{"id":23270,"date":"2025-12-22T08:37:15","date_gmt":"2025-12-22T03:07:15","guid":{"rendered":"http:\/\/www.sachdevajk.in\/?p=23270"},"modified":"2025-12-22T08:37:15","modified_gmt":"2025-12-22T03:07:15","slug":"relationship-of-nifty-50-with-supreme-industries-ltd","status":"publish","type":"post","link":"http:\/\/www.sachdevajk.in\/?p=23270","title":{"rendered":"Relationship of Nifty 50 with Supreme Industries Ltd"},"content":{"rendered":"

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Relationship of Nifty 50 with Supreme Industries Ltd.<\/span><\/u><\/b><\/p>\n

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Author<\/span><\/strong><\/h2>\n

Sahil Phonde<\/strong>
MBA (Operations and Supply Chain Management)
ITM Skills University<\/p>\n

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INTRODUCTION<\/span><\/u><\/b><\/p>\n

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Supreme Industries Limited<\/span><\/strong> is one of India\u2019s leading plastic processing companies, established in 1942. The company manufactures a wide range of plastic products including piping systems, packaging products, consumer products, and industrial components. Supreme Industries is known for its focus on quality, innovation, and sustainability, supported by advanced manufacturing facilities across India. Its strong distribution network and diversified product portfolio have enabled consistent growth and market leadership.<\/b><\/span><\/p>\n

OBJECTIVES OF THIS STUDY<\/span><\/u><\/u><\/h1>\n

To calculate the beta of <\/span>Supreme Industries Limited<\/span><\/strong> and observe its significance.<\/span><\/p>\n

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LITERATURE REVIEW<\/span><\/u><\/b><\/u><\/b><\/p>\n

Previous studies indicate that consumer purchase decisions<\/b> are influenced by multiple factors including price, product quality, brand image, service quality, and promotional activities<\/b>. Price plays a significant role as consumers assess fairness and value before making purchase decisions. Research highlights that product quality and durability<\/b> strongly affect customer satisfaction and repeat purchases. Service quality and after-sales support<\/b>, including warranty, enhance consumer trust and brand loyalty. Brand image has been found to mediate the relationship between price and purchase intention, strengthening consumer confidence. Studies also show that word-of-mouth communication<\/b> is often more influential than traditional advertising. Availability and distribution efficiency contribute positively to purchase convenience and decision-making. Demographic variables such as age, gender, and education are often found to have limited influence<\/b> on buying behavior. In durable goods markets, safety and material standards are critical evaluation criteria. Overall, existing literature suggests that functional attributes and brand credibility<\/b> are more decisive than demographic factors in shaping consumer purchasing behavior.<\/span><\/p>\n

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Previous studies highlight that stock prices and firm performance are influenced by both market movements and firm-specific factors<\/b>. Market indices such as the Nifty 50 are often used as benchmarks to explain equity price behavior, though their explanatory power varies across firms. Research suggests that companies with strong fundamentals may show only partial dependence on market indices. Studies on manufacturing firms emphasize the role of cost efficiency, operational performance, and profitability<\/b> in determining firm value. Cost structure and effective cost control are found to enhance competitiveness in the plastic manufacturing industry. Scholars note that macroeconomic indicators influence stock prices, but firm-level strategies moderate this impact. Empirical evidence shows that market indices explain a limited portion of stock price variation. Firm-specific risks and managerial efficiency account for significant price movements. Regression analysis is widely used to test market\u2013stock relationships. Overall, literature supports combining market indicators with company fundamentals<\/b> for better financial analysis.<\/span><\/p>\n

DATA COLLECTION<\/span><\/u><\/b><\/p>\n

The historical data of <\/span>Supreme Industries Limited<\/span><\/b> and nifty 50 index data was downloaded from the website from the period 1\/12\/24 to 30\/11\/25. The data was manipulated to get Friday closing prices. <\/span><\/p>\n

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DATA ANALYSIS<\/span><\/u><\/b><\/p>\n

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The regression model is statistically significant, indicating that approximately 23.3% of the variance in the dependent variable (Y) can be explained by the independent variable (X).<\/span><\/p>\n

Regression Equation\u00a0The linear regression equation derived from the coefficients is:\u00a0(Y=0.9133+1.1230X)<\/span><\/p>\n

This means that for every one-unit increase in the independent variable (X), the dependent variable (Y) is expected to increase by approximately 1.12 units.\u00a0Interpretation\u00a0Model Fit R Square<\/span><\/p>\n

The R-Square value of 0.2335 (23.35%) indicates that the independent variable accounts for roughly a quarter of the variation in the dependent variable. <\/span><\/p>\n

The remaining 76.65% is influenced by other unmeasured factors or random error.Overall Significance (F-Value & P-value): The P-value for the F-statistic (0.000504744) is very small (much less than the standard 0.05 threshold). This confirms that the overall regression model is statistically significant and reliable.Individual Predictor Significance (t-Stat & P-value): <\/span><\/p>\n

The independent variable X Variable 1 is a significant predictor of Y, with a P-value of 0.00050474. The high t-stat value (3.74) confirms the coefficient is significantly different from zero.\u00a0Conclusion<\/span><\/p>\n

p value is 0.00050474 <\/span><\/p>\n

No of observations = 50<\/span><\/p>\n

R square = 0.233415747<\/span><\/p>\n

F \u2013 value = <\/span>14.00645<\/span><\/p>\n

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CONCLUSION<\/span><\/u><\/b><\/p>\n

Based on the regression analysis between Nifty 50<\/b> and the equity price of Power Grid Corporation of India Ltd<\/b>, the following conclusions can be drawn:<\/span><\/p>\n