Title: Relationship of SBI with Nifty50.
Author: Supriya Pravin Deore
Introduction: The State Bank of India (SBI) is a premier financial institution and one of the largest and oldest public sector banks in India. Established in 1806 as the Bank of Calcutta, it was later renamed as the Bank of Bengal in 1809. Subsequently, it merged with the Bank of Bombay in 1840 and the Bank of Madras in 1843 to form the Imperial Bank of India. The Imperial Bank of India, in turn, became the State Bank of India in 1955 through an Act of Parliament.
Objective: To calculate Beta and find its significance.
Views and Reviews: State Bank of India (SBI) is widely regarded as a cornerstone in India’s banking sector, with a vast network and significant influence. It has earned praise for its commitment to financial inclusion, technological advancements, and diverse product offerings. However, some criticisms relate to bureaucratic processes and challenges in delivering a seamless customer experience. Overall, SBI stands as a key player, balancing its historical significance with ongoing efforts to adapt to modern banking trends.
Data collection: Nifty50 and SBI’s closing price was collected from yahoofinance.com. Weekly return of Nifty50 is termed as “X” and weekly return of SBI is termed as “Y”. Besides that, a few other things written in this report are taken from other websites and its information is provided in references.
Data Analysis:
Equation: Y=0.01777+0.01675x
Interpretation:
The above equation shows the relation between Nifty50 and SBI.
The regression equation is in the form of Y = mx + b, where:
- Y represents the dependent variable.
- X represents the independent variable.
Interpreting the coefficients:
- The coefficient is 0177 is the intercept of regression line.
- The coefficient 0.0167 is the slope of the regression line. It indicates the change in Y for a one-unit change in X. In this case, for every unit increase in X, Y is expected to increase by 0.0167 units.
- Number of observations are 50.
- 1039 is the t-stat for Y, the p-value for which is 0.9176.
- R square is 0.0404. This value indicates that approximately 42% of the variability in the dependent variable can be explained by the independent variables in the model.
- The ANOVA table shows the analysis of variance. The regression has a significant F 0.165 with a very low p-value 0.9176. This implies that the overall regression model is statistically significant in explaining the variability in the dependent variable.
Conclusion: Beta is 0.0177 which is less than 1, it means that SBI is good for long term investment.
Reference:
http://www.yahoofinance.com/
https://www.onlinesbi.sbi/