TITLE : Reliance Industries Limited
Author : Rutuja Pawar
Introduction
Analysis of Reliance Industries Limited data, specifically focusing on weekly returns and their relationship with the Nifty 50 index. The data includes weekly closing prices for both Reliance Industries and the Nifty 50, along with calculations of weekly returns. The analysis employs regression statistics to model the relationship between these two variables, presenting key metrics such as Multiple R, R-Square, Adjusted R-Square, Standard Error, and the number of observations. The output also includes an ANOVA table, which helps in understanding the variance in the data and the significance of the regression model. Furthermore, the file provides coefficients, standard errors, t-statistics, p-values, and confidence intervals for the intercept and the X Variable 1, which likely represents the Nifty 50’s influence on Reliance Industries’ returns. The analysis culminates in a regression equation and the identification of the intercept, slope, and beta values, offering insights into the nature and strength of the relationship between the two financial entities.
Objective :
To find the beta of Reliance Industries Limited and it’s significance.
Literature Review :
Dr. G. Lakshmi et.al (2021), conducted a study titled A Study on the Financial Analysis of Reliance Industries Limited, analyzing the company’s financial performance over five years. The study primarily focuses on liquidity, profitability, and turnover rates using ratio analysis. The findings indicate that while RIL has shown consistent profitability growth and efficient asset utilization, its liquidity ratios remain below the ideal benchmarks, suggesting potential short-term financial challenges. The study highlights that RIL effectively manages inventory and receivables, contributing positively to its overall financial health. However, the authors recommend that the company should implement strategies to improve its liquidity position to ensure financial stability. They suggest optimizing working capital management and reassessing credit policies to strike a balance between liquidity and profitability. By doing so, RIL can maintain its competitive edge while strengthening its financial resilience.
Impact of Reliance Industry Stock Price on NIFTY 50 – Granger Causality Test” by Abhijit Biswas (2018): This study examines the causal relationship between RIL’s stock prices and the NIFTY 50 index using the Granger causality test. Analyzing daily closing prices from 2008 to 2018, the research indicates that changes in RIL’s stock price can predict movements in the NIFTY 50, suggesting a unidirectional influence from RIL to the index.
Data Collection :
On Reliance Industries Limited data and Indices Nifty 50. The data includes the date, day, close, and weekly returns (%) for both Reliance Industries Limited and Indices Nifty 50. The weekly returns (%) data consists of 47 observations.
Data Analysis :
Equation: RIL = Y = (-1.28) + (-0.62) Nifty 50
Interpretation :
A linear regression was performed to examine the relationship between X Variable 1 and the dependent variable, using a sample of 47 observations. The regression model showed a very weak positive relationship, with a Multiple R of 0.13, indicating that the predictor accounts for only 2% of the variance in the dependent variable (R Square = 0.02). The Adjusted R Square was 0.00, suggesting that the model does not explain the variance well, even when accounting for the number of predictors. The Standard Error of the regression was 7.82. The ANOVA results indicated that the regression model was not statistically significant (F(1, 45) = 0.82, p = 0.37). The coefficient for X Variable 1 was -0.62, with a standard error of 0.69, leading to a t-statistic of -0.91 and a p-value of 0.37. The 95% confidence interval for the coefficient ranged from -2.00 to 0.76, indicating that zero is included within this interval. The intercept was -1.28, with a standard error of 1.15, a t-statistic of -1.12, and a p-value of 0.27. The 95% confidence interval for the intercept ranged from -3.59 to 1.03. In conclusion, the analysis suggests that X Variable 1 is not a significant predictor of the dependent variable in this model.
Conclusion :
A regression analysis of Reliance Industries Limited data. The analysis includes weekly returns, regression statistics, ANOVA, and coefficients. The regression equation is Y = (-1.28) + (-0.62)(X). The intercept is -1.28, the slope is -0.62, and Beta is -0.62.
Reference:
Lakshmi, G., Banu, et al (2021). A study on the financial analysis of Reliance Industries Limited. International Journal of Advanced Research, 9(05), 149-161.)
Biswas, A. (2018). Impact of Reliance Industry stock price on NIFTY 50 – Granger causality test. ResearchGate. https://www.researchgate.net/publication/329058963_Impact_of_Reliance_Industry_Stock_Price_on_NIFTY_50-Granger_Causality_Test