Regulators have introduced frameworks to enable retail participation while ensuring safeguards, including broker accountability, algorithm registration, and performance verification, aimed at improving transparency and investor protection.
Algorithmic trading in the equity market has been expanding rapidly, reaching $1.55 billion by 2033, driven by supportive policy measures from the market regulator, SEBI, and improvements in cloud infrastructure.
Algo trading already accounts for most of the activity on exchanges. As per the recent NSE report, algo trades accounted for 54 per cent of the cash market in this fiscal till November and about 67 per cent in the futures and options segment.
Strong growth projections
According to market research from the IMARC Group, algo trading will increase from about $562 million in 2024 to $1.27 billion by 2033.
AI-led momentum
The study forecasts a compound annual growth rate of 9.5 per cent in algo trading between 2025 and 2033, supported by AI/ML-based strategies.
Regulatory safeguards
Recognizing the growth of automated trading, regulators have sought to provide safeguards and level the playing field for retail participants.
Retail access framework
Last February, Sebi introduced a framework allowing retail clients to access algorithmic trading through their brokers while placing compliance responsibilities on intermediaries.
Clear accountability norms
Brokers are considered principals for API based orders; algorithm providers act as agents. Each order must carry a unique identifier; retail-developed algorithms must be registered with the exchange through their broker; exchanges will maintain lists of approved algorithm providers; and brokers must perform due diligence before onboarding them.
Performance verification push
SEBI further launched the Past Risk and Return Verification Agency to verify the performance claims made by investment advisers, research analysts, and algorithmic strategy providers.
Credibility assurance
The agency’s role is to audit and validate performance statistics before they are marketed, adding an extra layer of credibility to test results and historical returns.
Learning and infrastructure
Nitesh Khandelwal, Co-Founder of interactive learning platform QuantInsti, said mainstream adoption of systematic strategies will depend not just on regulation but also on the availability of learning tools and infrastructure.
Transparency boost
Exchange-led empanelment of algorithm providers, coupled with mandatory registration of strategies, should enhance transparency and investor protection by clarifying the roles of strategy creators, execution platforms, and brokers, he said.
Published on January 16, 2026