In this section, we present the findings of our research. 6. APT Model and regression analysis In…

In this section, we present the findings of our research. 6. APT Model and regression analysis In this part the results of how exchange rate fluctuations impact a MNC stock return are presented for the six selected companies. We used the APT model, as a multiple regression analysis. As mentioned before, the dependent variable is the stock return of each company and the explanatory variables are: market index, GDP, Exchange rate and Oil Price. The formula applied is the following is the formula (7) that we develop in the previous chapters: ri – rf = bex * (Ex – rf ) + bg * (G – rf ) + bm* (M – rf ) + bo * (O – rf ) Table 2: Regression of changes in all variables at 0.05 levels Company Percentage changes in independent variables – risk-free rate Standardized coefficients Beta t P value (constant) 1, 688 0, 104 % change in index – rf 0,777 4, 437 0, 000 % change SEK/USD – rf – 0, 075 -0, 243 0, 810 % change SEK/EUR – rf 0, 410 0, 502 0, 620 % change in GDP – rf -0, 257 -,319 0, 753 Volvo % change in oil price – rf 0, 052 , 435 0, 667 (constant) 1, 272 0, 215 % change in index – rf 0, 551 2, 523 0, 018 % change SEK/USD – rf 0, 255 0, 665 0, 512 % change SEK/EUR – rf -0, 398 -0, 391 0, 699 % change in GDP – rf 0, 317 0, 315 0, 756 SAAB % change in oil price – rf -0,115 -0, 765 0, 452 (constant) 0, 845 0, 406 % change in index – rf 0, 564 3, 815 0, 001 % change EUR/USD – rf 0, 105 0, 431 0, 670 % change in GDP -rf 0, 162 0, 652 0, 520 Peugeot % change in oil price -rf 0, 133 1, 013 0, 320 43 (constant) 1, 207 0, 238 % change in index – rf 0, 746 4, 631 0, 000 % change EUR/USD – rf 0, 113 0, 426 0, 674 % change in GDP -rf -0, 212 -0, 779 0, 443 Renault % change in oil price -rf 0, 174 1, 219 0, 234 (constant) 0, 8 53 0, 401 % change in index – rf 0, 781 6, 772 0, 000 % change EUR/USD – rf 0, 370 2, 130 0, 043 % change in GDP -rf -0, 234 -1, 361 0, 185 BMW % change in oil price -rf 0, 072 0, 654 0, 519 (constant) 1, 775 0, 088 % change in index – rf 0, 330 1, 756 0, 091 % change EUR/USD – rf 0, 025 0, 089 0, 930 % change in GDP -rf 0, 218 0, 776 0, 445 Audi % change in oil price -rf 0, 174 0, 967 0, 343 The table above sums up the results obtained from fitting the regression model and using SPSS with the data collected. A close look at those specific parameters for different companies give us details to analyze how each independent variable impacts each firm’s stock returns. We decide to use 5% or 0, 05 as our critical alpha value or significance level and it can be denoted by the Greek letter a. Statistically, the significant data refers to P-values. If an obtained P-Value is less than the chosen a level of 0.05, the P-Value is significant. As a consequence, we conclude that the concerned independent variable is a significant factor when explaining the changes in a given company’ stock return and the betas provide the sensitivity of the movements. In order to find any multi-co linearity relationship between the independent variables of each regression analysis of the selected company, a correlation matrix was produced (see appendix 2). We wanted to test if variables do not account for the same information in the regression analysis. For Swedish companies, we find that the SEK/USD exchange rate and the SEK/EURO exchange rate were highly correlated. We therefore tested the regression analysis without one of the exchange rate. However, the results remained the 44 same and we therefore chose to incorporate both exchange rates. For French companies, the GDP and the EURO/USD exchange rate were highly correlated. We could not test the regression analysis by excluding the exchange rate variable since this research is focusing on it. We therefore exclude the GDP but the results also remained the same. We therefore chose to have both variables in the regression analysis. For German companies, EURO/USD exchange rate and the GDP were found to be correlated but not at the same level as the above correlations. 6.1 Exchange rate For Swedish automobile companies, Volvo and Saab, we used two exchange rates, the SEK/USD and the SEK/EURO. For these two companies, the results show that there is not a significant relationship between their stock return and the two explanatory variables. The p-values are above the 5 % significance level and therefore not significant. Based on the betas values, we observe that Volvo stock return is negatively related to movements in SEK/USD whereas it is positively related to SEK/EURO. On the other hand, Saab stock return is positively related to movements in SEK/USD and positively related to SEK/EURO. For example, the beta can be interpreted like in this way: when the SEK appreciates by 1 %, Volvo stock return will increase with 0,075 % (and so on). For the French and the German companies, only the EURO/USD exchange rate was used as a currency variable. Beginning with the French companies, Peugeot and Renault provide almost similar results. The findings indicate that the relationship between EURO/USD exchange rate and companies’ stock returns is not significant at the 5% level. The betas values show a positive linkage between the EURO/USD exchange rate and the companies’ stock returns. For the German Companies, the results indicate that that there is no significant relationship between Audi stock return and the EURO/USD exchange rate at the 5%level of significance. However, BMW presents a different scenario from all the companies; the p-value indicates that there is a significant relationship between the BMW stock return