Author: Hetanshi Nilesh Gori.
Introduction: Hindustan Unilever Limited (HUL) is one of India’s leading fast-moving consumer goods (FMCG) companies and a subsidiary of Unilever. Established in 1933, HUL has a strong presence across home care, personal care, foods, and refreshments. The company serves millions of consumers through an extensive manufacturing and distribution network spread across India. With a focus on sustainability and innovation, HUL plays a significant role in shaping India’s FMCG supply chain and consumer markets.
Objective: To calculate Beta (β) of Hindustan Unilever Limited and observe it’s significance.
Literature Review:
Packaging strategies: Outlook on Consumer Buying Behaviour for FMCG Products
Harleen Mahajan and Jignesh Vidani (2023) said that, in this highly competitive market, innovative and user-friendly packaging is one of the new and creative strategies to achieve competitive advantage. Many studies are there to study the effect of product packaging on the buying behaviour of the customers, but only a few to check the holistic impact of all the different elements of packaging on the perception and buying intentions of the customers. In this study, the packaging objectives as elaborated by Kotler and Keller, i.e., identification of brand, description of the product, facilitation for transportation and protection, assistance in storage, and product consumption, are carefully studied to explain the underlying mechanism in Gujarat. AMOS (SEM) was used to test the conceptual model. This study developed a theoretical framework based on the responses from 400 respondents between the ages of 25 and 55 who are frequent FMCG buyers in one of the largest cities in India, Gujarat. The study identified assistance in storage and product consumption as a significant factor in changing the customers’ perception, leading to their actual buying intention towards FMCG products.
Exploring supply chain flexibility in a FMCG food supply chain
Jorieke H.M. Manders et al (2016), said that empirical studies about supply chain flexibility have mainly focused on one (manufacturing) company, occasionally incorporating the adjoining view from a supplier, distributor, or retailer. The present paper argues that a dyadic perspective is not sufficient and that an integrated perspective is required. In-depth case study data was collected and analyzed. The data covers eight organizations in a fast-moving consumer goods (FMCG) food supply chain, including suppliers, the main manufacturer, the logistics service provider, and retailers. Drawing on network theory and stakeholder theory, the study analyzed how these eight organizations experience flexibility across the supply chain. The findings show that each chain member implements flexibility to fulfill the direct needs of the next-tier chain member. Organizations at different positions in the supply chain prioritize other flexibilities. There is no support for overall supply chain flexibility.
Data Collection: Historical data of Hindustan Unilever Limited and Nifty50 index data was downloaded from NSE website for the period 1/12/2024 to 30/11/2025. The data was manipulated to get Friday closing prices.
Data Analysis: Regression equation with t-statistics for Beta (β)
Weekly return on Equity (Y on X) = 0.082 + 0.313
N = 48 | R square = 0.050 | F = 2.46 | P value = 0.1235
The above equation tells us the relationship between weekly return on equity (dependent variable) and weekly return of Nifty50 (independent variable). The positive coefficient indicates a positive relationship between Nifty50 returns and equity returns. This means that when the Nifty50 return increases by 1 unit, the equity return increases by approximately 0.31 units and vice versa. T stat for Beta (β) is 1.57 and the corresponding p-value is 0.1235, which is greater than 0.05. Hence Beta is statistically insignificant implying that the weekly return of Nifty does not have statistically insignificant impact on the return on equity at the 5% level. The R-square value is 0.050, which means that only 5% of the variation in equity returns is explained by Nifty returns while the remaining 95% variation is due to other factors. The F-statistic is 2.46 with a p-value of 0.1235 which is again greater than 0.05 indicating that the overall regression model is not statistically significant.
Conclusion:
Since the Beta value (1.569) is greater than 1, the stock moves more than the market. So, it is good for short-term investment when the market is rising, but it is riskier when the market falls.
Reference:
Harleen Mahajan and Jignesh Vidani (2023). Journal of Management and Entrepreneurship, (2023). Jorieke H.M. Manders et al (2016). Journal of Purchasing and Supply (2016).