Author – Piyush Chhattani
Introduction – Pidilite Industries Limited is India’s leading manufacturer of adhesives and construction chemicals, with a dominant market position in the organized adhesives segment through its flagship brand Fevicol. Established in 1959, the company has evolved into a diversified player across consumer and industrial adhesives, construction chemicals, art materials, and industrial resins, serving both retail and institutional markets. With a robust pan-India distribution network and consistent revenue growth, Pidilite represents a significant player in India’s building materials and specialty chemicals sector. This study analyses Pidilite’s stock performance against the Nifty 50 index to understand its market sensitivity and systematic risk profile during the sample period.
Objective – Calculation Of Beta And Observe its significance.
Literature Review –
· Sharpe (1964) introduced the Capital Asset Pricing Model (CAPM), establishing beta as a measure of systematic risk that captures an asset’s sensitivity to market movements. This framework provides the theoretical foundation for analysing the relationship between individual stock returns and market index returns.
· Fama and French (1992) demonstrated that beta alone explains only a modest portion of stock return variations, with firm-specific factors contributing significantly to return behaviour. This finding is consistent with the low R-squared observed in single-factor market models, suggesting additional variables may be necessary for comprehensive return prediction.
Data Collection – Historical Data Of Pidilite Industries And Nifty50 was downloaded from NSE India.com Friday closing prices were found and weekly returns were calculated. Weekly returns of nifty50 was taken as x and weekly returns of Pidilite Industries taken as y. Y was regressed on x.
Data Analysis – This study uses OLS regression to examine the relationship between Pidilite Industries’ weekly stock returns and Nifty 50 index weekly returns over 47 weeks. Weekly returns were calculated using Friday closing prices for both variables.
1. Regression Equation –
The estimated regression equation is:
Pidilite Weekly Returns = 0.0263 + 2.4990 × Nifty 50 Weekly Returns
The beta coefficient of 2.4990 shows Pidilite has high market sensitivity. For every 1% change in Nifty 50, Pidilite’s returns change by approximately 2.50% in the same direction. Since beta > 1, Pidilite is a high-volatility stock. The intercept of 0.0263 represents expected weekly return when market return is zero.
2. T-Test Analysis –
The t-statistic for beta is 2.122 with p-value of 0.0394. Since p-value < 0.05, I reject the null hypothesis (H₀: β = 0), confirming a statistically significant positive relationship between Pidilite’s and Nifty 50’s returns. The 95% confidence interval [0.127, 4.871] indicates the true beta lies within this range. The intercept’s p-value of 0.242 shows it is not statistically significant.
3. F-Statistic –
The F-statistic is 4.502 with p-value of 0.039 (< 0.05), confirming the overall regression model is statistically significant.
4. Model Fit –
The R-squared value of 0.091 indicates only 9.1% of Pidilite’s return variation is explained by Nifty 50 movements. This low R-squared suggests 91% of variation comes from firm-specific factors like company fundamentals, raw material costs, and industry dynamics rather than market movements alone.
5. Price and Demand Implications –
Pidilite’s high beta of 2.50 means during bull markets, the stock rises 2.5 times faster than the market, attracting aggressive investors. During bear markets, it falls more sharply, deterring risk-averse investors. This creates cyclical demand – high during optimistic periods, low during downturns – confirming Pidilite is viewed as a growth-oriented, high-risk investment.
Conclusion -This regression analysis reveals Pidilite Industries exhibits significant systematic risk (β = 2.50, p < 0.05), amplifying Nifty 50 movements by 2.5 times, though 91% of return volatility stems from firm-specific factors..
Reference –
Fama, E. F., & French, K. R. (1992). The cross-section of expected stock returns. The Journal of Finance, 47(2), 427–465. https://doi.org/10.2307/2329112
Sharpe, W. F. (1964). Capital asset prices: A theory of market equilibrium under conditions of risk. The Journal of Finance, 19(3), 425–442. https://doi.org/10.2307/2977928