Relationship of Nifty 50 with Shree Cements Ltd.

Relationship of Nifty 50 with Shree Cements Ltd.

Author: Sachin Rajan Gupta

 

About the Company:

Shree Cement is an Indian cement manufacturer, founded in Beawar, Rajasthan, in 1979. Now headquartered in Kolkata, it is India’s third largest cement producer and second largest cement company by market capitalisation. Shree Cement has moved in the last two decades from having 2 million tonne (mt) production capacity to becoming the country’s third largest cement player, with an installed capacity of 43.3 mt in India and 47.4 mt overseas. It also produces and sells power under the name Shree Power (Captive Power Plant) and Shree Mega Power (Independent Power Plant).

Since 2006, it has more than quadrupled its production capacity both by expanding into new areas and increasing the capacities of the existing plants. Shree Cement has been ranked 4th in 2017 Responsible Business Rankings developed by IIM Udaipur.

 

Objective:

To calculate the beta of Shree Cements Ltd. and its significance.

Views & Reviews:

Lead in creating prosperity and happiness for all stakeholders through innovation and sustainable practices.

As an organisation, we aim to be a blue-chip greenest building material solutions company in India with industry leading performance benchmarks via strong brands, leading innovation and best-in-class people. Our vision is to spread happiness amongst everyone connected with our ecosystem and create wealth for all stakeholders where we operate.

It has been four decades of our contribution towards infrastructure development of the country. The journey involved many crests and troughs, testing our endurance and perseverance. Over the years, the business ecosystem has evolved considerably, and we have witnessed various externalities recasting the business environment. As rightly stated by our philosophy, ‘आ नो भद्रा: क्रतवो यन्तु व वश्वतः, we are imbibing noble thoughts from all over the world into our business, bringing in prosperity and excellence as we grow.

Pushing our limits to reimagine our future, we are growing with a renewed vigour while taking our sustainability and business commitments to greater heights. The purpose of Shree’s existence is about shared values. Our spirit of sharing and mutual growth is reflected through relationships we have nurtured with our stakeholders throughout our journey.

Looking forward to a year of well-being, collective growth, and success.

Data Collection:

Data has been downloaded from NSE historical data reports from 1st Feb 2023 to 31st Jan 2024.

Weekly returns are calculated where;

Independent Variable(X) = Weekly return of Nifty 50

Dependent Variable (Y) = Weekly return of Shree Cements Ltd

Equation of regression will be:

Weekly return of Shree Cements Ltd. = -0.142291829 + 0.551422267(Weekly Return of Nifty 50) + Error

This regression analysis aims to understand the relationship between the weekly return of Nifty 50 (independent variable, X) and the weekly return of Shree Cements Ltd. (dependent variable, Y).

 

Regression Statistics:

✓ Multiple R: The correlation coefficient between the Nifty 50 and Shree Cements weekly data is approximately 0.2232, indicating a weak positive linear relationship.
✓ R Square (R²): This value suggests that only around 4.98% of the variability in Shree Cements’ weekly performance can be explained by changes in the Nifty 50.
✓ Adjusted R Square: This adjusts R Square for the number of predictors in the model. It’s similar to R Square but penalizes additional predictors. Here, it’s slightly lower than R Square, indicating the addition of the predictor might not significantly improve the model’s fit.
✓ Standard Error: Measures the average difference between the observed values and the predicted values by the model. In this case, it’s approximately 1.6416.
✓ Observations: Number of data points available, which is 51.

 

ANOVA:

✓ The analysis of variance (ANOVA) table breaks down the variance into components attributable to the regression model and residual error.
✓ The F-statistic tests the overall significance of the regression model. A higher F-value and a lower p-value indicate greater significance. Here, the F-value is 2.5691 with a p-value of 0.1154, suggesting the regression model might not be statistically significant at conventional significance levels (e.g., α = 0.05).
✓ The “Regression” row indicates the variability explained by the regression model, while the “Residual” row represents unexplained variability.

Coefficients:

✓ Intercept: The intercept is approximately -0.1423. It represents the estimated value of Shree Cements when the Nifty 50 value is zero. However, since stock prices don’t usually start from zero, this interpretation might not be meaningful.
✓ X Variable 1 (Nifty 50): The coefficient associated with the Nifty 50 is 0.5514. This suggests that, on average, for every unit increase in the Nifty 50, the Shree Cements’ performance increases by approximately 0.5514 units. However, since the p-value is 0.1154, it’s not statistically significant at conventional levels.

Overall, while there appears to be a weak positive relationship between the Nifty 50 and Shree Cements’ weekly performance, the regression model’s statistical significance is questionable, as indicated by the p-values. More data or additional variables might be necessary to improve the model’s explanatory power.

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