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Revisiting Insider Trading In The Age Of Algorithmic Trading: Is The SEBI Framework Adequate?




Katriona Sen & Aneesha Biswas, B.A. LL.B. (Hons.), Amity Law School, Amity University, Kolkata.


ABSTRACT


The explosive growth of algorithmic and high-frequency trading in the Indian capital markets where algorithmic trading is now seen to account for over 60% of the market activity and has fundamentally altered the speed, anonymity and as well as the complexity with which securities transactions are executed. Regardless, India's primary instrument for combating insider trading is the SEBI (Prohibition of Insider Trading) Regulation, 2015, which continues to operate on legal assumptions that calibrate to a human-paced market, a conscious insider, an identifiable communication and traceable transaction. This paper argues that the PIT Regulations are structurally inadequate to detect, attribute and deter insider trading in an environment which is algorithmically dominant. Looking back on the July 2025 Jane- street matter, where SEBI accused a U.S. based proprietor trading firm of manipulating Indian markets through coordinated algorithmic strategies across derivatives and cash segments and this paper identifies few discrete regulatory gaps which are the temporal mismatch between microsecond execution and post-hoc surveillance, the collapse of mens rea attribution when trading decisions are automated, the definitional strain placed on concepts of “insider’, “connected persons” and “communication”, when the operative actor is a machine and the cross border complexity generated by algorithms operating across jurisdictions which are beyond the territorial reach of SEBI.


The paper situates these gaps within a comparative framework, drawing lessons from the SEC’s Market Abuse Unit, the EU’s Market Abuse Regulation and MiFID II obligations and the UK FCA’s Senior Managers and Certificate Regime. It concludes with six targeted legislative and institutional recommendations including definitional amendments to the PIT Regulations and a mandatory Algorithmic Trading Responsible Officer regime, real-time surveillance mandates and a Rule 10b5-1 style safe harbour for the purpose of pre-committed algorithmic strategies.


The central claim of this paper is not that the existing framework has failed but that it was never actually designed for the market which it now governs and that the cost of inaction compounds with every percentage point of market share that algorithms capture.


Keywords: Insider Trading, Algorithmic Trading, SEBI PIT Regulations, Unpublished Price Sensitive Information (UPSI), Market Abuse Regulation.



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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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.

 

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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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