Title: RELATIONSHIP OF DALMIA BHARAT WITH NIFTY 50
Author: DHARA GALA
Introduction:
One of the top producers of sugar in the nation, the sugar industry is geographically well-diversified and dedicated to “Green Growth,” enabling the group to increase value for all of its clients. The group, which has historically been active in southern, eastern, northern, and north-eastern India, has increased its global presence through its business in refractories by making numerous acquisitions in Germany and other European nations. The group’s sales have increased over the past sixteen years at a CAGR of 24%, reaching over 13,800 Cr in 2021, and its market capitalization has increased as well, reaching 31,191 Cr.
Objective: Calculation of Beta of ‘Dalmia Bharat’ and its significance
Literature:
1. Nifty 50
The seven-year period from 2007 and 2020 was taken into account and separated into six segments at the times when crises had occurred. The stock behaviour was monitored during each period, and the tail index was calculated using the weighted least squares (WLS) estimator, which was developed by Nair et al. (2019).According to the study, only a few stocks’ tail activity was affected by the crisis events; other stocks’ behaviour was unaffected. Additionally, during some periods, these stocks were able to withstand the change brought on by the crisis events, but not during others. Using the tail index values, the study determines the periods that are severe and those that are not severe. (Srilakshminarayana G, 2021)
2. Nifty fifty on NSE
In the context of the Indian stock market, this article seeks to identify trends in intraday volatility and examines how changes in the Indian economy have an effect on stock market volatility. For the aim of this study, one minute tick data for Nifty 50 futures from January 1, 2011, to August 31, 2018, was employed. For several time periods and each day of the week, volatility was calculated. Our investigation provides proof of the anticipated U-shaped intraday volatility pattern (greater at the start and end of the day). Over the time period under study, we additionally noticed a decrease in the hourly volatility. However, there was insufficient data to assess how the Indian economy’s growth affected stock market volatility. (Singh et all, 2018)
Data Collection:
The closing price data of Nifty50 from yahoo finance and Dalmia Bharat Limited was taken from www.nseindia.com (National Stock Exchange) for the time period 1ST APRIL 2022 to 31ST MARCH 2023.
From the available data, the closing rates of all the Fridays in the year were sorted to find out weekly returns for both Nifty as well as Dalmia Bharat Limited then the weekly returns were calculated for both by using the formula –
Weekly return = (C3-C2)/C2 *(100)
Where C3 represent week’s closing price and C2 is the previous week closing price.
Once the data is calculated, the weekly return column for NIFTY50 is considered as the “X” variable and the weekly returns column for Dalmia Bharat Limited is considered as the “Y” variable.
The Model and formulas used are:-
Y = a +bX
X ̅ =∑X/N
Y ̅=∑Y/N
x = X – X ̅
y = Y – Y ̅
b=∑ xy /∑(x)^2
a= Y ̅- bX ̅
e = Y – Y ̅
Variance of error=(σe)^2 =∑e^2/N-K
S.E of b = √ ((σe)^2 /∑x^2)
t stat of b = b/ S.E of b
TSS=ESS+RSS
ESS = (b^2)*(∑x^2)
RSS = ∑e^2
R^2 = ESS/TSS
F = Mean ESS/Mean RSS
Data Analysis:
Utilizing the Regression Add-on in the Microsoft Excel Data Analytics tool below values were acquired
R Square = R^2 = 0.226751788
a = 0.633838793
b = 1.16121065
F = 14.36904403
P value = 0.30759658
Below expression shows the relationship model between Dalmia Bharat Limited and NIFTY50 weekly returns:
Dalmia Bharat Ltd Weekly Return = 0.633838793+ 1.16121065*(NIFTY50 Weekly Return)
The P value 0.9276 which is greater than 0.05 it means the overall model is not statistically significant at 5% level.
Conclusion:
Beta is more than 1 so the company is good for short-term investment.
Reference:
Singh, Ritvik and Gangwar, Rachna, 2018, A Temporal Analysis of Intraday Volatility of Nifty Futures on the National Stock Exchange, Munich Personal RePEc Archive, September 2018,
Srilakshminarayana G, 2021, Tail behaviour of the nifty-50 stocks during crises periods, Advances in Decision Sciences (ADS), published by asia university, Taiwan