Author – Sakshi Manjrekar
MBA – Finance
ITM Skills University
INTRODUCTION
Solar Industries India Limited is one of India’s leading manufacturers of industrial explosives and explosive initiating systems. Established in 1995 and headquartered in Nagpur, Maharashtra, the company serves core sectors such as mining, infrastructure, construction, and defense. Solar Industries has developed a strong domestic as well as international presence, exporting its products to several countries across Asia, Africa, and Australia.
The company plays a critical role in supporting India’s infrastructure development by supplying high-quality explosive solutions for mining and large-scale construction projects. In addition, Solar Industries has made significant advancements in the defense sector by manufacturing specialized ammunition and explosive products under the Government of India’s “Make in India” initiative. With continuous focus on research, innovation, and capacity expansion, Solar Industries India Limited has emerged as a strategically important company contributing to industrial growth and national security.
OBJECTIVE OF THIS STUDY
The main objective of this study is to calculate the beta of Solar Industries India Limited and to examine the relationship between the stock returns of the company and the movements of the Nifty 50 index. The study also aims to analyze whether the stock is more suitable for short-term or long-term investment based on its systematic risk.
LITERATURE REVIEW
1. Market Risk and Beta Analysis
Sharpe (1964) explained that beta measures the systematic risk of a stock in relation to market movements. A stock with beta greater than one is more volatile than the market, while a beta less than one indicates lower volatility and relatively stable returns.
2. Stock Market Volatility
Fama and French (1992) highlighted that stock returns are influenced by market-wide factors and company-specific fundamentals. Companies operating in capital-intensive industries, such as explosives and infrastructure support, often show moderate sensitivity to market fluctuations.
3. Industrial Sector Performance
Kumar and Singh (2021) observed that industrial manufacturing companies tend to exhibit stable long-term growth due to consistent demand from infrastructure and mining sectors, making them suitable for long-term investors when beta remains below one.
DATA COLLECTION
The historical data of Solar Industries India Limited and Nifty 50 was collected from the official website of NSE India. Friday closing prices were selected to remove daily market noise, and weekly returns were calculated. Weekly returns of Nifty 50 were considered as the independent variable (X), while weekly returns of Solar Industries India Limited were considered as the dependent variable (Y). Regression analysis was conducted by regressing Y on X.
DATA ANALYSIS (As per Excel Data)
Intercept (a) = -0.083998233
Beta Coefficient (b) = 0.098868515
Regression Equation:
y = -0.083998233 + 0.098868515x
The beta value of 0.098868515 indicates that Solar Industries India Limited is less volatile compared to the overall market.
The t-statistic for beta is 2.692061285 with a p-value of 0.009689883. Since the p-value is less than 0.05 and 0.01, the beta coefficient is statistically significant.
R-square = 0.322387
Number of observations = 51
F-value = 7.24719396
The R-square value indicates that approximately 32% of the variation in Solar Industries India Limited’s returns is explained by movements in the Nifty 50 index, while the remaining variation is due to other firm-specific factors.
CONCLUSION
The study concludes that Solar Industries India Limited has a positive but low beta value, indicating limited sensitivity to market movements. Since the beta is less than one, the stock is considered suitable for long-term investment, especially for investors seeking relatively stable returns with lower market risk.
REFERENCE EXPLANATION
1. Sharpe, W. F. (1964)
This study introduced the Capital Asset Pricing Model (CAPM) and explained the concept of beta as a measure of systematic risk, forming the theoretical base of this research.
2. Fama, E. F., & French, K. R. (1992)
This research highlighted the importance of market-related factors in explaining stock returns and supports the use of regression analysis in market studies.
3. Kumar, R., & Singh, A. (2021)
This study provided insights into the performance and risk characteristics of industrial sector companies, supporting the long-term investment suitability of firms with low beta values.