本篇文章讲的是净资产收益，股权、净收入和资产的高范围意味着样本中包含的银行范围很广，可以被划分为中小型银行和大型银行。同样，ROE和ROA的范围意味着，这些数据包括工作效率高、盈利能力强的银行(ROE和ROA为正值)，以及过去几年盈利能力不强的银行(ROE和ROA为负值)。本篇墨尔本论文代写文章由澳洲论文人EducationRen教育网整理，供大家参考阅读。
The high range of equity, net income and assets imply that the sample consists of a broad range of banks which can be qualified into small to medium to large banks. Similarly, the range of ROE and ROA imply that the data consists of banks which are working efficiently and profitably (positive values for ROE and ROA) as well as those which have been not so profitable in the past years (negative values for ROE and ROA).
The return on equity (ROE) variable is the variable corresponding to the return the banks get on their equity. Essentially, it is the net income as a percent of the stakeholders’ equity. It is an indicator of the profitability that the bank generates as a percent of the money invested by the shareholders. A positive ROE indicates better profitability. It is evident from the data that the minimum ROE is negative at -0.89 whereas the maximum is positive at 0.087. Evidently the ROE is generally low for the dataset implying low profitability. A negative mean at -0.014 shows that the average bank has a negative profitability in the given dataset. The skewness of the data is -3.561 implying that the data is negatively skewed. This implies that most of the banks in the sample have a negative ROE. The mean is lower than the median. The standard deviation of the data is 0.1644. However, it cannot be sad that the dispersion in the data is low because standard deviation as a measure of dispersion is affected by the values in the data. The coefficient of variation of the data which is the ratio of standard deviation and mean is 11.74. This is a better measure of dispersion because it, being a ratio of two statistical measures both of which are affected by the value of the data and the extreme values, is not affected much by the data points. A CoV of 11.74 is considered high which means that across the sixty observations, the data is highly dispersed even though the range of the data is 0.98. The kurtosis of the dataset is 14.813.
The return on assets (ROA), on the other hand, measures the profitability of the assets of the banks. It points out the credibility and efficiency of the management of the institution, here banks, in their adeptness to generate income out of the assets available at their disposal. The data considered shows that the minimum value is -0.029 and the maximum is 0.006. The mean is also negative at -0.00003. The standard deviation is 0.0065. The skewness of the data is -2.594. A negative skew implies that the mean will be lower than the median. Using similar logic as mentioned in the case of ROE, coefficient of variation will be a better measure to understand the dispersion of the data. The CoV of ROA dataset is 216 which is very high implying that the data of ROA is very highly dispersed albeit the range of the data is only 0.035. The kurtosis of the data is 7.356.
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