BUS601: Financial Management

Table 3. Results of the regression analysis

As you can see from the table 3 that 7.6%, 4.2% and 3% of the perceived variability in the models I, III, and IV were demonstrated by the variations in the explanatory variables (EVA, FL, and TL) used in the study. Remaining 92.4%, 95.8%, and 97% of the variations in the models were associated with factors which were not shown in the models. These R2 values suggest that there might be factors which may have greater explanatory power in predicting MVA. Hence H3 and H4 both are rejected implying that EVA and leverage have no profound impact on MVA. Furthermore, it is clear that Operating Leverage has no impact on MVA. 

Table 4. Coefficient for predictors of MVA

By referring to the table 4, the regression models can be written as follows;

MVA = 13,547.18 - 0.478X1 + ε ⟶   Model I

MVA = 9,790.55 + 418.66X2 + ε ⟶ Model II

MVA = 17,163.48 - 1,882.28X3 + ε  ⟶  Model III

MVA = 14,665.54 - 804.69X4 + ε ⟶ Model IV

As you can see from the models that EVA, FL, TL denoted by X1, X3, X4 respectively exhibit a negative association with MVA whereas OL denoted by X2 exhibits positive association with MVA.