Conclcusion Large: Equity Valuation using accounting numbers

Large sample

In this paper, the researcher empirically examined also the success of multiple regression model. The researcher investigated if the Assets turnover, Profit margin, Equity Multiplier, and Return on total assets have no effect on the Equity Valuation from the informational data of LUVLE course website: https://luvle.lancs.ac.uk/Acfin/703.nfs. The researcher also used Frequency distribution and analysis of variance (ANOVA).

This paper examined the informational data of LUVLE course website: https://luvle.lancs.ac.uk/Acfin/703.nfs. The researcher discovered that the Assets turnover, Profit margin, Equity Multiplier, and Return on total assets have significant effect on the Return on Equity from the informational data of LUVLE course website.

This means that other variables can affect the result of the equity valuation. The researcher suggested the additional parameters for the greater accuracy of the model.

Conclusion-small: Equity Valuation using accounting numbers

VII. CONCLUSION:
Small sample
In this paper, the researcher empirically examined the success of multiple regression model. The researcher investigated if the R&D to Total Assets, Intangibles to Total Assets, Assets turnover, Profit margin, Equity Multiplier, and Return on total assets have no effect on the Equity Valuation from the informational data of LUVLE course website: https://luvle.lancs.ac.uk/Acfin/703.nfs. The researcher also used Frequency distribution and analysis of variance (ANOVA).
This paper examined the informational data of LUVLE course website: https://luvle.lancs.ac.uk/Acfin/703.nfs. The researcher discovered that the R&D to Total Assets, Intangibles to Total Assets, Assets turnover, Profit margin, Equity Multiplier, and Return on total assets have an effect on the Equity Valuation from the informational data of LUVLE course website. This means that other variables can affect the flaws of the equity valuation. The researcher suggested the additional parameters for the greater accuracy of the model.

Graph 4: Equity Valuation using accounting numbers

The statistical informational data was from LUVLE course website: https://luvle.lancs.ac.uk/Acfin/703.nfs.
It can be gleaned in Graph 4 above, that there were seven Firms who makes a remarkable inflation in terms of ratio analysis. Firm 513 got the highest inflation of Assets turnover, Profit margin and Equity Multiplier which range almost 6000 and followed by Firm 129, range above 5000. Third Firm who got Assets turnover, Profit margin and Equity Multiplier is 671, then 702, 607, 94 and 478.
Summary of the graphs were scrutinized by the researcher. It was found out that only three Firms got the high inflation. These Firms were Firm 702, Firm 671 and Firm 478. This implies that the Firms are performing well in the stock market place and they have good inflation elasticity. It was notable that some companies were also trying their best to be on top such as Firm 513, Firm 129, Firm 607, Firm 624, and Firm 165. This can be seen in their inflation elasticity variables.
The Analysis of Variance was used to determine if the Assets turnover, Profit margin, Equity Multiplier, and Return on total assets have an effect on the Equity Valuation. The null hypothesis is that the Assets turnover, Profit margin, Equity Multiplier, and Return on total assets have no effect on the Equity Valuation.
Thus, all independent variables have no significant effect on the equity valuation: Ho: μ1 = μ2 = μ3= μ4, or Ho. We assume that there should be at most five percent chance of erroneously rejecting a true Ho. Thus we specify a level of significance of 0.05. We used F-distribution and an Analysis of variance (ANOVA)test , and next step is to define the rejection or critical region. The degree of freedom numerator value is 4 and the degree of freedom denominator value is 706. So with α = 0.05, the critical value of F in this analysis of variance test is F0.05 (4,706) = 2.73.
The final statistical decision is rejected the null hypothesis. Since computed F (F c) is greater than Tabulated F (Ft), Ho is rejected and thus, all the independent variables of this study have a significant effect on the equity valuation should be considered as acceptance of the alternative hypothesis. The result of the “Analysis of Variance” (ANOVA) shows that the computed F (21.875) is greater than the tabular values of F-statistics at 0.05 degree of freedom (2.37).
The Regression results are as follows: the unbiased estimator of the variance of the error in the multiple regression model is equal to 2740.285. There is small value of MSE denominator than the MSE numerator (59944.883) so the estimator is a good fit of the regression. Standard error of estimate is equal to 52.34773. Multiple coefficient of determination is .105. (R^2) and an adjusted multiple coefficient of determination is equal to .110 (R2) showed that the data produced a good predictions. This was stated because the adjusted R^2 is closer to the unadjusted R^2.

Large Sample Result: Equity Valuation using accounting numbers

Large sample
This section presents the analysis of the data on the study to find out if the Assets turnover, Profit margin, Equity Multiplier, and Return on total assets have an effect on the Equity Valuation. The Multiple Regression model were used to examined the effect of the other values to the return on equity using LUVLE course website informational data
The descriptive statistics was also used in this study for the presentation purposes. Graphs 3 to 4 show the inflation of the elasticity of the variables.

