Results 6.1. Descriptive Statistics

6. Results

6.1. Descriptive Statistics

Table 4 reports the summary statistics of the important variables generated by implementing the methodology and data within the proposed period from the section above. Table 4 describes returns of the risk factors over the entire period. The average daily market premium is -0.0016%. The daily premium related with HML risk factor is slightly larger than the daily risk premium associated with SMB risk factor which are 0.0000607% and 0.0000055%, respectively. The market premium has the highest level of volatility while the HML porftolio has the highest level of excess return.

Table 5 shows the correlation between dependent variable and independent variables within the proposed time period. The table shows that market index, SMB, and oil index have a positive correlation with the auto index. In additional, only HML has a negative correlation with the auto index.The strongest correlation is occured between the auto index and the market index which its correlation coefficient is larger than 0.5. Moreover, the table also shows the correlation between independent variable and another independent variable. The table exhibits that all independent variables are imperfectly correlated each other which showed all correlations between each independent variables are smaller than 0.5 or larger than -0.5. Thus, correlation between all these independent variables may not violate multicollinearity.

Figure 3 and figure 4 describe that the auto index almost mimics the market index. The existence of a positive relationship between the auto index and the market index, and high level of statistical significance in terms of the regression results could be explained both figures. Therefore, automobile companies give the biggest boost to the TOPIX index. Daisuke Shimazu, as cited by Bloomberg, said that Toyota as the largest company in Japan, has a big influence on the TOPIX index because of its weighting index.

Figure 4: Returns on the auto index