Open Access
Research Article
Equity research analysis on automobile sector of India
Abhishek PatilAbhishek.patil2025@sibmnagpur.edu.inSymbiosis Institute of Business Management Nagpur Campus Constituent of Symbiosis International (Deemed) University, PuneNagpur, Maharashtra, 440008, IndiaView full profile → , *Palaniappan SellappanCorresponding authors.palaniappan@sibmnagpur.edu.inSymbiosis Institute of Business Management Nagpur Campus Constituent of Symbiosis International (Deemed) University, PuneNagpur, Maharashtra, 440008, India0000-0002-2890-1412View full profile →
* Corresponding author · click or hover a name for details
- Received:
- 05 Feb 2025
- Published Online:
- 01 Nov 2025
- Article type:
- Research Article
- Language:
- EN
- Article no.:
- JIOS-2078
- Pages:
- 2545–2564
Abstract
This research paper analyses the financial performance of leading companies in the Indian Automotive Industry—Tata Motors, Bajaj Auto, Ashok Leyland, Eicher Motors, Hero MotoCorp, and Mahindra & Mahindra—using fundamental and technical analysis. Ratio analysis highlights profitability, operational efficiency, debt management, and working capital metrics, while technical analysis evaluates stock market trends and investor sentiment. Key findings reveal Eicher Motors as the best performer due to superior profitability margins, strong ROCE, and efficient debtor management, followed by Bajaj Auto, excelling in asset efficiency and a robust Cash Conversion Cycle. The study provides valuable insights into market dynamics, enabling informed investment decisions and contributing to the understanding of the fast-paced automotive sector.
Keywords
Subject Classifications
62P2091B8491G5091G7091G80
References
[1] S. Aluru, B. V. R. V. Tej, and M. Arkanath, “Identifying stock market bubbles and evaluation with momentum index and CCI,” Journal of Statistics and Management Systems, vol. 26, no. 5, pp. 1291–1301 (2023), doi: 10.47974/JSMS-1183.[2] M. A. Hossen, M. M. Rahman, M. N. A. Nahid, R. Islam, S. K. Banshal, V. Gupta, and P. Dass, “Impact on GDP and the stock market during pandemics or epidemics of 21st century,” Journal of Interdisciplinary Mathematics, vol. 26, no. 5 (2023).[3] R. Santran and R. Singh, “Understanding vehicle demand dynamics in Indian road transport: A qualitative framework,” Systems Research and Behavioral Science (2024), doi: 10.1002/sres.2998.[4] Y. Nauhria, S. Pandey, and M. S. Kulkarni, “Competitive Priorities for Indian Car Manufacturing Industry (2011–2020) for Global Competitiveness,” Global Journal of Flexible Systems Management (2011), doi: 10.1007/BF03396603.[5] A. Meena, S. Dhir, and S. Sushil, “An analysis of growth-accelerating factors for the Indian automotive industry using modified TISM,” International Journal of Productivity and Performance Management (2021), doi: 10.1108/IJPPM-01-2019-0047.[6] S. Duvisac, “Reconstituting the Industrial Worker: Precarity in the Indian Auto Sector,” Critical Sociology (2019), doi: 10.1177/0896920518754341.[7] S. Garg and S. Sushil, “Globalisation and its impact on performance: an empirical study on selected firms using multimethod approach,” Benchmarking (2024), doi: 10.1108/bij-08-2024-0639.[8] S. K. Sharma and A. Bhat, “Supply chain risk management dimensions in Indian automobile industry: A cluster analysis approach,” Benchmarking: An International Journal (2014), doi: 10.1108/BIJ-02-2013-0023.[9] M. Asadi, U. A. Sheikh, M. Balcilar, D. Roubaud, and H. R. Ghasemi, “Are there inextricable connections among automobile stocks, crude oil, steel, and the US dollar?,” Energy Economics (2023), doi: 10.1016/j.eneco.2023.107176.[10] S. H. Penman, “Return to Fundamentals,” Journal of Accounting, Auditing & Finance (1992), doi: 10.1177/0148558X9200700403.[11] X. Zhang, Y. Zhang, S. Wang, Y. Yao, B. Fang, and P. S. Yu, “Improving stock market prediction via heterogeneous information fusion,” Knowledge Based Systems (2017), doi: 10.1016/J.KNOSYS.2017.12.025.[12] S. Usmani and J. A. Shamsi, “News sensitive stock market prediction: literature review and suggestions,” PeerJ Computer Science (2021), doi: 10.7717/PEERJ-CS.490.[13] A. Picasso, S. Merello, Y. Ma, L. Oneto, and E. Cambria, “Technical analysis and sentiment embeddings for market trend prediction,” Expert Systems With Applications (2019), doi: 10.1016/J.ESWA.2019.06.014.[14] M. J. S. de Souza, D. G. F. Ramos, M. G. Pena, V. A. Sobreiro, and H. Kimura, “Examination of the profitability of technical analysis based on moving average strategies in BRICS,” Financial Innovation (2018), doi: 10.1186/S40854-018-0087-Z.[15] G. Meissner, A. Alex, and K. Nolte, “A Refined MACD Indicator – Evidence against the Random Walk Hypothesis?,” ABAC Journal (2001).[16] Y. Gao, J. Wu, Z. Feng, G. Hu, Y. P. Chen, and W. He, “A new BRB model for technical analysis of the stock market,” Intelligent Systems with Applications (2023), doi: 10.1016/j.iswa.2023.200198.[17] N. Kulshrestha and V. K. Srivastava, “Synthesizing Technical Analysis, Fundamental Analysis & Artificial Intelligence – An Applied Approach to Portfolio Optimisation & Performance Analysis of Stock Prices in India,” in International Conference on Computer Communications (2020). doi: 10.1109/ICRITO48877.2020.9197966.[18] Y. Han, K. Yang, and G. Zhou, “A New Anomaly: The Cross-Sectional Profitability of Technical Analysis,” Journal of Financial and Quantitative Analysis (2013), doi: 10.1017/S0022109013000586.[19] K.-H. Lee and G.-S. Jo, “Expert system for predicting stock market timing using a candlestick chart,” Expert Systems With Applications (1999), doi: 10.1016/S0957-4174(99)00011-1.[20] Y. Lin, S. Liu, H. Yang, and H. Wu, “Stock Trend Prediction Using Candlestick Charting and Ensemble Machine Learning Techniques With a Novelty Feature Engineering Scheme,” IEEE Access (2021), doi: 10.1109/ACCESS.2021.3096825.[21] D. Avramov, G. Kaplanski, and H. Levy, “Talking Numbers: Technical versus fundamental investment recommendations,” Journal of Banking and Finance (2018), doi: 10.1016/J.JBANKFIN.2018.05.005.[22] W.-C. Hsiao and R.-S. Liou, “Integrating technical indicators, chip factors and stock news for enhanced stock price predictions: A multi-kernel approach,” Asia-Pacific Management Review (2023), doi: 10.1016/j.apmrv.2023.10.001.
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