Legal Analysis Of Algorithmic Trading And AI- Enabled Market Manipulation
- IJLLR Journal
- Apr 13
- 1 min read
Kavidharani R, Presidency University, Bengaluru
ABSTRACT
The paper provides a granular doctrinal examination of the specific legal problems that arise from algorithmic trading and AI-enabled market manipulation. The central question is not merely whether existing law prohibits the impugned conduct in most instances it does but whether the legal definitions, evidentiary standards, and liability frameworks constructed for a world of human decision-making are capable of being applied, coherently and consistently, to the outputs of autonomous AI systems.
The paper examines the statutory status of algorithmic trading under Indian securities law, identifying the absence of specific legislative recognition and assessing the adequacy of SEBI's circular-based regulatory framework. It undertakes a doctrinal analysis of four principal forms of AI-enabled market manipulation -spoofing and layering, quote stuffing, wash and circular trading, and momentum ignition, examining each against the applicable provisions of the SEBI Act, 1992, and the SEBI (Prohibition of Fraudulent and Unfair Trade Practices) Regulations, 2003 (PFUTP Regulations). Also examines the novel and legally unresolved problem of insider trading by algorithmic inference- the question of whether an AI system that derives material price-sensitive insights from publicly available alternative data can be said to possess Unpublished Price Sensitive Information (UPSI) within the meaning of the SEBI (Prohibition of Insider Trading) Regulations, 2015 (PIT Regulations). Finally analyses the attribution of legal liability when AI systems cause market harm, examining vicarious liability, negligence, strict liability, and the case for a reverse burden of proof. Throughout, the research draws on Indian statutory provisions, SEBI enforcement orders, Securities Appellate Tribunal (SAT) jurisprudence, and comparative regulatory developments.
