Objective
To calculate β & find its significance
Data collection
The data was gathered from a secondary source, the NSE’s official website. Data on the NSE’s daily closing stock price & the Shell has been gathered. The data has been narrowed down to the weekend (Friday) closing price only.
Data Analysis
Regression Statistics
Multiple R 0.239675
R Square 0.057444
Adjusted R Square 0.053613
Standard Error 78.50437
Observations 248
Interpretations:
Here, we can observe that the R square value is 0.057444, which means that 5.74% of weekly returns of Shell industries can be explained by Nifty.
We can infer that to the given extent shell does follow the Nifty trend.
ANOVA
df SS MS F Significance F
Regression 1 92397.56854 92397.57 14.99246 0.000138
Residual 246 1516082.099 6162.935
Total 247 1608479.667
Interpretations:
H0: Nifty is not influencing the weekly returns of Shell
H1: Nifty is influencing the weekly returns of Shell
Here as the F value is 14.99246 which is more than 4, thus we reject the null hypothesis & accept the alternate hypothesis, concluding that nifty is influencing the weekly returns of Shell.
Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept 739.2919 68.1186838 10.853 1.12E-22 605.1217 873.4622 605.1217 873.4622
X Variable 1 0.015951 0.004119612 3.87201 0.000138 0.007837 0.024065 0.007837 0.024065
Interpretations:
We can observe here that the Beta value is 0.843596 meaning that 1 unit change in Nifty leads to 0.843596 change in weekly returns of Shell. Also, the value of beta is positive indicating the presence of a positive relationship between the two variables.
The P value is 1.12E-22 which is less than 0.05, thus the model is significant at 95% confidence interval.