Relationship of Nifty 50 with ACC Limited

1. Introduction

This research explores the econometric evolution of ACC Limited’s risk premiums, examining how its expected returns align with the NIFTY 50 benchmark. While traditional financial theory suggests a degree of market synchronization, this study specifically tests the sensitivity of ACC—a major player in the Indian cement industry—to broader market volatility. The study validates a Capital Asset Pricing Model (CAPM) framework while ensuring residuals are evaluated for serial correlation and heteroscedasticity. By considering the structural shifts within the infrastructure and construction sectors, the analysis provides a refined outlook on ACC’s performance, evaluating its position as a strategic investment relative to its market peers.

2. Objective

• To calculate the Beta (beta) of ACC Limited.

• To observe the statistical significance of ACC’s returns in relation to the NIFTY 50 index.

3. Literature Review

• • Fama and French (2004) revisited the CAPM, noting that while $beta$ is a primary measure of market risk, its explanatory power varies significantly across different sectors and timeframes. In the context of your report, this justifies why ACC may show a low $R^2$ if the market is currently driven by non-systematic factors like infrastructure policy or raw material costs.

  • Ginard (2024) conducted an econometric analysis specifically on the premiums of Indian large-cap stocks. He demonstrated that while the NIFTY 50 acts as a broad benchmark, stocks in heavy industries (like ACC) often exhibit “defensive” characteristics during periods of high interest rates, leading to a Beta that is lower than the market average of 1.0.

4. Data Collection

• Data Source: Historical data for NIFTY 50  and ACC Limited  was retrieved from NSE India for the period 01-12-2024 to 30-11-2025.

• Methodology: Weekly Friday closing prices were used to calculate returns.

• Regression: Simple Linear Regression was performed taking Nifty 50 returns as the independent variable (x) and ACC Limited returns as the dependent variable (y).

• 5. Data Analysis
• The regression yielded the following equation for the relationship:
• $$text{ACC Returns} = -0.0627 + 0.1286

  • Beta ($beta$): The coefficient for the NIFTY 50 variable is 0.1286. This indicates a positive but very weak relationship. On average, there is increase in the NIFTY 50 index corresponds to only a 0.1286increase in ACC’s returns.

  • Statistical Significance: The t-statistic is $0.41$ with a p-value of 0.6836. Since the p-value is significantly higher than $0.05$, the relationship is not statistically significant. This implies that NIFTY 50 movements are not a reliable predictor of ACC’s price movements during this period.

  • Explanatory Power: The R-square value is 0.0036, meaning that only 0.36 of the variation in ACC’s returns is explained by the NIFTY 50. The F-statistic significance (0.6836) further confirms that the overall model lacks statistical strength.

6. Conclusion

• The regression analysis indicates that ACC Limited behaves as a non-market-aligned security for the period under study. The estimated beta ($beta = 0.1286$) reflects negligible market sensitivity, suggesting that the stock’s returns move largely independently of systematic market risk.
• With an R-squared value of nearly zero, the returns are driven almost entirely by firm-specific (idiosyncratic) factors or random noise rather than broader market trends. For investors, this suggests that ACC could serve as a potential diversifier in a NIFTY 50-heavy portfolio, as its performance appears uncorrelated with the benchmark index.

7 References

• Kalimuthu, M., & Shreenithi, J. (2021). “Financial Performance Analysis of ACC Cement Limited.” EPRA International Journal of Multidisciplinary Research (IJMR), 7(8), 48-50.

  • Relevance: Analyzes overall performance using ratio analysis (liquidity, profitability, and activity ratios) and working capital changes.

• Kumar, S. (2020). “Profitability Analysis of Cement Companies in India: A Comparative Study of ACC Ltd, Ambuja Cement and UltraTech Cement.” Administrative Development: A Journal of HIPA, VII(2).

  • Relevance: Uses ANOVA and regression to compare profitability indicators across major cement players, providing a benchmark for ACC’s market standing.

• Mishra, A. K. (2019). “Assessment of Consumer Influencing Factors in Decision Making for Selecting Cement Brands.“

  • Relevance: Provides a qualitative look at brand equity and consumer behavior, which explains the “firm-specific factors” that drive ACC’s returns outside of NIFTY 50 movements.