Add TITLE : RELATIONSHIP OF PROCTOR AND GAMBLE HYGIENE AND HEALTHCARE LIMITED WITH NIFTY 50
AUTHOR: PRIYA SALVE
INTRODUCTION
• PROCTOR AND GAMBLE HYGIENE AND HEALTHCARE LIMITED MANUFACTURES PERSONAL AND BEAUTY CAREAND HEALTHCARE PRODUCTS. OVER 65 INDIVIDUAL BRANDS ARE ORGANIZED INTO 10 PRODUCT CATEGORIES.
• P&G hygiene and healthcare limited company is one of the fastest growing FMCG companies.
• THE BETA OF A FIRM REFERS TO THE SENSITIVITY OF ITS SHARE PRICE WITH RESPECT TO AN INDEX OR BENCHMARK.
• BETA CAN BE SEEN AS A MEASURE OF RISK , THE HIGHER THE BETA OF THE COMPANY , THE HIGHER THE EXPECTED RETURN SHOULD BE TO COMPENSATES FOR THE EXCESS RISK CAUSED BY VOLATILITY.
OBJECTIVE: Calculation of beta of PROCTOR AND GAMBLE HYGIENE AND HEALTHCARE LIMITED.
LITERATURE REVIEW
ARTICLE 1: RESEARCH OF INVESTMENT RISK USING BETA COEFFICIENT
Beta is a widely used quantity in investment analysis. The systematic risk of an investment or asset in respect to the entire stock market is measured by the beta coefficient. It makes it possible to compare the level of risk associated with investments or assets that have various characteristics. Before interpreting its findings, it is important to comprehend the unique characteristics of this coefficient, the state of the capital market, and the assets that are being scrutinised. This study compares the level of risk and return of investments in capital projects to investments in a portfolio of chosen stocks on the Croatian capital market, and it analyses the applicability of beta in determining the risks of, by the characteristics, different types of investments. ( Karacic , bukvik 2014)
Article 2: Testing for Time-variation in Beta in India
The beta of a stock is significant in a number of scenarios, including asset pricing theory, the cost of capital, and hedging with index derivatives. In order to estimate betas, it is usual practise to estimate the market model using straight ordinary least square (OLS) regression. Although there are compelling economic justifications for time-varying betas, this presupposes that betas are stable. Using the modified Kalman filter of Harvey et al. (1992), we test for time-varying betas in the context of a market model with Generalised Auto Regressive Conditional Heteroscedasticity (GARCH) errors in this article. For 52% of stocks, the null of beta constancy is rejected. This has important ramifications for hedging and portfolio diversification. (Syed abuzar , Et al 2003)
CONCLUSION
To followers of CAPM, beta is useful. A stock’s price variability is important to consider when assessing risk. If you think about risk as the possibility of a stock losing its value, beta has appeal as a proxy for risk. Intuitively, it makes plenty of sense. Think of an early-stage technology stock with a price that bounces up and down more than the market. It’s hard not to think that stock will be riskier than, say, a safe-haven utility industry stock with a low beta.
Besides, beta offers a clear, quantifiable measure that is easy to work with. Sure, there are variations on beta depending on things such as the market index used and the time period measured. But broadly speaking, the notion of beta is fairly straightforward. It’s a convenient measure that can be used to calculate the costs of equity used in a valuation method.
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DATA COLLECTION
Firstly we have downloaded the data of proctor and gamble and nifty 50 dated from 1st April 2022 to 31st March 2023 from the official website of National stock exchange (nseindia.com) . firstly we have taken the data of nifty 50 and after deleting all the column except date and closing stock , we have added the weekday column in the data using weekday function of excel , then we have deleted all the rows except 5th day Friday rows . then we added another column named as returns column where we have found the returns by using the values in closing stock column and named it as X ( which will be X for our Regression also.) . Similarly repeating all these steps for our selected company we named it as Y ( which will be Y for regression also. Here is how we have collected the X and Y values.
DATA ANALYSIS
We can write the equation in the form of Y = a +b(X )
Where Y = Proctor and Gamble Returns
X= NIFTY-50 RETURNS
a =intercept , b = slope
hence the equation becomes ,
Y = Hence, the equation becomes,
Y = 0.246 + (0.71)*X
PROCTOR AND GAMBLE Returns = (0.246) + (0.71)*(Nifty-50 Returns)
(7.025)
n = 51 R² = 0.136 and F = 49.213
The above equation in the Data analysis explains us the relationship between X (Nifty-50 Returns) and Y (PROCTOR AND GAMBLE Returns). + SIGN INDICATES that there is a direct relationship which implies that if x rises , Y also rises vice versa. In this equation b= 0.71 that is if X rises by 1 unit , Y will rise by 0.71 units. Hence b is statistically significant at 5% significance level.
R2 =0.136 which means 13.6% of Y is explained by X , SIMILARLY F=49.213 which is also greater than table value. Hence overall model is statistically significant at 5% significance level.
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CONCLUSION
Since it can be seen that value of b beta is less than 1 which means that proctor and gamble hygiene and healthcare limited is good for long term investment.
References
• Domagoj Karacic & Ivana Bestvina Bukvic, 2014. “Research Of Investment Risk Using Beta Coefficient,” Interdisciplinary Management Research, Josip Juraj Strossmayer University of Osijek, Faculty of Economics, Croatia, vol. 10, pages 521-530.
• Syed Abuzar Moonis & Ajay Shah, 2003. “Testing for Time-variation in Beta in India,” Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 2(2), pages 163-180, May.
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