RELATIONSHIP OF NIFTY WITH SUZLON LIMITED
AUTHOR – Subhodeep Pal
Introduction
Suzlon Group is a global leader in renewable energy, specializing in wind power solutions, providing end-to-end services from manufacturing wind turbine generators (WTGs) and components in-house to installation and maintenance, with a strong presence in India and internationally, focusing on sustainable development and technological innovation. Founded in India in 1995 by Tulsi Tanti, Suzlon is a vertically integrated company known for pioneering wind energy in India and offering integrated wind-solar hybrid solutions, backed by extensive R&D and a large service portfolio
Objective
To calculate the Beta of Suzlon with respect to Nifty 50 and examine its statistical significance in order to understand the systematic risk associated with Suzlon shares.
Literature Review
Understanding the relationship between individual stock returns and market movements is a central theme in financial research. The foundation of this inquiry lies in the Capital Asset Pricing Model (CAPM), which posits that a stock’s expected return is a linear function of its sensitivity to broader market risk, typically measured by beta (β) (Sharpe, 1964; Lintner, 1965). According to CAPM, a higher beta implies greater responsiveness to market fluctuations, and beta estimates provide insights into systematic risk exposure relative to the market.
Subsequent empirical literature has examined the predictive power and stability of beta estimates. These findings suggest that for many stocks, especially in emerging markets, idiosyncratic factors may dominate systematic risk influences.
Research specific to emerging markets, such as India, underscores distinct market dynamics compared to developed markets. Bekaert and Harvey (2002) documented those emerging markets exhibit higher volatility, lower integration with global markets, and greater influence from country-specific events. In this context, stock returns often show weaker correlations with benchmark indices. Studies focusing on Indian equities, including Rangarajan and Sridhar (2017), confirm that individual stocks frequently deviate from expected CAPM relationships, largely due to firm-level news, sectoral trends, and liquidity effects.
Data Collection
Historical data for Suzlon Limited and Nifty 50 was collected from www.nseindia.com for the period 01-12-2024 to 30-11-2025.
Friday closing prices were considered.
Weekly returns were calculated.
Nifty 50 weekly returns were treated as the independent variable (X).
Suzlon Limited weekly returns were treated as the dependent variable (Y).
A simple linear regression was conducted by regressing Y on X.
Data Analysis
Regression Equation
[Suzlon]Y = -39.4655 + [ Nifty50] 0.8911
Regression Statistics
· Beta (Slope coefficient) = 0.8911
· Intercept = –39.4655
· t-Statistic (Beta) = 0.9542
· p-value (Beta) = 0.34497
· Number of observations (N) = 48
· R² = 0.0194 (= 1.94%)
· F-statistic = 0.9105
Interpretation (Quick Insight)
· The slope coefficient (β = 0.8911) is not statistically significant (p-value > 0.05).
· R² = 1.94% indicates the independent variable explains very little variation in the dependent variable.
· The F-statistic also suggests the overall regression model is not statistically significant.
Interpretation
The regression analysis examining the relationship between Suzlon Energy (Y) and the NIFTY 50 index (X) indicates a positive but weak association between the stock and the broader market. The estimated beta coefficient of 0.89 suggests that Suzlon generally moves in the same direction as the NIFTY 50, but with slightly lower sensitivity to market movements. However, this relationship is not statistically significant, as indicated by a low t-statistic (0.95) and a high p-value (0.345). The R² value of 1.94% further highlights that movements in the NIFTY 50 explain only a very small portion of the variation in Suzlon’s stock performance. This implies that Suzlon’s price behavior is largely influenced by company-specific and sector-specific factors, such as financial restructuring, order inflows, renewable energy policy developments, and investor sentiment, rather than by overall market trends. The low F-statistic also confirms that the regression model as a whole lacks explanatory power.
Conclusion
In conclusion, the regression results show that Suzlon Energy does not have a strong or statistically significant dependence on the NIFTY 50 index. While the direction of movement is positive, the market index fails to meaningfully explain Suzlon’s stock fluctuations. Therefore, Suzlon should not be viewed as a market-driven stock; instead, investors and analysts should focus more on fundamental company performance and sector dynamics when evaluating its future prospects.
References
Sharpe, W. F. (1964). Capital Asset Prices: A Theory of Market Equilibrium under Conditions of Risk. Journal of Finance.
Lintner, J. (1965). The Valuation of Risk Assets and the Selection of Risky Investments in Stock Portfolios and Capital Budgets. Review of Economics and Statistics.