### 1^{st} Table Explanation

The correlation method is one of the research methodologies that depicts the relationship between two or more variables. Moreover, correlation also describes the positive and negative aspects. In case of negative correlation, one variable increases than the other variable. A positive correlation shows the perfect relation among the things or variables. In this research study, ROA, APT, ART, CCC, CL, CR, F_L and Debt are the variables. In this way, the correlation among these variables mentions that the APT has a negative correlation with ROA, which means APT has no relation with ROA. However, ART has also negative correlation with ROA but has positive link with APT.

These situations describe the positive and negative both values, in negative there is no impact among ART and ROA but has the positive and perfect relation among the ART and APT. Further, continuing with other variables, CCC, which is the cash conversion cycle, has positive links with ROA and APT but a negative relation with ART. Current liabilities have a negative relation with ROA, APT, ART and CCC. As well The current ratio also has a negative relation with ROA, ART, and CL but a positive relation with APT and CCC. So, financial leverage and debt have positive and negative relationships with other variables. Now, here, financial leverage has a positive impact on ROA, APT, CCC and CR but also has a negative impact on ART and CL. Debt also has a negative correlation with all variables except current liabilities, which shows debt has no relation among all the above-given variables except CL. All the above correlations show a kind of correlation in the shape of positive and negative, but some variables that have negative correlations reveal that variables have a relationship only when one variable increases and decreases.

In positive correlation two or more variables move in same direction, if one variable increases then other one variable will also increase with same amount or value. As a concern with financial performance and working capital, current assets and current liabilities have a negative relation with financial performance. Here, the indicator of financial performance is the ROA. The ROA is also a dependent variable in this research work. In further, the working capital which is also equal to the CA-CL (Garg, 2015). This term shows the negative linkage between ROA and WC.

### 2^{nd} Table Explanation

The results of descriptive studies reveal that the ROA sorts from (22) to 19 with an average of 6.5. In this way, APT sorts from 0.41 to 15 with an average of 5.9. ART sorts from 0.88 to 575, which shows an average of 36.06. The conversion cycle of cash also sorts from (151) to 469, with an average of 64.7. Furthermore, CL has a 10935.94 average, which ranges from 40 to 41517, which is the maximum value of current debt. The current ratio shows an average of 0.288061, with a value of 0.0498 and a maximum value of 4.746.

The research about liquidity (Gill, 2011) revealed that the result of its study was that organizations that were confident in balancing the higher stages of liquidity confronted fewer chances of stringent financial situations. However, this study could not establish a significant relationship between liquidity and firm growth. Moreover, the financial leverage ratio is also sorted from 1.056 to 74.88, averaging 3.93. In last, debt value starts from 44 to 122743 with an average of 12658. These are the minimum and maximum values explanation of the variables of the study mentioned in descriptive studies. The mean values show the company’s average profit or financial performance in which the current assets are lower than current liabilities. An average corporation has a 12658.12 value of debt.

As the retort of the financial leverage, Rehman (2010) declared that the organizations receive more hold on the overcoming factors in the external level financing; the author also mentions the more concentration on the sources of external financing than the options of internal financing as well as found the significant and positive link among financial leverage the growth of the firm. Huynh (2010) studied the impact of initial financial size and leverage as firm growth determinants and found a significant positive relationship between leverage and firm growth. The results of this work are validated by the above-mentioned studies. Here, in descriptive statistics, mean, median, and standard deviation, which are also called variance, kurtosis and skewness, show the central tendency and measure the variability. So, the values of SD, kurtosis and skewness measure the variability and variance among the variables. The Jarque-Bera test is also used for normality and is the best fitness test.

In this concern, this test shows the normality and rejects or accepts the null hypothesis based on the value of Skewness and the Kurtosis tests. This test works like the p-value test where the acceptance rate falls in 0.00, 0.05 and 0.10 or 0%, 5% and 1%. This test also measures the difference between Skewness and Kurtosis values (Descriptive Statistics; Zivot, 2007). Lastly, the sum and sum sq. deviation shows the difference from the mean and also provide enhancement to the variance (Anderson, 1989).

### 3^{rd} Table Explanation

The regression analysis shows that the dependent variable is ROA. In this way, 149 observations are considered for this research work. The regression analysis shows the significant and non-significant levels of the value of the variables. In this way, the values for the probability and coefficient have different meanings. The coefficient values always show the beta or risk ratio. In this concern, APT has a significant level of p-value, which is also between 0 and 5%. So, the APT variable hypothesis is accepted, and the null hypothesis is rejected because this value shows the significant impact of the independent variable APT on the ROA with a coefficient of 0.356 and a standard error of 0.124.

