Roll no-046, ITM, EMBA 15,KHARGHAR.
Introduction:

Objectives:
To Calculate beta of Vadilal Industries and find its significance using regression analysis with NIFTY50.

Data collection:
The closing price data of Nifty50 and Vadilal Industries was taken from www.nseindia.com for the time period 1st March 2019 to 28th Feb 2020.
From the available data, the closing rates of all the Fridays in the year was sorted to find out weekly returns for both Nifty as well as Vadilal Industries . Then the weekly returns was calculated for both by using formula –
where, C3 is present week closing price and C2 is the previous week closing price.
Once the data is calculated, weekly return column for NIFTY50 is considered as “X” variable and the weekly returns column for Vadilal Industries is considered as “Y” variable.

Data analysis:
Using the Regression Add-on in Microsoft Excel Data Analytics tool we get following values:
R Square R2=0.1448
N (Observations) = 51
F = 8.1317
Therefore, formulating below question:
Y^= 0.8793+1.1373X(2.8516)
t-stat =2.8516, N=51, R2=0.1448, F=8.1317
The above equation tells us the relationship between NIFTY50 (X) and VADILAL INDUSTRIES (Y),
that is Price and Demand. If there is in NIFTY50 by 1 unit then the vadilal industries rises by 1.1373 and vice versa.
t-stat for b is 2.8516 and the t value is 0.0063 which means b is statiscally significant at 2% level.
R2 is 0.1448 which means 15% of Y is explain by X, which means 85% are other factor which are not in the model.

Conclusion:-
The model is good but we can depend only 15% on it.