{"id":24866,"date":"2026-03-22T11:06:11","date_gmt":"2026-03-22T05:36:11","guid":{"rendered":"http:\/\/www.sachdevajk.in\/?p=24866"},"modified":"2026-03-22T11:06:11","modified_gmt":"2026-03-22T05:36:11","slug":"relationship-between-nifty-50-and-shree-cement-ltd","status":"publish","type":"post","link":"http:\/\/www.sachdevajk.in\/?p=24866","title":{"rendered":"Relationship between Nifty 50 and Shree cement ltd"},"content":{"rendered":"
\n

Title:<\/span><\/b> Relationship between Nifty 50 and Shree cement ltd<\/p>\n

Author<\/b>: Sakshi Haware (65)

<\/span><\/p>\n<\/div>\n


1. Introduction:<\/b>
Shree Cement Ltd is one of the leading cement manufacturing companies in India and is known for its strong operational efficiency and cost leadership. The company plays a significant role in the infrastructure and construction sector, contributing to economic growth. It has a wide presence across India and maintains a strong market reputation. Due to its consistent performance, it attracts the attention of investors. Therefore, studying its relationship with NIFTY 50 helps in understanding its market behaviour.<\/span><\/p>\n


2. Objective:<\/b>
To calculate Beta and observe its significance.
\u00a0<\/span><\/p>\n

3. Literature Review:\u00a0<\/span><\/b><\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0\u00a0<\/span><\/b>a<\/span><\/p>\n

Study on Risk and Return Relationship:<\/span><\/b><\/p>\n

William F. Sharpe (1964), explains that beta is an important measure to understand the relationship between risk and return of a stock. He states that stocks with higher beta show more fluctuation with market changes, while stocks with lower beta are less risky. This concept is useful in analyzing Shree Cement Ltd, as it helps to identify how sensitive the company\u2019s returns are to market movements.3<\/span><\/p>\n

\u00a0<\/span>Study on Market Influence on Stock Prices:<\/span><\/b><\/p>\n

Eugene F. Fama (1970), states that stock prices are influenced by overall market information and trends. According to his study, companies in industries like cement are affected by economic growth and market conditions. Shree Cement Ltd, being a part of this sector, is influenced by the performance of NIFTY 50. Therefore, studying this relationship helps investors understand the behaviour of the stock.<\/span><\/p>\n

4. Data Collection:<\/span><\/b>
Data for Nifty 50 And Shree cement ltd was downloaded from NSE India\u2019s website for the period of 1\/1\/2025 to 31\/12\/2025. The Data was manipulated to get Friday closing prices of Nifty 50 and Shree cement ltd. Weekly returns were calculated. Weekly returns of Nifty 50 are named as X and weekly returns of shree cement ltd were named as Y. Y was regressed on X.<\/p>\n