The statistical informational data was from LUVLE course website: https://luvle/.lancs.ac.uk/Acfin/703.nfs.

From Graph 3, shows that there were 710 selected companies or firm. It is notable that there were 6 firms who got high income before extraordinary items, sales, and assets. Firm 702 got the highest inflation of income before extraordinary items, sales, and assets which range between 400000 to 450000 and followed by Firm 94, range near 40000. Third Firm who got income before extraordinary items, sales, and assets is 671, then 624,165 and 478.

Graph 2:Equity Valuation using accounting numbers

The statistical informational data was from LUVLE course website: https://luvle.lancs.ac.uk/Acfin/703.nfs.
From Graph 2 above, the researcher found out that there were two Firms who makes a remarkable inflation in terms of ratio analysis. The Firm 6 got the highest inflation of RTA, ITTA, Assets turnover, Profit margin and Equity Multiplier which range above 20 and followed by Firm 21, range almost 20. There were three Firms who were almost on range 10. The three Firms were 9, 12, and 24.
Summary of the graphs were scrutinized by the researcher. It was found out that only Firm 6 got high inflation. The Firm 21 got a high Analysis of ratio but slightly lows in terms of R & D. This implies that the only Firm 6 perform well in the stock market place and it has good inflation elasticity. It was notable that some Firms were also trying their best to be on top such as Firm 9, Firm 2, Firm 8, Firm 5, and Firm 4. This can be seen in their inflation elasticity variables.
The Analysis of Variance was used to determine if the R&D to Total Assets, Intangibles to Total Assets, Assets turnover, Profit margin, Equity Multiplier, and Return on total assets have an effect on the Return on Equity. The null hypothesis is that the Assets turnover, Profit margin, Equity Multiplier, R&D to Total Assets, Intangibles to Total Assets, and Return on total assets have no effect on the Equity Valuation.
Thus, Ho: μ1 = μ2 = μ3= μ4= μ5= μ6, or Ho: All independent variables have no significant effect on the equity valuation. The alternative is that not all independent variables have a significant effect on the return on equity. Let’s assume that there should be at most five percent chance of erroneously rejecting a true Ho. Thus we specify a level of significance of 0.05. We used F-distribution and an Analysis of variance (ANOVA)test , and next step is to define the rejection or critical region. The dfnum value is k-1, or 6 and the dfden value is T-k, or 18. So with α = 0.05, the critical value of F in this analysis of variance test is F0.05 (6,18) = 2.66. The decision Rule is Reject Ho in favor of Ha if the value of the computed F is greater than the value of tabulated F. Otherwise, do not reject Ho. The next step is to compute the test statistic. Find the computed F, by dividing the mean sum of square of regression value by the mean sum of square of residual value. The final step now is to make the statistical decision. Since computed F (F c) is greater than Tabulated F (Ft), Ho is rejected and thus, not all the independent variables of this study have a significant effect on the return on equity. The result of the “Analysis of Variance” (ANOVA) shows that the computed F (13.656) is greater than the tabular values of F-statistics at 0.05 degree of freedom (2.66). Hence, Ho must be rejected.
The Regression results are as follows: the unbiased estimator of the variance of the error in the multiple regression model is equal to .010. There is small value of MSE denominator than the MSE numerator (.131) so the estimator is a good fit of the regression. Standard error of estimate is equal to .09777. Multiple coefficient of determination is .820 (R2) and an adjusted multiple coefficient of determination is equal to .760 (R2) showed that the data produced a good predictions. This was stated because the adjusted R^2 is closer to the unadjusted R^2.

Results: Equity Valuation using accounting numbers

VI. RESULTS
Small sample
This section presents the analysis of the data on the study to find out if the R&D to Total Assets, Intangibles to Total Assets, Assets turnover, Profit margin, Equity Multiplier, and Return on total assets have an effect on the Equity Valuation. The Multiple Regression model was used to examine the effect of the other values to the equity valuation using LUVLE course website informational data. The descriptive statistics was also used in this study for the presentation purposes. Graphs 1 to 2 show the inflation of the elasticity of the variables.

The statistical informational data was from LUVLE course website: https://luve.lancs.ac.uk/Acfin/703.nfs.
Graph 1 above shows that out of 25, only 6 companies have a high R & D Range. The Firm number 6 got the highest inflation of R & D value which range between 150,000,000 and followed by Firm 5 and Firm 2, range near 50,000,000. The fourth firm who got R & D lower than 50,000,000was Firm 4. This implies that there were only few Firms who focused on the R & D. This means that many Firms were afraid to gamble or to take the risk in spending too much in Research and Development (R & D). This also shows that even though Firms belong to above £ 10,000 R & D, there were still other factors that can affect the interest of the investors.