Risk and return analysis of selected stocks in the Indian automobile industry on the national stock exchange

https://doi.org/10.55214/25768484.v8i6.3528

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The Indian automobile industry has experienced substantial growth, driven by rising domestic demand, urbanization, and technological advancements, positioning India as a significant global manufacturing hub. The industry has also embraced the shift towards electric vehicles (EVs), particularly in the two-wheeler and three-wheeler segments, spurred by government initiatives like the Faster Adoption of Manufacturing of Electric Vehicles in India (FAME) and the Production Linked Incentive (PLI) schemes. This study explores the risk-return dynamics of selected publicly listed Indian automobile companies, analyzing their equity performance between 2017 and 2023. By evaluating market, financial, operational, and regulatory risks, the research aims to offer insights into the investment potential of these companies. The study investigates how systematic and unsystematic risks influence investment decisions, with a focus on prominent companies such as Maruti Suzuki, Mahindra & Mahindra, Tata Motors, Hindustan Motors, and Ashok Leyland. Using statistical tools like mean, standard deviation, variance, and beta, the analysis provides a comprehensive understanding of the volatility, return potential, and overall risk profile of the companies. Results suggest a direct correlation between higher risk and higher returns, with Ashok Leyland emerging as a top performer, while Maruti Suzuki demonstrated more stable returns. The study also provides recommendations for investors, emphasizing the importance of diversification and long-term analysis. Despite its limitations, the research contributes valuable insights for investors looking to navigate the evolving Indian automobile sector.

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Madhavedi, S. ., Hoo, W. C. ., Pung, N. C. ., & Reddy, A. A. . (2024). Risk and return analysis of selected stocks in the Indian automobile industry on the national stock exchange. Edelweiss Applied Science and Technology, 8(6), 7063–7138. https://doi.org/10.55214/25768484.v8i6.3528

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Published

2024-12-06