## 3 Results
### Company Valuation Based on DCF
**} & \multicolumn{1}{c}{**M1**} & **M2** & **M3** & **M4** & **M5** & **M1** & **M2** & **M3** & **M4** & **M5** & **M1** & **M2** & **M3** & **M4** & **M5** & **M1** & **M2** & **M3** & **M4** & **M5** & **M1** & **M2** & **M3** & **M4** & **M5** & **M1** & **M2** & **M3** & **M4** & **M5** \\ \hline \multirow{3}{*}{**Brazil**} & Mean & 17.26 & 8.74 & 12.72 & 9.98 & 8.75 & 13.71 & 16.38 & 19.19 & 15.60 & 15.62 & 24.43 & 15.20 & 10.16 & 9.55 & 10.87 & 13.14 & 7.39 & 6.76 & 7.59 & 11.24 & occ 13.34 & 13.09 & 7.79 & 8.24 \\  & Median & 17.82 & 6.22 & 13.63 & 9.41 & 8.35 & 11.52 & 11.47 & 13.31 & 16.64 & 15.78 & 19.09 & 14.86 & 10.16 & 10.07 & 10.82 & 11.27 & 6.39 & 6.63 & 6.24 & 6.92 & 8.72 & 8.49 & 13.37 & 8.00 & 7.36 \\  & STD & 9.38 & 5.93 & 7.29 & 5.88 & 5.54 & 8.44 & 10.74 & 11.95 & 9.00 & 8.96 & 11.76 & 5.60 & 2.17 & 4.69 & 5.14 & 8.99 & 4.07 & 2.53 & 5.58 & 9.16 & 9.62 & 10.25 & 9.16 & 4.40 & 4.58 \\ \hline \multirow{3}{*}{**India**} & Mean & 9.63 & 18.04 & 16.88 & 5.43 & 4.46 & 12.23 & 7.70 & 9.01 & 5.29 & 5.15 & 18.09 & 12.94 & - & 13.65 & 9.78 & 6.48 & 8.50 & 3.14 & 9.14 & 8.61 & - & - & - & - \\  & Median & 4.90 & 21.43 & 16.66 & 4.97 & 4.60 & 8.41 & 6.63 & 7.20 & 4.77 & 4.55 & 17.58 & 7.53 & - & 8.17 & 6.35 & 3.05 & 3.65 & 3.14 & 5.29 & 5.26 & - & - & - & - \\  & STD & 6.69 & 10.68 & 6.13 & 3.03 & 2.37 & 9.46 & 5.08 & 6.73 & 2.85 & 2.63 & 10.19 & 7.63 & - & 10.65 & 6.92 & 5.40 & 6.74 & 0.51 & 6.73 & 6.59 & - & - & - & - \\ \hline \multirow{3}{*}{**Japan**} & Mean & 11.71 & 9.12 & 11.11 & 4.74 & 5.22 & 13.66 & 7.35 & 11.43 & 7.22 & 7.15 & 11.67 & 9.96 & 13.49 & 8.05 & 8.15 & 6.48 & 8.50 & 3.14 & 9.14 & 8.61 & 13.61 & 7.80 & 8.34 & 6.48 & 6.70 \\  & Median & 10.82 & 7.44 & 7.66 & 4.48 & 5.23 & 11.68 & 6.35 & 8.98 & 7.24 \begin{table}
\begin{tabular}{l c c c c c} \hline \hline
**Markef Sector** & **Consumer** & \multicolumn{2}{c}{**Consumer**} & & & \\
**Cyclvals** & **Non-Cyclycals** & **Industrial** & **Technology** & **Utilities** \\ \hline
**Spain** & 10 & 9 & 10 & 9 & 7 \\ \hline
**United States** & 9 & 9 & 9.5 & 11 & 6.50 \\ \hline
**Japan** & 9 & 8.50 & 9 & 10 & 6.50 \\ \hline
**Brazil** & 15 & 15 & 15 & 14 & 12 \\ \hline
**India** & 19 & 19 & 18 & 15 & - \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Published reference Weighted Average Cost of Capital (WACC) (in %) by sectors and market. Figure 5: Errors for several years (\(x\) axis) and companies (\(y\) axis) obtained when considering the reference WACC in the EV models: (**a**) M1, (**b**) M2, (**c**) M3, (**d**) M4, (**e**) M5. Based on these last results, we should argue that even the application of strongly sustained and widely used published reference WACCs does not lead to accurate valuation of companies. This fact drives the concept supported earlier about the difficulty to extend WACC analysis to sectors or regions. It is also proven in this experiment the better performance of models M4 and M5 than the others, which is consistent with the previous findings in the preceding experiment. As a summarizing result of this section, we can state that the use of the DCF model based exclusively on intrinsic information, regardless of how intensive were the efforts to set a right WACC, could not offer an accurate model to estimate cross-company valuations. Additional information and other techniques were required for an effective unbiased valuation. Hence, we propose in the next section to investigate and use other techniques, such us ML, which together with extrinsic information could better suit each specific company, sectors, markets, or regions.