Algorithmic Trading and Market Fairness: Assessing Whether Indian Securities Regulation Can Protect Retail Investors in Machine-Speed Markets

Sanya Singh

doi:10.36948/ijfmr.2026.v08i04.83407

Algorithmic Trading and Market Fairness: Assessing Whether Indian Securities Regulation Can Protect Retail Investors in Machine-Speed Markets

Author(s)	Ms. Sanya Singh
Country	India
Abstract	Algorithmic trading and the use of artificial intelligence (AI) and machine learning (ML) have reconstituted securities markets from human-paced environments into machine-speed systems in which orders are generated and executed in microseconds; in India, algorithmic orders now account for a majority of turnover in several market segments. This article asks whether Indian securities regulation, and the Securities and Exchange Board of India (SEBI) in particular, is equipped not only to preserve market integrity and systemic stability but also to protect retail investors from the structural disadvantage that machine-speed markets produce. Drawing on a comparative survey of algorithmic-trading regulation in the United States, the European Union, the United Kingdom and Singapore, and on the literature concerning app-based trading platforms and AI in corporate accountability, it argues that efficiency alone is an inadequate measure of a fair market. While automation can narrow spreads, deepen liquidity and sharpen price discovery, it also amplifies volatility, enables manipulation through spoofing and layering, and entrenches infrastructural inequality between institutional and retail participants — a concern made concrete by SEBI’s own finding that the great majority of individual derivatives traders lose money. The article contends that SEBI’s framework, including its June 2025 AI/ML consultation and its February 2025 retail-algorithm circular, remains oriented towards integrity and systemic risk rather than retail fairness. After weighing the principal objections, it identifies doctrinal and policy gaps and proposes a retail-fairness framework of risk-based registration, model governance, human oversight, gamification limits, liability rules and a structured compensation mechanism.
Keywords	Algorithmic trading · High-frequency trading · SEBI · Retail investor protection · Market fairness · AI/ML governance
Published In	Volume 8, Issue 4, July-August 2026
Published On	2026-07-12
DOI	https://doi.org/10.36948/ijfmr.2026.v08i04.83407

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Algorithmic Trading and Market Fairness: Assessing Whether Indian Securities Regulation Can Protect Retail Investors in Machine-Speed Markets

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