Author : Manoj Gawli (EMBA -15 , Roll No. – 65)

Introduction :

MRF Ltd is an Indian MNC listed on BSE and NSE and the largest manufacturer of tyres in India and the fourteenth largest manufacturer in the world. The company manufactures rubber products including tyres, treads, tubes and conveyor belts, paints and toys. Its total revenue for year 2017 was 22,683.87 Crores INR (US\$3.3 billion). Its subsidiaries are MRF Corp Limited, Funskool (India) Ltd., MRF SG Pte Ltd, MRF Lanka (P) Ltd.

Objective : To calculate the beta (β) of MRF Ltd and find its significance.

Data Collection :

Data for this company and Nifty 50 is downloaded from NSE site, from 1st March 2019 to 28th February 2020.
Out of the data which was downloaded from that, only Friday closing price was considered, thus converting the data into weekly closing format.

Data Analysis :

On basis of collected data below statistics were derived:
Weekly returns of Nifty50 and MRF Ltd has been calculated.
The Weekly returns of Nifty50 are considered as X and Weekly returns of MRF Ltd were considered as Y.
Later Y was regressed on X , using the “Regression” option under “Data Analysis” in Excel. Following Output was generated :

Equation :

Ŷ = 0.283 + 0.743 X (0.780)*
N (Number of Observations) = 50
R Square (R2) = 0.240 F = 15.185

Description :

Ŷ = 0.283 + 0.743 X

t -Stat = 0.780 , N = 50 , R2 = 0.240 , F = 15.185 , SE = 2.564 , P = 0.438

• The above equation tells us the relationship between Nifty50 (X) and MRF Ltd (Y).
If MRF Ltd’s weekly returns rises by 1 unit then Nifty50’s weekly returns rises by 0.743 units and vice versa.
(Positive sign means that there is a Direct Positive Relationship between both , which means if MRF Ltd weekly returns rises then Nifty50’s weekly returns also rises and vice versa.)
• T – Stat for b value (0.780) and the p value (0.438) is more than 0.05 which means b is not statistically significant at 5% level.
• F is 15.185 and the p value for which is more than 0.05 which means overall the model is not statistically significant.

Conclusion : The overall model is not significant , therefore we cannot depend on it.