Fundamental Analysis of Mid-Cap Stocks in the Indian IT Sector

Year : 2025 | Volume : 15 | Issue : 01 | Page : 1 11
    By

    Dhruv Jindal,

  • Nidhi Sharma,

  1. Student, Department of Management Studies (BBA), Rukmini Devi Institute of Advanced Studies, New Delhi, India
  2. Associate Professor, Department of Management Studies (BBA), Rukmini Devi Institute of Advanced Studies, New Delhi, India

Abstract

Fundamental analysis is also needed for the classification of financial assets (stocks, bonds, and currencies) using economic indicators or valuation methods to determine their true value. The present study focuses on mid-cap stocks in the information technology (IT) sector of the Indian market, which includes sectors such as software development, hardware manufacturing, semiconductors, IT services, internet and e-commerce, telecommunications, cybersecurity, and cloud computing. Mid-cap stocks may offer a good mix of growth potential and somewhat lower risk. The intended research methodology includes defining the research goal, selecting a sample population, and utilizing data analysis tools such as Economic, Industry, and Company (EIC) analysis, quantitative analysis, competitive analysis, and SWOT surveys. The report sheds light on the economic landscape, industry trends, and individual company performance, helping investors track key financial metrics of companies with similar profiles. Despite constraints, the research provides valuable insights for investors, who are advised to consider industry dynamics, technological development, and macroeconomics in addition to fundamental analysis when making decisions.

Keywords: Fundamental analysis, mid-cap stocks, Indian IT sector, economic factors, financial metrics, industry trends, SWOT analysis, investment decisions

[This article belongs to Current Trends in Information Technology ]

How to cite this article:
Dhruv Jindal, Nidhi Sharma. Fundamental Analysis of Mid-Cap Stocks in the Indian IT Sector. Current Trends in Information Technology. 2024; 15(01):1-11.
How to cite this URL:
Dhruv Jindal, Nidhi Sharma. Fundamental Analysis of Mid-Cap Stocks in the Indian IT Sector. Current Trends in Information Technology. 2024; 15(01):1-11. Available from: https://journals.stmjournals.com/ctit/article=2024/view=171877


References

  1. Birba DE. A comparative study of data splitting algorithms for machine learning model selection [Degree project]. Stockholm (Sweden): KTH Royal Institute of Technology, Electrical Engineering and Computer Science; 2020. Available from: https://www.diva-portal.org/smash/get/diva2:150 6870/FULLTEXT01.pdf.
  2. International Energy Agency. Renewables 2023: Analysis and forecast to 2028. Paris: International Energy Agency; 2023.
  3. Gaude VP, Gawas NM, Khandeparkar K, Naik GR, Rivonker NU, Kapdi GG. Fundamental and technical analysis of select FMCG companies in India. Migration Letters. 2024;21(Supplement 6):871-883.
  4. Pierdicca R, Frontoni E, Zingaretti P, Malinverni ES, Colosi F, Orazi R. Making visible the invisible: Augmented reality visualization for 3D reconstructions of archaeological sites. In: De Paolis L, Mongelli A, editors. Augmented and Virtual Reality. AVR 2015. Lecture Notes in Computer Science, vol. 9254. Cham (Switzerland): Springer; 2015. DOI: https://doi.org/10.1007/ 978-3-319-22888-4_3.
  5. Hanafi I, Hamsal, Pratama D. Comprehensive examination of determinants influencing capital structure and stock returns in mining companies listed on the Indonesian Stock Exchange (2013-2018). Riau Int Conf Econ Bus Account. 2024;1(2):518–29.
  6. Giwa YA. Over the counter stocks data acquisition and analysis with time series prediction. Int J Soc Sci Stud. 2024;4:3643-3670.
  7. Kumar Jha N. The impact of fundamental analysis in the IT industry before investing: A comparative study on Wipro, TCS, and Infosys. Int J Sci Res. 2024;13:494–500. DOI: 10.21275/ SR231229194428.
  8. Kara Y, Acar Boyacioglu MA, Baykan ÖK. Predicting direction of stock price index movement using artificial neural networks and support vector machines: The sample of the Istanbul stock exchange. Expert Syst Appl. 2011;38:5311-5319. DOI: 10.1016/j.eswa.2010.10.027.
  9. König G, Neugebauer C, Goldlücke B, Döllner J. HoloMap: Interacting with large geospatial datasets in mixed reality. IEEE Trans Vis Comput Graph. 2019;25:2146-2156.
  10. Ma Z, Bang G, Wang C, Liu X. Towards earnings call and stock price movement. [Preprint]. ArXiv:2009.01317. 2020 Aug 23. DOI: https://doi.org/10.48550/arXiv.2009.01317
  11. Silpa KS, Mol JA, Ambily AS. A study on fundamental analysis of selected IT companies listed at NSE. J Adv Res Dyn Control Syst. 2017;9:1-10.
  12. Rezaei H, Faaljou H, Mansourfar G. Stock price prediction using deep learning and frequency decomposition. Expert Syst Appl. 2021;169:114332. DOI: 10.1016/j.eswa.2020.114332.
  13. Shen J, Shafiq MO. Short-term stock market price trend prediction using a comprehensive deep learning system. J Big Data. 2020;7:66. DOI: 10.1186/s40537-020-00333-6. PubMed: 32923309.
  14. Tiwari P. Augmented reality and its applications in geographical information systems (GIS). IOP Conf Ser: Mater Sci Eng. 2020;913:012027.
  15. Wulandari W, Iskandar R, Rasyad FH. Analysis of the influence of fundamental financial factors of manufacturing companies in the consumer goods industry on share prices in ISSI. J Sci. 2023;12:2332-2342.
  16. Bharath G, Rupa Ch, Karthik M, Bhavani AL, Chowdary VM. Revelation of geospatial information using augmented reality. 2021 Sixth International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), Chennai, India. 2021. pp. 303–8. DOI: 10.1109/WiSPNET51692.2021.9419459.

Regular Issue Subscription Review Article
Volume 15
Issue 01
Received 02/08/2024
Accepted 13/08/2024
Published 02/12/2024
Publication Time 122 Days



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