5. Data Analysis:<\/b>
The following data was derived for the taken time period:

<\/span><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\n

Return (Nifty50)<\/span><\/b><\/p>\n<\/td>\n

\n

Return (Shree cement ltd)<\/span><\/b><\/p>\n<\/td>\n<\/tr>\n

\n

X<\/span><\/p>\n<\/td>\n

\n

Y<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

-0.29<\/span><\/p>\n<\/td>\n

\n

-3.10<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

0.31<\/span><\/p>\n<\/td>\n

\n

2.68<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

0.54<\/span><\/p>\n<\/td>\n

\n

-0.80<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

0.06<\/span><\/p>\n<\/td>\n

\n

1.25<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

-0.51<\/span><\/p>\n<\/td>\n

\n

0.30<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

-0.61<\/span><\/p>\n<\/td>\n

\n

0.83<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

-1.61<\/span><\/p>\n<\/td>\n

\n

2.53<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

0.90<\/span><\/p>\n<\/td>\n

\n

3.42<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

0.28<\/span><\/p>\n<\/td>\n

\n

1.40<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

-0.33<\/span><\/p>\n<\/td>\n

\n

3.43<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

-1.65<\/span><\/p>\n<\/td>\n

\n

-0.83<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

-1.55<\/span><\/p>\n<\/td>\n

\n

-0.90<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

-0.96<\/span><\/p>\n<\/td>\n

\n

-0.93<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

2.73<\/span><\/p>\n<\/td>\n

\n

3.36<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

-0.84<\/span><\/p>\n<\/td>\n

\n

-1.00<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

-1.49<\/span><\/p>\n<\/td>\n

\n

1.56<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

-1.27<\/span><\/p>\n<\/td>\n

\n

-2.55<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

1.81<\/span><\/p>\n<\/td>\n

\n

2.49<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

-2.04<\/span><\/p>\n<\/td>\n

\n

1.37<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

0.83<\/span><\/p>\n<\/td>\n

\n

0.85<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

1.11<\/span><\/p>\n<\/td>\n

\n

0.90<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

0.53<\/span><\/p>\n<\/td>\n

\n

-0.52<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

0.73<\/span><\/p>\n<\/td>\n

\n

1.36<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

1.24<\/span><\/p>\n<\/td>\n

\n

0.34<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

0.69<\/span><\/p>\n<\/td>\n

\n

-0.91<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

-2.05<\/span><\/p>\n<\/td>\n

\n

-6.94<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

-1.57<\/span><\/p>\n<\/td>\n

\n

2.55<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

1.15<\/span><\/p>\n<\/td>\n

\n

-0.03<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

-1.01<\/span><\/p>\n<\/td>\n

\n

-0.02<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

0.41<\/span><\/p>\n<\/td>\n

\n

6.42<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

0.67<\/span><\/p>\n<\/td>\n

\n

0.38<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

-4.04<\/span><\/p>\n<\/td>\n

\n

-7.54<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

1.41<\/span><\/p>\n<\/td>\n

\n

0.36<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

-1.26<\/span><\/p>\n<\/td>\n

\n

4.11<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

-5.04<\/span><\/p>\n<\/td>\n

\n

-1.41<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

0.33<\/span><\/p>\n<\/td>\n

\n

1.95<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

2.68<\/span><\/p>\n<\/td>\n

\n

-0.62<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

-0.72<\/span><\/p>\n<\/td>\n

\n

-4.97<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

-3.42<\/span><\/p>\n<\/td>\n

\n

-3.46<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

-1.90<\/span><\/p>\n<\/td>\n

\n

-2.51<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

3.03<\/span><\/p>\n<\/td>\n

\n

4.11<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

0.59<\/span><\/p>\n<\/td>\n

\n

0.53<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

2.75<\/span><\/p>\n<\/td>\n

\n

-1.07<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

-0.22<\/span><\/p>\n<\/td>\n

\n

-1.60<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

-1.77<\/span><\/p>\n<\/td>\n

\n

-7.24<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

0.48<\/span><\/p>\n<\/td>\n

\n

-1.81<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

0.98<\/span><\/p>\n<\/td>\n

\n

1.67<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

2.45<\/span><\/p>\n<\/td>\n

\n

1.39<\/span><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\n

SUMMARY OUTPUT<\/span><\/i><\/p>\n<\/td>\n

\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n
\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n
\n

Regression Statistics<\/span><\/p>\n<\/td>\n

\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n
\n

Multiple R<\/span><\/p>\n<\/td>\n

\n

0.47<\/span><\/p>\n<\/td>\n

\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n
\n

R Square<\/span><\/p>\n<\/td>\n

\n

0.22<\/span><\/p>\n<\/td>\n

\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n
\n

Adjusted R Square<\/span><\/p>\n<\/td>\n

\n

0.21<\/span><\/p>\n<\/td>\n

\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n
\n

Standard Error<\/span><\/p>\n<\/td>\n

\n

2.56<\/span><\/p>\n<\/td>\n

\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n
\n

Observations<\/span><\/p>\n<\/td>\n

\n

48<\/span><\/p>\n<\/td>\n

\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n
\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n
\n

ANOVA<\/span><\/p>\n<\/td>\n

\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n
\n

\u00a0<\/span><\/i><\/p>\n<\/td>\n

\n

df<\/span><\/i><\/p>\n<\/td>\n

\n

SS<\/span><\/i><\/p>\n<\/td>\n

\n

MS<\/span><\/i><\/p>\n<\/td>\n

\n

F<\/span><\/i><\/p>\n<\/td>\n

\n

Significance F<\/span><\/i><\/p>\n<\/td>\n

\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n
\n

Regression<\/span><\/p>\n<\/td>\n

\n

1<\/span><\/p>\n<\/td>\n

\n

86.85<\/span><\/p>\n<\/td>\n

\n

86.85<\/span><\/p>\n<\/td>\n

\n

13.26<\/span><\/p>\n<\/td>\n

\n

0.00<\/span><\/p>\n<\/td>\n

\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n
\n

Residual<\/span><\/p>\n<\/td>\n

\n

46<\/span><\/p>\n<\/td>\n

\n

301.34<\/span><\/p>\n<\/td>\n

\n

6.55<\/span><\/p>\n<\/td>\n

\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n
\n

Total<\/span><\/p>\n<\/td>\n

\n

47<\/span><\/p>\n<\/td>\n

\n

388.19<\/span><\/p>\n<\/td>\n

\n

\u00a0<\/span><\/p>\n<\/td>\n

\n

\u00a0<\/span><\/p>\n<\/td>\n

\n

\u00a0<\/span><\/p>\n<\/td>\n

\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n
\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n\u00a0<\/td>\n<\/tr>\n
\n