In further, the variable CCC is also accepted because of the p-value is also fall among the significant values if 0 to 0.05, in this way, this variable is also accepted on the basis of significant value and the null hypothesis is rejected. CCC has a 0.01 coefficient or variance and a standard error of 0.0039. Moreover, the financial leverage has a probability of 0.0007, which also shows the acceptability of H8 and the rejection of the null hypothesis for this variable. The financial leverage also has a coefficient of 0.214748, with the standard error and t-statistics of 0.06 and 3.46. In more detail, if the t-statistic value is more than 0.10, then the independent variable also has an impact on the dependent variable. In this table, the APT, CCC and F_L have a significant impact on the dependent variables with the t-statistics of more than 0.10. In this table, three more values of variables test methodology are important.

The Durbin-Watson statistics show the 0.66 value, which means that the percentage of multi-collinearity does not exist because the value is near two and more than zero. In this concern, in accordance with the Durbin-Watson table, if the value is zero, the collinearity exists, and if the value is four or near 4, then the negative correlation among the independent variables exists. In this way, the other important value of the table is the R-squared, which is also used for the sake of testing the amount of variance among the variables. The adjusted R-squared is -0.13, which means that the adjusted R-squared is too low. This value shows that the -13% ROA is explained by the independent variables. In this concern, the R-squared also has a negative value, which means only (7.7) per cent variance exists among the variables.

This table has 149 observations with ROA. The current asset is rejected in which the null hypothesis is also accepted because the p-value is not fall 0 to 0.10. The t-statistics value is also less than 0.10, with the coefficient and standard error of -0.66 and 0.077. In this way, the current liability variable is also rejected, and the null hypothesis is accepted. In this concern, the debt variable is rejected, and the null hypothesis is accepted because the value of probability is also not in the range of 0 to 10 of the p-value. Furthermore, the current ratio has a p-value of 0.1538, which shows the maximum amount or value of probability and more than 0.10. In this table, the ART, CA, CL, DEBT and CR are rejected, and the null hypothesis is accepted. In this table, the amount of p-value shows the significant and insignificant levels of percentage for alternative or null hypothesis acceptance. In this case, the ART, CA, CL, DEBT And CR don’t have a significant impact or effect on the dependent variable. In this case, the dependent variable is ROA.

### 4^{th} Table Explanation

The regression analysis shows that the dependent variable is APT. In this way, 146 observations are considered for this research work. The regression analysis shows the significant and non-significant levels of the value of the variables. In this way, the values for the probability and coefficient have different meanings. The coefficient values always show the beta or risk ratio. In this concern, ART has a significant level of p-value, which is also between 0 and 5%. So, the ART variable hypothesis is accepted, and the null hypothesis is rejected because this value shows the significant impact of the independent variable ART on the APT with a coefficient of 0.03 and a standard error of 0.0035.

In further, the variable CCC is also accepted because of the p-value is also fall among the significant values if 0 to 0.05, in this way, this variable is also accepted on the basis of significant value and the null hypothesis is rejected. CCC has the 0.01 coefficient or variance and the standard error of 0.002. Moreover, the financial leverage has a probability of 0.000, which also shows the acceptability of H7 and the rejection of the null hypothesis for this variable. The debt variable is accepted because the value of probability is also in the range of 0 to 10 of the p-value. This value also rejects the null hypothesis. In this way, the current liability variable is also accepted, and the null hypothesis is rejected.

The financial leverage also has a value of 0.90 coefficient with the standard error and t-statistics of 0.16 and 5.334. The ROE also has a significant value in this table, which also has the -0.04 and 0.0098 coefficient and standard error. In this way, the ROE variable also accepts the alternative hypothesis and rejects the null hypothesis. Also, the current ratio has a positive and significant impact on the APT, which means the null hypothesis is also rejected, and the alternative hypothesis is accepted in this case with the values 2.235 and 0.65 of coefficient and standard error.

In more detail, if the t-statistic value is more than 0.10, then the independent variable also has an impact on the dependent variable. In this table, the ART, CCC, CR, DEBT, F_L and ROE have a significant impact on the dependent variables. The Durbin-Watson statistics show the 0.42 value, which means that the percentage of multi-collinearity does not exist because the value is towards the two and more than zero. In this concern, in accordance with the Durbin-Watson table, if the value is zero, the collinearity exists, and if the value is four or near 4, then the negative correlation among the independent variables exists. In this way, the other important value of the table is the R-squared, which is also used for the sake of testing the amount of variance among the variables. The adjusted R-squared is -0.13, which means that the adjusted R-squared is too low. This value shows that the -13% ROA is explained by the independent variables. In this concern, the R-squared also has a negative value, which means only (7.7) per cent variance exists among the variables.

In this way, this table has a low observation as compared to the previous table. The current asset is rejected in which the null hypothesis is also accepted because the p-value is not fall 0 to 0.10. In this way, the current liability variable is also rejected, and the null hypothesis is accepted due to more than a percentage of the p-value. In this concern, the debt variable is accepted because the value of probability is also in a range of 0 to 10 of the p-value. This value also rejects the null hypothesis. In this table, the amount of p-value shows the significant and insignificant levels of percentage for alternative or null hypothesis acceptance. In this case, the CA doesn’t have a significant impact and effect on the dependent variable. In this case, the dependent variable is ROA (Durbin Watson Table; Sekaran).