# Correlation Methods

#### 1^{st} Table Explanation

Correlation method is one of the techniques of research methodology which depicts the relationship among 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. In positive correlation shows the relation or 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 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. In further, continue with other variables, CCC which is cash conversion cycle has the positive links with ROA and APT but negative relation with ART. Current liabilities have the negative relation with ROA, APT, ART and CCC. As well as current ratio also has negative relation with ROA, ART, CL but positive relation with APT, CCC. So, financial leverage and debt have positive and negative both relationships with other variables. Now, here financial leverage has positive impact with ROA, APT, CCC and CR but has negative impact also in ART and CL. Debt has also negative correlation with all variables except current liabilities which show debt has no relation among all above given variables except CL. In all above correlations show that a kind of correlation in shape of positive and negative but some variables which have negative correlation reveal that variables have relationship only when one variable increase and decrease.

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 concern with financial performance and working capital, current assets and the current liabilities have negative relation with financial performance. Here, the indicator of financial performance is the ROA. The ROA is also dependent variable in this research work. In further, the working capital which is also equal to the CA-CL (Garg, 2015). This term shows that the negative linkage among ROA and WC.

#### 2^{nd} Table Explanation

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

The research about liquidity, (Gill, 2011) revealed that the result of its study, organizations which were confident to balance the higher stages of liquidity confronted less chances of stringent financial situations. However, this study could not establish a significant relationship between liquidity and firm growth. Moreover, financial leverage ratio is also sorts from 1.056 to 74.88 with an average of 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 study mentioned in descriptive studies. The mean values are showing the average number of profit or financial performance of the company in which the current assets are lower as compare to current liabilities. An average corporation has 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, 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 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 said studies. Here, in descriptive statistics mean, median, standard deviation which is also called variance; kurtosis and the skewness show the central tendency and measure the variability. So, the value of SD, kurtosis and skewness are measuring the variability and variance among the variables. The Jarque-Bera test is also used for normality and best fitness of test.

In this concern, this test shows the normality and reject or accept the null hypothesis basis 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 among Skewness and Kurtosis values (Descriptive Statistics; Zivot, 2007). Lastly, the sum and sum sq. deviation show 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 level and non-significant level of the value of the variables. In this way, the values for the probability and coefficient have different meaning. The coefficient values always show the beta or risk ratio. In this concern, APT has the significant level of p-value which is also in between 0 to 5%. So, the APT variable hypothesis is accepted and null hypothesis is rejected because this value is showing the significant impact of independent variable APT on the ROA with the coefficient of 0.356 and standard error 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 the 0.01 coefficient or variance and the standard error of 0.0039. Moreover, the financial leverage has the probability of 0.0007 which is also showing the acceptability of H8, and the rejection of null hypothesis for this variable. The financial leverage also has the value of 0.214748 coefficient 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 the impact on dependent variable. In this table, the APT, CCC and F_L have the 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 shows the 0.66 value which means that the percentage of multi collinearity does not exist because the value is near to 2 and more than zero. In this concern accordance with Durbin-Watson table, if the value is zero the multi collinearity exist and if the value is 4 or near to four then the negative correlation among the independent variables are exist. In this way, the other one 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 explain by the independent variables. In this concern, the R-squared also has negative value which means only (7.7) percent variance exists among the variables.

In this way, this table has the 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. As well as the t-statistics value is also less than the 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 null hypothesis is accepted. In this concern, the debt variable is rejected and null hypothesis is accepted because of the value of probability is also not in range of 0 to 10 of p-value. In further, current ratio has the p-value of 0.1538 which shows the maximum amount or value of probability and more than from 0.10. In this table, the ART, CA, CL, DEBT and CR are rejected and null hypothesis are accepted. In this table the amount of p-value which shows the significant level and insignificant level of percentage for alternative or null hypothesis acceptance. In this case the ART, CA, CL, DEBT And CR doesn’t have the significant impact and 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 level and non-significant level of the value of the variables. In this way, the values for the probability and coefficient have different meaning. The coefficient values always show the beta or risk ratio. In this concern, ART has the significant level of p-value which is also in between 0 to 5%. So, the ART variable hypothesis is accepted and null hypothesis is rejected because this value is showing the significant impact of independent variable ART on the APT with the coefficient of 0.03 and standard error 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 the probability of 0.000 which is also showing the acceptability of H7, and the rejection of null hypothesis for this variable. The debt variable is accepted and accepted because of the value of probability is also in range of 0 to 10 of p-value. This value also rejects the null hypothesis. In this way, the current liability variable is also accepted and null hypothesis is rejected.

The financial leverage also has the value of 0.90 coefficient with the standard error and t-statistics of 0.16 and 5.334. The ROE also has the 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. As well as, current ratio has the positive and significant impact on the APT which means the null hypothesis is also rejected and 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 the impact on dependent variable. In this table, the ART, CCC, CR, DEBT, F_L and ROE have the significant impact on the dependent variables. The Durbin-Watson statistics shows the 0.42 value which means that the percentage of multi collinearity does not exist because the value is towards the 2 and more than zero. In this concern accordance with Durbin-Watson table, if the value is zero the multi collinearity exist and if the value is 4 or near to four then the negative correlation among the independent variables are exist. In this way, the other one 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 explain by the independent variables. In this concern, the R-squared also has negative value which means only (7.7) percent variance exists among the variables.

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