Relationship of Nifty with Rail Vikas Nigam Limited
Author Name: Rohan Dhivar
Introduction to Rail vikas nigam Limited
Rail Vikas Nigam Limited (RVNL) is a public sector enterprise under the Ministry of Railways, established in 2003 to accelerate the development and modernization of railway infrastructure in India. It focuses on executing projects like the construction of new rail lines, electrification, station redevelopment, and capacity enhancement of the Indian Railways network. RVNL also works on projects related to safety, signalling, and freight corridors. Fully owned by the Government of India, it aims to improve connectivity, efficiency, and safety across India’s rail network.
Objective
The objective of this study is to determine the beta value of Rail vikas nigam Limited relative to the Nifty 50 index. Beta measures the stock’s volatility compared to the market. This analysis will help investors assess the risk associated with Rail vikas nigam Limited stock and make informed investment decisions.
Literature Review
1. Infrastructure Stocks and Market Performance
The performance of infrastructure stocks like RVNL often correlates with broader economic indicators. Infrastructure companies are heavily influenced by government policies, infrastructure development spending, and national economic growth, which can be mirrored in the movements of the Nifty 50 Index. Kumar and Gupta (2018) noted that Indian infrastructure stocks generally align with macroeconomic trends, especially those reflected in stock market indices like Nifty. These stocks show a positive correlation during periods of government investment in infrastructure projects, which boosts both market sentiment and investor confidence.
2. Stock Market Correlation with Nifty Index
Several studies have analyzed the correlation between sectoral stocks and broad market indices. According to Raj & Patel (2020), stocks like RVNL, which are linked to the government’s infrastructure initiatives, tend to experience movements in sync with Nifty due to similar responses to fiscal policies, budget allocations, and national economic performance. When Nifty rises due to positive economic sentiment, RVNL often sees an uptick as well, particularly if the government announces new infrastructure projects or funding for railways.
Data Collection
Data for Rail vikas nigam Limited and Nifty 50 was downloaded for the period from 1st January 2024 to 31st December 2024. The data was manipulated to calculate the Friday closing prices for both indices. The Nifty 50 was represented as X and Rail vikas nigam Limited as Y. A linear regression analysis was performed where Y was regressed on X.
Data Analysis
Equation: RVNL=2.06 + 1.917 Nifty50
Interpretation:
The regression equation describes the relationship between Nifty50 (X) and RVNL’s share price (Y), indicating that RVNL’s share price is the dependent variable, while Nifty50 is the independent variable. The positive coefficient of 1.917 suggests that for every unit increase in Nifty50, RVNL’s share price is expected to increase by 1.917 units.
With 46 observations ((N = 46)), the (R^2) value is 0.08, implying that approximately 8% of the variation in RVNL’s share price can be explained by changes in Nifty50. The F-value for the model is 4.27, and the p-value for the slope is 0.04, which is less than the conventional threshold of 0.05. This indicates that the relationship between Nifty50 and RVNL’s share price is statistically significant at the 5% level. Consequently, this model provides evidence to suggest a significant linear relationship between Nifty50 and RVNL’s share price.
Conclusion:
Since the Beta (1.917226) is greater than 1, it indicates that Rail Vikas Nigam Limited is preferable for Short-term investment.
References
Kumar, S., & Gupta, R. (2018). Macroeconomic factors and infrastructure stocks: A study of the Indian context. Journal of Financial Economics, 22(3), 213-230.
Raj, M., & Patel, D. (2020). Stock market performance and its correlation with market indices in India: Focus on infrastructure stocks. Indian Journal of Economics and Business, 34(2), 78-92.