REGRESSION ANALYSIS OF THE WEEKLY RETURNS OF NIFTY 50 AND ADITYA BIRLA FASHION & RETAIL LTD.

Arline Joseph
M. A. Economics
Shreemati Nathibai Damodar Thackersey Women’s University, Mumbai

1.1 INTRODUCTION
Aditya Birla Fashion and Retail Ltd. (ABFRL), formerly known as Pantaloons Fashion & Retail Limited, was formed after the consolidation of the branded apparel businesses of Aditya Birla Group comprising Aditya Birla Nuvo Ltd.’s (ABNL) Madura Fashion division and ABNL’s subsidiaries Pantaloons Fashion & Retail Limited (PFRL) and Madura Garments Lifestyle Retail Company Limited (MGLRCL) in May 2015. Post consolidation, PFRL was renamed as Aditya Birla Fashion and Retail Limited with effect from 12 January 2016. ABFRL is India’s No. 1 fashion lifestyle entity. It altogether hosts India’s largest fashion network with over 8,000 points of sale in over 750+ cities and towns, which include more than 2,161 exclusive brand outlets (EBOs) and 245 value stores. The Company is engaged in the business of manufacturing and retailing of branded apparels and runs a chain of apparels and accessories retail stores in India. The NIFTY 50 index is National Stock Exchange of India’s benchmark broad based stock market index for the Indian equity market. It represents the weighted average of 50 Indian company stocks in 13 sectors and is one of
the two main stock indices used in India, the other being the BSE Sensex.

1.2 OBJECTIVE
To calculate the Beta (b) of the Aditya Birla Fashion & Retail Ltd. (ABFRL) and observe its significance for the period January 1, 2019 to December 31, 2019.

1.3 DATA COLLECTION
The paper studies the relationship between the weekly returns of NIFTY and ABFRL. The historical data of NIFTY 50 and ABFRL’s Security-wise Price Volume & Deliverable Position Data was retrieved from the NSE site for the period starting January 1, 2019 and ending December 31, 2019. The raw data for NIFTY 50 and ABFRL was filtered to obtain only the closing prices for Friday for the above-mentioned period. The weekly returns of the two data sets were also acquired. The weekly returns of NIFTY are the X variable and the weekly returns of ABFRL are the Y variable. Both the variables contain 50 observations
each.

1.4 DATA ANALYSIS
The following results are obtained after using the statistical tool of Regression to find the (b) and the significance of the weekly returns of NIFTY 50 (X Variable) and ABFRL (Y Variable) for the period January 1, 2019 to December 31, 2019.

Regression Line: Y = – 43.606 + 0.014X + e

N = 50, R^ 2 = 0.248, F = 15.855

1. The above equation shows the relationship between X (Weekly Returns of NIFTY 50) and Y (Weekly Returns of ABFRL).

2. A positive sign means that there is a positive relationship between the two variables.
If X rises, then there is a rise in Y too. If X falls, then there is a fall in Y also.

3. In the case of the above equation, if X (Weekly Returns of NIFTY 50) increases by 1 unit then Y (Weekly Returns of ABFRL) will increase by 0.014 units.

4. T – Stat for b is 3.982.

5. P value is 0.00023 which is less than 0.01. Since, P value is less than 0.01, b is statistically significant at 1% level.

6. R 2 is 0.248. It means that 24.8% of the variations in Y (Weekly Returns of ABFRL) i.e. the dependent variable are explained by X (Weekly Returns of NIFTY 50) i.e. the independent variable.

7. The F value is 15.855, the significance for which is less than 0.01. So overall, the model is statistically significant at 1% level.

1.5 CONCLUSION
It can be rightly concluded that the objective of the paper i.e. to find the Beta (b) of ABFRL has been achieved. Even though the model has proven to be statistically significant on the basis of the Regression, the value of Multiple R (0.498) suggests that there is a weak correlation between the two variables. R^ 2 also known as the Coefficient of Correlation (0.248) is a small value and hence the goodness fit of the model is weak.
Hence, it can be concluded that the model even though weak, is statistically significant.