Research Methodology
Report Writing
Title: – Relationship of Nifty with Apar Industries Ltd
Prepared By: Arya Patil
ROLL NO: – 021331025076
BATCH: – Operations and Supply Chain Management
INTRODUCTION
Apar Industries Limited is a leading Indian manufacturer and supplier of conductors, specialty oils, cables, and polymers, serving power transmission, telecom, renewable energy, and industrial sectors.
The company has a strong presence in both domestic and international markets and is known for its technological capabilities and diversified product portfolio.
Given its exposure to infrastructure development and capital markets, analysing the relationship between Apar Industries’ stock returns and broader market movements such as the NIFTY index is important for understanding its market sensitivity.
OBJECTIVE
• To calculate the beta (β) of Apar Industries Ltd.
• To examine the impact and significance of NIFTY’s weekly returns on the weekly returns of Apar Industries Ltd.
DATA COLLECTION
Secondary data has been used for the study.
Historical weekly closing price data of Apar Industries Ltd. and NIFTY index was collected from publicly available financial sources.
The study covers 48 weekly observations, and weekly returns were computed based on Friday closing prices.
LITERATURE REVIEW
Previous studies suggest that stock returns of infrastructure and manufacturing companies are influenced by overall market movements along with firm-specific factors such as operational efficiency, sectoral demand, and macroeconomic conditions.
Companies with diversified operations often exhibit moderate to high sensitivity to market indices, depending on their exposure to cyclical industries and capital expenditure trends.
DATA ANALYSIS
Regression Equation:
y=1.6727x+0.6297
Where:
• 𝑦
y = Weekly Return of Apar Industries Ltd.
• 𝑥
x = Weekly Return of NIFTY
The regression equation indicates a positive and moderately strong relationship between NIFTY’s weekly returns and Apar Industries’ weekly returns. A 1% increase in NIFTY’s weekly return leads to an average 1.67% increase in Apar Industries’ weekly return.
Number of Observations = 48
The analysis is based on 48 weekly observations, which is sufficient for short-term return-based regression analysis.
t-stat for β = 3.254
The t-statistic value is high, indicating that NIFTY returns have a meaningful influence on Apar Industries’ returns.
p-value for β = 0.0021
Since the p-value is less than 0.05 and 0.01, the beta coefficient is statistically significant, confirming that market movements significantly affect Apar Industries’ stock returns.
R² = 0.1871
The R² value shows that approximately 18.7% of the variation in Apar Industries’ weekly returns is explained by NIFTY’s weekly returns.
The remaining 81.3% variation is due to firm-specific, industry-related, and other macroeconomic factors not included in the model.
F-statistic = 10.595
Significance F = 0.0021
Since the Significance F value is less than 0.05, the overall regression model is statistically significant, indicating that the model provides a better fit than a model with no independent variables.
CONCLUSION
The results indicate that Apar Industries Ltd. has a beta greater than 1, suggesting that the stock is more volatile than the market.
The positive and statistically significant beta implies that Apar Industries tends to outperform the market during bullish phases but may underperform during market downturns.
Therefore, the stock may be suitable for investors with higher risk tolerance, particularly during periods of positive market sentiment.
REFERENCES
• National Stock Exchange (NSE) historical data
• Financial literature on market risk and beta analysis