 0.385*X7+ 0.024*X8-0.009*X9+ 0.052*X10FAC2= 0.524*X3+0 .539*X4-0.081*X5+0.015*X6-0.066*X7+0.074*X8-0.025*X9+0.037*X10FAC3= -0.038*X3+0.070*X4-0.059*X5-0.001*X6+0.029*X7+0.643*X8-0.002*X9-0.628*X10FAC4= .066