Too Fast, Too Furious? SEBI Slows Down Algo Trading for Retail Safety

[Akshat is an Associate at Khaitan & Co, and Tanvi is a student at National Law Institute University, Bhopal.]

Algorithmic trading, or algo trading, has revolutionized financial markets across the world, including in India. With the use of algo trading, the trading system employs computer programs to place orders automatically using pre-determined trading rules to execute orders in a highly efficient manner with minimal human intervention. Since Securities and Exchange Board of India (SEBI) brought in broad guidelines in 2012, algo trading has gained immense popularity among high-frequency traders and institutional players. Today, it accounts for nearly 50-60% of total turnover in Indian stock exchanges such as Bombay Stock Exchange and National Stock Exchange. The entry of application programming interface platforms (API-based platforms) such as Upstox, Zerodha, and AngelOne has boosted retail players to engage algorithmic approaches, which has on the downside raised concerns over transparency, fairness, and volatility in the market.

SEBI has shown a number of apprehensions regarding retail investors getting involved in algo trading, citing possible manipulation of the market, unfair access to market information, and excessive volatility. In response to this, on 4 February 2025, SEBI introduced a new regulation to enable safer involvement without compromising on market stability or integrity. The reforms intend to provide a systematized method of regulation to keep algorithmic trading a fair and transparent process.

Understanding Algorithmic Trading

Algorithmic trading is a highly developed way of trading in which the rules are set in motion in advance and mathematical models place orders to purchase or sell automatically. SEBI’s official definition of algo trading is any order that is generated using automated execution logic. Algorithmic trading allows orders to be carried out at high speeds, taking advantage of price differentials in the marketplace. 

The marketplace has seen an upward trend towards algo trading in the last decade with the introduction of direct market access and co-location services. Retail investors were also able to effectively involve themselves with the arrival of API-based platforms, democratising algo trading yet also creating challenges for regulation.

For retail investors, algo trading is beneficial in various ways, some of these advantages include (a) rapid order execution; (b) elimination of emotional effects, (c) chance to trial strategies in a simulated way before using them in live trading; and (d) effectuating orders with less surveillance based on predetermined instruction pattern. With the set of advantages, there are also possible risks such as latency disadvantage in data, regulation requirements, and potential market instability when there is over-automation of order entries.

SEBI’s Existing Regulatory Framework on Algo Trading

The evolution of algo trading in India has been marked by a string of regulator interventions. SEBI initially came up with guidelines in 2012 to manage institutional algo trading, followed by additional mandates in 2013, 2015, and 2016 to follow risk management processes.

The initial guidelines in 2012 were introduced to check market manipulation under which brokers were obliged to institute risk control mechanisms in place. In 2013, SEBI asked brokers offering algo trading services to be audited every 6 months to check whether they are in conformity with the working rules. In 2015, SEBI came up with additional provisions to enable fair access to co-location services in order to prevent unfair speed benefits to specific participants. By 2016, SEBI allowed co-location centers to be connected directly to each other to facilitate more efficiency in market execution.

Despite these efforts, there were lacunae in the system of regulation. Retail algo trading, which was largely unregulated, was raising concern regarding unmonitored trading patterns. Market distortions, asymmetric access to information, and possible manipulation tactics has necessitated a review of approach to regulation by SEBI.

Recent SEBI Guidelines on Algo Trading

In response to such fears, SEBI’s new circular of February 2025 introduces stricter control mechanisms. The new regulation requires brokers to obtain exchange approval for each algorithm trading method, subjecting each algo to a rigorous validation process. The algo providers must be registered with exchanges, enabling more regulation to be applied to them. The circular also emphasises use of separate API tagging and authentication processes to enable more traceability and security.

The classification of algorithmic trading between Black Box and White Box is a fundamental departure from the extant framework on algo trading. The transparent execution logic of White Box algos would be approved more easily, while Black Box algos, relying on proprietary models, would require more documentation of their research to be approved. The exchanges would be more proactively involved in algo compliance surveillance and in using kill-switch mechanisms to halt disruptive trading patterns.

These new standards impact different participants in different manners. The brokers would be in charge of ensuring regulation adherence, something that would be more costly to maintain. Retail investors would also be required to adhere to more procedures, something that would limit entry to algorithmic trading. The rules would better safeguard investors, but would also limit independent traders and fintech firms to take part in trading owing to higher compliance costs and entry barriers.

Taking cue from a global perspective, it is pertinent to note that such regulations have been put in place by other countries as well to ensure transparent and fair market trading. For instance, the United States Securities and Exchange Commission and Financial Industry Regulatory Authority require strict regulation of algo trading, holding brokers liable for algorithmic strategies. Further, the United Kingdom’s Financial Conduct Authority also demands registration of algorithms and firms have to ensure that proper policies are procedures are set out for automated surveillance of market manipulation. The European Union’s Markets in Financial Instruments Directives II requires the stakeholders to ensure stress testing and explicit declaration of algo trading strategies. 

Implications for Retail Investors and Market Stability

One of the primary objectives of SEBI’s new framework is to enhance investor protection. By requiring API authentication and tagging, SEBI aims to reduce the risk of unauthorized or manipulative trading practices. The brokers would be liable to handle grievances in respect of algos, providing retail traders with a transparent redressal system. Real-time surveillance of the exchanges would stop flash crashes caused by errant algos, making the market more resilient.

However, these attempts would be fraught with their own challenges. Retail algo traders would be required to face more compliance requirements such as registration of strategies and approvals by exchanges that would hinder innovation. The brokers’ fees would be higher to cover up for expenses of compliance, making algo trading more expensive to small traders. Restrictive open API limits would limit the potential of retail traders to craft dynamic trading strategies, reducing marketplace competitiveness.

The impact on volatility and market liquidity is another key concern. In one sense, more regulation can restrict abusive trading practices, making markets more resilient. In another sense, high compliance expenses can force retail traders out of algo trading, decreasing liquidity and inducing more price volatility when large institutional players dominate order flows.

Conclusion and the Road Ahead

SEBI’s latest regulation is a move to tighten regulation without suppressing responsible algorithmic trading practices. As these reforms enhance security and transparency, they also pose challenges to smaller fintech players and retail traders. The challenge of sustaining a healthy algo trading ecosystem is in finding a balance between protection of investors and encouraging innovation.

A potential approach would be to institute a tiered system of regulation, in which small retail traders would be subject to less stringent requirements than high-frequency traders. Implementing a fintech start-up regulatory sandbox would enable new trading algorithms to be tested in a controlled manner before large-scale deployment. SEBI would also need to simplify algo approval procedures to ensure that regulation is not inhibiting adaptability in the marketplace.

Furthermore, promoting fair access to the market through low-cost co-location services and removing execution speed differentials would level the playing field for retail traders. More security procedures should be flexibility-oriented, allowing secure means of authentication without unnecessarily hampering entry to the market.

The future of algorithmic trading in India would also be dependent on SEBI’s ability to calibrate such rules to be in line with new technologies that continue to emerge. By designing a regulation system that balances protection of investors and innovation, India can continue to enjoy the benefits of algo trading without sacrificing long-term market stability and fairness.