FinTechNavigating the Legal Landscape of Algorithmic Trading in India

INTRODUCTION

Algorithmic trading (algo-trading) has gained significant traction in India’s financial markets over the past decade, driven by technological advancements and increased participation from institutional and retail investors. Today, it accounts for a substantial share of total trades on Indian stock exchanges, leveraging automation, complex algorithms, and high-speed data processing to enhance market efficiency, reduce transaction costs, and improve liquidity.

However, its rapid expansion has raised regulatory concerns regarding market fairness, potential manipulation, and systemic risks. In India, algorithmic trading is regulated by the Securities and Exchange Board of India (SEBI), which ensures that algo-trading adheres to market integrity norms and prevents unfair trade practices. SEBI has introduced various measures to strike a balance between fostering financial innovation and maintaining investor protection.

The following article examines the development of algo-trading in India, its advantages, the evolving regulatory landscape, and key legal challenges associated with its growing adoption.\

ALGORITHMIC TRADING IN INDIA: GROWTH AND ADOPTION

Algorithmic trading in India has been quickly adopted, especially by institutional investors, brokerage houses, and traders who trade frequently. The National Stock Exchange (NSE) and Bombay Stock Exchange (BSE) have also invested in high-speed trading platforms, enabling microsecond-level executions.

Major drivers of algo-trading in India are technological innovation, regulatory patronage by SEBI, enhanced liquidity, and growth in retail participation. Some of the most popular algo-trading strategies in India are statistical arbitrage, mean reversion, and execution algorithms with a view to reducing market impact.

REGULATORY FRAMEWORK FOR ALGORITHMIC TRADING IN INDIA

SEBI has implemented a series of regulations to ensure that algorithmic trading operates within a fair, transparent, and orderly market framework. Initially introduced in India in 2008 with the approval of Direct Market Access (DMA), algo-trading saw its first major regulatory intervention in 2012 when SEBI issued guidelines to monitor and control its use. Since then, the regulatory landscape has evolved significantly, with SEBI introducing stricter risk controls, order-to-trade ratio requirements, system audits, and real-time surveillance to prevent market manipulation and systemic risks. Recent measures have also focused on regulating retail algo-trading platforms and third-party algorithmic strategies, reflecting SEBI’s commitment to balancing financial innovation with investor protection and market stability.

Strengthening Surveillance and Risk Management (2013–2014)

In May 2013, SEBI made bi-annual system audits compulsory for brokers dealing in algorithmic trading to make them compliant. Stock exchanges were required to strengthen their monitoring mechanisms to prevent market manipulation and penalties for non-compliance were raised. In March 2014, SEBI enforced a minimum order-to-trade ratio (OTR) compulsorily to deter unnecessary order placement and enforced order randomization’ to prevent abuse of latency benefits.

Formalizing Direct Market Access and Certification Requirements (2016–2020)

In February 2016, SEBI made DMA regulations formal by mandating pre-trade risk controls and real-time surveillance to check incorrect trades. In March 2020, SEBI implemented stricter algorithm certification norms, mandatory back-testing, and real-time surveillance to identify unusual trading patterns. In June 2020, updated order-to-trade ratio guidelines permitted stock exchanges to implement higher OTR slabs with fines and cooling-off periods for excessive ratios.

Addressing Retail Algo-Trading and Third-Party Risks (2021–2022)

SEBI issued a consultation paper in 2021 suggesting tighter norms for algo-trading, and then guidelines in 2022. These were aimed at regulating retail algo-trading platforms, improving transparency, and ensuring brokers retain control over third-party algos. The guidelines were intended to stem the growth of unregulated algo-trading platforms and impose tighter oversight on retail traders employing automated strategies.

LEGAL AND ETHICAL CHALLENGES IN INDIA

Despite regulatory oversight, algo-trading in India faces several legal and ethical concerns:

1. Market Manipulation Risks

Malpractices such as spoofing (placing large orders and canceling them before execution to create a false impression of demand or supply) and layering (placing multiple non-genuine orders to manipulate prices) remain prevalent. These strategies distort market dynamics and mislead investors. SEBI has taken enforcement actions against entities engaging in such practices, imposing penalties and strengthening surveillance mechanisms to detect irregular trading patterns. However, ensuring real-time detection and swift regulatory action remains a challenge.

2. Systemic Risks and Flash Crashes

The increasing reliance on automated trading raises the risk of sudden market disruptions due to algorithmic errors, faulty execution strategies, or technical failures. The 2021 NSE trading glitch, which led to a temporary halt in trading, underscored concerns over system vulnerabilities and the need for enhanced safeguards. Additionally, global incidents such as the 2010 U.S. Flash Crash, where high-frequency trading (HFT) contributed to extreme market volatility, highlight the dangers of automated trading spirals. SEBI has mandated stringent circuit breakers, kill switches, and risk controls, but the threat of algorithm-induced volatility persists, particularly in low-liquidity scenarios.

3. Uneven Playing Field

Institutional traders with access to co-location services and advanced technology gain a significant speed advantage over retail traders. SEBI has taken measures to reduce latency arbitrage, including restrictions on tick-by-tick data access and enhanced surveillance of high-frequency trades, but disparities persist.

4. Data Privacy and Cybersecurity

The increasing reliance on data-driven trading strategies raises concerns about data security, insider trading risks, and algorithmic integrity. SEBI has mandated strict cybersecurity protocols for brokers and trading platforms.

RECENT SEBI INTERVENTIONS AND FUTURE OUTLOOK

SEBI has acted with urgency on risks related to algo-trading in the form of certification of algorithms, strengthened monitoring using artificial intelligence tools, and upgraded norms for retail-based algo-trading platforms. The future holds higher importance for trading functions of AI and machine learning, calling for regulation  upgrades. Blockchain technology will possibly also find uses for heightened transparency of algorithmic trades.

Globally, regulators in countries such as the U.S. and the EU have placed stringent regulations on high-frequency trading and algorithmic techniques. India’s regulatory stance follows global best practices but remains evolving in response to domestic market realities.

AMLEGALS REMARKS

Algorithmic trading has reshaped India’s financial markets, enhancing efficiency, liquidity, and execution speed. However, it also presents challenges, including market manipulation, systemic risks, and an uneven competitive landscape.

SEBI’s regulatory framework strives to balance innovation with investor protection, yet continuous refinements are necessary to ensure fair and transparent markets. As technology progresses, regulatory vigilance and adaptive oversight will be crucial. The future of algo-trading in India will depend on the ability of regulators, exchanges, and market participants to address emerging risks while fostering responsible innovation.

– Team AMLEGALS assisted by Mr. Mehul Agarwal (Intern)

For any feedback or queries, feel free to reach out to rohit.lalwani@amlegals.com or mridusha.guha@amlegals.com