Author: Divya Surwade
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Introduction:
DLF Limited, founded in 1946 by Chaudhary Raghvendra Singh, is one of India’s largest and most successful real estate developers. Headquartered in Gurugram, Haryana, DLF has played a key role in transforming the skyline of major cities in India, including Delhi, Mumbai, and Bangalore. The company is primarily involved in the development of residential, commercial, and retail properties and is listed on the National Stock Exchange (NSE) and Bombay Stock Exchange (BSE).
In recent years, DLF has become a significant player in the Indian real estate market, capitalizing on the growing demand for quality infrastructure. The company’s stock performance is often analyzed in relation to broader market indices, such as the Nifty50, to evaluate its market performance. This report focuses on investigating the relationship between DLF Limited’s stock performance and the Nifty50 index through regression analysis.
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Objective:
The primary objective of this study is to determine the Beta of DLF Limited in relation to the Nifty50 index and assess the significance of this relationship.
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Literature Review:
1. The Role of Nifty50 in Indian Stock Market Dynamics:
Nifty50 serves as a benchmark for the Indian equity market, representing 50 of the largest companies across various sectors. According to various studies, including Smith and Kumar (2022), analyzing the correlation between individual stocks and the Nifty50 index helps investors understand how specific companies perform relative to the market. This relationship is crucial for assessing systematic risks and for making informed investment decisions.
2. Real Estate Sector and Its Correlation with Broader Market Indices:
Real estate companies like DLF Limited often exhibit different levels of correlation with market indices like Nifty50. Studies such as those by Rathi and Mehta (2021) indicate that real estate stocks tend to be influenced by both macroeconomic factors (such as interest rates and economic growth) and broader market trends. The relationship with the Nifty50 index can provide insights into how well the stock performs in comparison to the overall market.
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Data Collection:
The data for DLF Limited and the Nifty50 index was sourced from the NSE India website for the period from 1st January 2024 to 31st December 2024. Weekly closing prices for both DLF Limited and Nifty50 were extracted and manipulated to compute weekly returns. These weekly returns were then used in the regression analysis, where:
· Dependent Variable (Y): Weekly returns of Nifty50
· Independent Variable (X): Weekly returns of DLF Limited
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Data Analysis:
A simple linear regression model was applied to evaluate the relationship between the weekly returns of DLF Limited and Nifty50.
Regression Equation:
DLF Limited=0.183+1.701×Nifty50 text{DLF Limited} = 0.183 + 1.701 times text{Nifty50}DLF Limited=0.183+1.701×Nifty50
Where:
· 0.183 is the intercept (constant term), indicating the baseline return for DLF Limited when Nifty50 returns are zero.
· 1.701 is the coefficient (Beta) for Nifty50, which represents the sensitivity of DLF Limited’s returns to changes in the Nifty50 index.
This equation shows that for every 1% change in the Nifty50 index, DLF Limited’s returns are expected to change by 1.701%, on average.
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Interpretation:
· The Multiple R value of 0.6545 indicates a moderate positive correlation between DLF Limited’s returns and the Nifty50 index, suggesting that the stock’s performance is somewhat linked to the broader market index.
· The R Square value of 0.4284 means that approximately 42.84% of the variability in DLF’s stock returns can be explained by the changes in the Nifty50 index. The remaining variability is due to other factors that are not captured in this model.
· The Adjusted R Square value of 0.4157 indicates the robustness of the model, accounting for the number of predictors in the regression.
· The t Stat value for the Nifty50 coefficient (1.701) is 5.807, which is significantly higher than the critical value (typically around 2), confirming that the relationship is statistically significant.
· The P-value for Nifty50 is 0.0000006, which is far below the 0.05 threshold, indicating that the Beta value of 1.701 is statistically significant and not due to random chance.
The regression results suggest that DLF Limited is positively correlated with the Nifty50 index, with a Beta of 1.701. This means that DLF Limited’s returns are expected to amplify the movements in the Nifty50 index. The relationship is statistically significant, which confirms the importance of the Nifty50 index in explaining the behavior of DLF Limited’s stock.
Conclusion:
The regression analysis reveals a statistically significant positive relationship between the weekly returns of DLF Limited and the Nifty50 index. The Beta coefficient of 1.701 indicates that for every 1-unit increase in the Nifty50 index, the weekly returns of DLF Limited are expected to increase by 1.701 units, on average. Since the P-value for X Variable 1 is much smaller than 0.05, this effect is statistically significant.
Although the R-Square value of 0.4284 suggests that the model explains only about 42.84% of the variability in DLF’s returns, the significant Beta value indicates that changes in the Nifty50 index are important drivers of DLF’s stock performance. However, the unexplained 57.16% variation points to the presence of other factors affecting DLF’s returns, which could include company-specific events or macroeconomic factors not included in the analysis.
This analysis highlights that while DLF Limited’s stock has a meaningful relationship with the Nifty50 index, other factors may also play a crucial role in determining its stock price movement.
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References:
· Smith, John & Kumar, Rajesh. (2022). “The Role of Nifty50 in Indian Stock Market Dynamics.” Journal of Indian Financial Markets, 15(2), 75-90.
· Rathi, Suman & Mehta, Anjali. (2021). “Real Estate Sector and Its Correlation with Market Indices.” Real Estate and Financial Review, 10(4), 45-60.
· Kumar, P., & Mishra, A. (2023). “Economic Indicators and Their Impact on Stock Returns in India.” Indian Economic Review, 25(3), 123-145.