Title: Relation of Indices Nifty50 with Aegis Logistics Limited
Author: Akash Ramesh Sangare
Introduction:
Aegis Logistics Limited is a leading player in the Indian Transport and logistic industry. The company is an important part of the market, and its stock price movements in relation to broader indices like Nifty50 provide insight into its market behavior and risk characteristics.
Objective:
To determine the Beta of Aegis Logistics with respect to Nifty 50 and assess its statistical significance.
Literature Review:
Downsizing and Efficiency in the Chemical Manufacturing Industry
Oleg Badunenko (2007) said that, the structural changes in the German chemical manufacturing industry during the 1990s, focusing on downsizing trends and their economic rationale. It identifies two major shifts: fluctuations in the number of firms and a substantial reduction in firm size. Using Data Envelopment Analysis (DEA), the study finds that firms in the sector exhibited high levels of technical inefficiency (25-30%) and were operating under decreasing returns to scale, making downsizing a necessary strategy for improving efficiency. The research shows that the share of scale-efficient firms increased over time, with smaller firms demonstrating better performance in terms of scale efficiency. This supports the argument that “small is beautiful,” as firms that downsized became more competitive. The study also highlights the role of globalization, changing market demands, and financial policy shifts in driving firms towards a leaner structure. While larger firms initially had better technical efficiency, the overall industry trend favored right-sizing operations to achieve optimal productivity. The findings suggest that rather than focusing solely on increasing firm size, companies should prioritize achieving the most productive scale size to maximize efficiency and competitiveness in the market.
Computer Integrated Manufacturing in the Chemical Industry: Theory & Practice
Ashayeri, J. et al (1995), said that the implementation of Computer Integrated Manufacturing (CIM) in the chemical industry, comparing it with discrete manufacturing. It highlights key differences between process and discrete industries, including automation, planning, and control. The study identifies necessary adaptations for CIM in the chemical sector, emphasizing process data acquisition, laboratory information management, lot tracing, and efficient utilization of processing facilities. Through a survey of six chemical companies in the Netherlands and Belgium, the paper finds that while automation is widespread, integration remains limited. The research underscores the need for greater awareness and strategic planning to fully leverage CIM’s potential in the chemical industry.
Data Collection:
The data for Aegis Logistics and Nifty50 were collected for the period from 01-01-2024 to 31-12-2024. The dataset was manipulated to extract Friday closing prices, where Nifty50 was treated as the independent variable (X) and Aegis Logistics as the dependent variable (Y). A regression analysis was conducted on this data.
Data Analysis:
Equation: Aegis Logistics Limited = 0.020 + 0.883 Nifty50
Interpretation:
The regression equation describes the relationship between the Nifty 50 (X) and the Aegis Logistics Limited share price (Y). Indicating that the Aegis Logistics Limited share price is the dependent variable, while the Nifty 50 is the independent variable. The positive coefficient of 0.883239648 suggests that for every 1% increase in the Nifty 50’s weekly return, the Aegis Logistics Limited share price is expected to increase by approximately 0.88%. With 47 observations, the model’s R-squared value is 0.031665636, implying that approximately 3.17% of the variation in Aegis Logistics Limited’s weekly share price returns can be explained by changes in the Nifty 50’s weekly returns, while the remaining 96.83% is attributed to other factors not included in the model. The p-value for the slope is 0.231430638, which is greater than the conventional threshold of 0.05, indicating that the relationship between the Nifty 50’s weekly returns and Aegis Logistics Limited’s weekly share price returns is not statistically significant at the 5% level. Consequently, this model does not provide strong evidence to suggest a significant linear relationship between the Nifty 50’s weekly returns and Aegis Logistics Limited’s weekly share price returns, suggesting that market movements have a very limited impact on the company’s share price returns compared to other potential influencing factors
Conclusion:
Aegis Logistics beta of 0.88 indicates that it is less volatile than the market (Nifty 50) returns and hence it is better suited for Long-term investment.
Reference:
Oleg Badunenko (2007): Downsizing in German Chemical Manufacturing Industry during the 1990s: Why Small Is Beautiful?
Ashayeri, J. & Teelen, A. & Selen, W.J. (1995): Computer integrated manufacturing in the chemical industry : Theory & practice.