\u00a0<\/span><\/i><\/p>\n<\/td>\n

\n

Coefficients<\/span><\/i><\/p>\n<\/td>\n

\n

Standard Error<\/span><\/i><\/p>\n<\/td>\n

\n

t Stat<\/span><\/i><\/p>\n<\/td>\n

\n

P-value<\/span><\/i><\/p>\n<\/td>\n

\n

Lower 95%<\/span><\/i><\/p>\n<\/td>\n

\n

Upper 95%<\/span><\/i><\/p>\n<\/td>\n

\n

Lower 95.0%<\/span><\/i><\/p>\n<\/td>\n

\n

Upper 95.0%<\/span><\/i><\/p>\n<\/td>\n<\/tr>\n

\n

Intercept<\/span><\/p>\n<\/td>\n

\n

0.14<\/span><\/p>\n<\/td>\n

\n

0.37<\/span><\/p>\n<\/td>\n

\n

0.37<\/span><\/p>\n<\/td>\n

\n

0.71<\/span><\/p>\n<\/td>\n

\n

-0.61<\/span><\/p>\n<\/td>\n

\n

0.88<\/span><\/p>\n<\/td>\n

\n

-0.61<\/span><\/p>\n<\/td>\n

\n

0.88<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

X<\/span><\/p>\n<\/td>\n

\n

0.79<\/span><\/p>\n<\/td>\n

\n

0.22<\/span><\/p>\n<\/td>\n

\n

3.64<\/span><\/p>\n<\/td>\n

\n

0.00<\/span><\/p>\n<\/td>\n

\n

0.35<\/span><\/p>\n<\/td>\n

\n

1.23<\/span><\/p>\n<\/td>\n

\n

0.35<\/span><\/p>\n<\/td>\n

\n

1.23<\/span><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u00a0<\/span><\/p>\n

\u00a0<\/p>\n

\u00a0<\/p>\n

\u00a0<\/p>\n

\u00a0<\/p>\n

\u00a0<\/p>\n

\u00a0<\/p>\n

\u00a0<\/p>\n

\u00a0<\/p>\n

\u00a0<\/p>\n

\u00a0<\/p>\n

\u00a0<\/p>\n

\u00a0<\/p>\n

\u00a0<\/p>\n

\u00a0<\/p>\n

The regression equation obtained is:<\/span><\/p>\n

Y = 0.1377 + 0.7897X<\/span><\/b><\/p>\n

The above equation indicates the relationship between Market Return (X) and Shree Cement Ltd Return (Y). The R Square value is 0.2237<\/b>, which means 22.37% <\/b>of the variance in Shree Cement returns is explained by market return, and the remaining 77.63%<\/b> is due to other factors not included in the model. The F value is 13.258<\/b> and its significance value is 0.000686<\/b>, which is less than 0.05, hence the model is statistically significant at 5% level. The p-value of the coefficient is 0.000686<\/b>, which is also less than 0.05, indicating that market return has a significant impact on Shree Cement returns. The intercept is 0.1377<\/b>, which means if market return is 0, the return on Shree Cement Ltd will be 0.1377. The coefficient of market return (Beta) is 0.7897<\/b>, which means for every 1 unit increase in market return, Shree Cement return increases by 0.7897 units<\/b>. The number of observations used in the study is 48<\/b>.<\/span><\/p>\n

\u00a0<\/span><\/p>\n

6. Conclusion:\u00a0\u00a0 <\/span><\/span><\/b><\/p>\n

Since the beta for this company is 0.79, the stock is less volatile than the market and is suitable for long-term investment. <\/span><\/p>\n


7. Reference:<\/b>
<\/span>\u00a0<\/span><\/span>Sharpe, W. F. (1964). Capital asset prices: A theory of market equilibrium under conditions of risk<\/i>. Journal of Finance.<\/span><\/p>\n

Fama, E. F. (1970). Efficient capital markets: A review of theory and empirical work<\/i>. Journal of Finance.<\/span><\/p>\n

\u00a0<\/p>\n

\u00a0<\/p>\n","protected":false},"excerpt":{"rendered":"

Title: Relationship between Nifty 50 and Shree cement ltd Author: Sakshi Haware (65) 1. Introduction:Shree Cement Ltd is one of the leading cement manufacturing companies in India and is known for its strong operational efficiency and cost leadership. The company plays a significant role in the infrastructure and construction sector, contributing to economic growth. It… Continue reading Relationship between Nifty 50 and Shree cement ltd<\/span><\/a><\/p>\n","protected":false},"author":140115,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-24866","post","type-post","status-publish","format-standard","hentry","category-uncategorized","entry"],"_links":{"self":[{"href":"http:\/\/www.sachdevajk.in\/index.php?rest_route=\/wp\/v2\/posts\/24866","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/www.sachdevajk.in\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/www.sachdevajk.in\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/www.sachdevajk.in\/index.php?rest_route=\/wp\/v2\/users\/140115"}],"replies":[{"embeddable":true,"href":"http:\/\/www.sachdevajk.in\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=24866"}],"version-history":[{"count":1,"href":"http:\/\/www.sachdevajk.in\/index.php?rest_route=\/wp\/v2\/posts\/24866\/revisions"}],"predecessor-version":[{"id":24867,"href":"http:\/\/www.sachdevajk.in\/index.php?rest_route=\/wp\/v2\/posts\/24866\/revisions\/24867"}],"wp:attachment":[{"href":"http:\/\/www.sachdevajk.in\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=24866"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/www.sachdevajk.in\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=24866"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/www.sachdevajk.in\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=24866"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}