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The Role Of Artificial Intelligence (AI) In Stock Market Analysis




Sivabakkiyavathi R, KMC College of Law


ABSTRACT


This paper explores the transformative role of Artificial Intelligence (AI) in stock market analysis, highlighting its applications, benefits, and challenges. AI technologies such as machine learning, natural language processing (NLP), and neural networks have revolutionized financial markets by enabling real-time data processing, predictive modelling, algorithmic trading, sentiment analysis, and portfolio risk management. The paper reviews key literature, emphasizing AI’s superior performance over traditional methods in forecasting and investment strategy optimization. It also examines the regulatory and ethical implications of AI within the framework of the Indian Companies Act, 2013, focusing on areas like corporate governance, risk disclosure, fraud prevention, and the auditor’s role. Despite concerns around data quality, model overfitting, and market fairness, AI’s future in financial markets is promising, with its integration into blockchain technologies and decentralized finance (DeFi) set to redefine investment strategies. As AI continues to evolve, addressing transparency and regulatory compliance will be critical to ensuring its responsible and equitable deployment in stock market analysis.



Indian Journal of Law and Legal Research

Abbreviation: IJLLR

ISSN: 2582-8878

Website: www.ijllr.com

Accessibility: Open Access

License: Creative Commons 4.0

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Licensing: 

 

All research articles published in The Indian Journal of Law and Legal Research are fully open access. i.e. immediately freely available to read, download and share. Articles are published under the terms of a Creative Commons license which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

 

Disclaimer:

The opinions expressed in this publication are those of the authors. They do not purport to reflect the opinions or views of the IJLLR or its members. The designations employed in this publication and the presentation of material therein do not imply the expression of any opinion whatsoever on the part of the IJLLR.

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