SEBI’S CRACKDOWN ON ALGO TRADING: A STEP FORWARD OR A REGULATORY PUZZLE?

This post is authored by Madhvendra Jha and Devanshu Khurana, B.A. LL.B. (Honours) students at Dr. Ram Manohar Lohia National Law University, Lucknow.

1. INTRODUCTION

Algo trading is the dominant form of everyday trading operations in the contemporary stock market.  On February 4, 2025, the Securities and Exchange Board of India (SEBI) released a  circular to regulate retail investors’ involvement in algorithmic trading. According to SEBI’s earlier guidelines, it refers to any form of automated rule-based trading wherein decision making is entrusted to an algorithmic model. The general reason behind using algos for trading was convenience, increase in traders’ productivity and  reduction in market impact, as mentioned in the Trade survey.

The algo trading saga in India begins with a SEBI press release dated April 03, 2008, introducing Direct Market Access (DMA) facility for investors  providing electronic facilities that allow clients to place orders directly into the exchange trading system. The allowance of colocation facilities by NSE in 2010 led to its expansion. During the last 15 years, SEBI has released various notifications and consultation papers to regulate algorithmic trading and protect the interests of investors.

Keywords – SEBI, Security Regulations, Financial Markets & Stock Exchanges

2. DEEP DIVE INTO THE CIRCULAR

The latest circular is part of the SEBI’s ongoing efforts to establish a structured framework for algorithmic trading in India, addressing concerns over unfair practices in the market. Thus, to curb these practices  SEBI has instructed use of a unique identifier for each client.. This identifier ensures that every trade and order can be traced back to the specific user which enables the oversight of trading activities. By linking trades to individual clients, SEBI aims to enhance transparency, deterring corrupt officials and market manipulators from exploiting algorithmic anonymity to engage in insider trading or other fraudulent acts.

The circular has also mandated registration of algorithms created by tech savvy investors for their own benefit to be registered if they cross the specified order per second threshold which is to be decided by SEBI. This move shows a positive approach by SEBI in regulating algo trading by limiting the spread to just family members of the investors. The European Securities and Markets Authority (ESMA) also has a similar provision of specific threshold to trade ratio.

Furthermore, SEBI has prohibited open APIs, citing potential security risks such as data breaches by malicious actors. Instead, it has enforced the use of a specific API key-based system to enhance traceability and security. The framework limits authentication options, allowing only Open Authentication/OAuth (open standard protocol for authorization of an application for using user information). This streamlines the access for traders while discontinuing all other authentication mechanisms. Further, reduces the use of API for unauthorized trades, which lowers  their utilization for dubious trades. However, it raises questions about flexibility and innovation in India's evolving algorithmic trading ecosystem.

SEBI has announced that algorithms will now be classified into two distinct categories. The first category includes execution or "white box" algorithms, where the underlying logic is fully transparent and can be used by any trader once registered, making it easier to regulate. The second category consists of "black box" algorithms, where the logic remains hidden from the user. Here, providers will be required to register as Research Analysts with SEBI and maintain and publish comprehensive research reports.

This democratization of algorithmic trading has  potential to revolutionize how millions of Indians engage with the stock market. By automating trade execution, algo trading enhances speed, efficiency, and precision. However, it also introduces significant risks, as even minor technical glitches such as server malfunctions or coding errors can lead to unintended trades, potentially destabilizing the market. Ensuring robust risk management measures and fail-safe mechanisms will be crucial in mitigating these risks while maximizing the benefits of algorithmic trading.

3. KEY CHALLENGES: HIGH-FREQUENCY MANIPULATION AND MARKET FAIRNESS

The rapid evolution of algorithmic trading, driven by breakthroughs in AI and coding, poses significant challenges for global regulators, as seen in SEBI’s recent study, which found that 97% of FPI profits and 96% of proprietary trader profits in F&O trading for FY24 came from algo trading.

Algo trading has found its most controversial application in High-Frequency Trading (HFTs) where complex algorithms execute transactions within mere fractions of a second. Spoofing (placing and cancelling futures bids before execution) is one example of how algorithms are used to manipulate the market.  The recent notification counteracts this and other forms of algorithmic manipulations through increasing transparency. The requirement for unique identification and restriction on open APIs reduces the potential anonymity that malicious actors could have utilised. Despite SEBI’s commendable efforts, weak enforcement mechanisms risk rendering the new guidelines ineffective. The regulator’s strict penalty on NSE in the Dark Fibre case reflects its stance, yet the violation traced back to a 2012 circular underscores the delayed response. In absence of stronger enforcement, mere guidelines may fall short in curbing algorithmic trading malpractices.

4. SEBI’S ENFORCEMENT CHALLENGES: CONSTRAINTS, OVERLAPS, AND DELAYED ACTION

Unlike its global counterparts, such as the U.S. SEC or China's SAMR, SEBI does not have a dedicated team of specialized enforcement officers. This resource limitation often leads to delayed investigations, weaker enforcement, and insufficient deterrence against market manipulation, particularly in complex areas like algorithmic trading.

The NSE co-location scam highlights that  while SEBI eventually imposed penalties, the investigation took over five years, underscoring the resource limitations. In contrast, the SEC’s enforcement actions, such as the CFTC vs. Navinder Singh Sarao (2021), are often resolved more swiftly due to the SEC’s robust infrastructure and specialized teams.

SEBI faces challenges from overlapping regulatory authority with agencies like the CCI and RBI, leading to miscommunication, fragmented investigations, and delays—particularly in cases of financial fraud and algorithmic trading. In the  Karvy Stock Broking case (2019), SEBI uncovered that the broker had misused client securities worth ₹2,300 crore (approx. $310 million). While SEBI acted against Karvy, the involvement of multiple agencies slowed the process, leaving the investors in limbo.

SEBI’s reliance on a small team of generalist officers weakens its enforcement capabilities, unlike the SEC, which has dedicated divisions for market abuse. This limitation often necessitates the involvement of agencies like the Enforcement Directorate (ED) for asset seizures, further complicating regulatory actions. The lack of specialized resources also slows the adoption of advanced surveillance tools, making SEBI increasingly dependent on external audits and whistleblower reports to detect market abuses.

5. A GLANCE OUTSIDE INDIA

From the findings of a study on HFTs conducted by National Institute of Financial Management, more than half of all orders at NSE and BSE come from regular investors using algo trading whereas in countries like the US and UK, 80% of all trades are algorithmic, which means India is catching up with global trends.

As India catches up with global algo trading trends, regulatory challenges have necessitated strict measures, as seen in the U.S. with the Dodd-Frank Act (2010). The SEC and the Commodity Futures Trading Commission (CFTC) are the regulatory bodies who act on this and further regulations.

Another critical regulation is the Market Access Rule (Rule 15c3-5), which mandates that brokers implement pre-trade risk controls to prevent erroneous or manipulative orders from reaching the market. This rule requires firms to limit order sizes, unique identification of algorithms. credit exposure, and trading activity, ensuring that only legitimate orders are executed. Additionally, Regulation SCI (Systems Compliance and Integrity) requires firms to ensure the operational resilience of their trading systems, including algorithms, and to report any system disruptions or failures promptly.  In a fashion, the recent notification has tried to cement implementation of similar rules in India.

The SEC also relies on advanced surveillance tools like MIDAS (Market Information Data Analytics System), which collects and analyses real-time market data to detect irregularities, such as spoofing, layering, quote stuffing, etc. MIDAS enables regulators to identify manipulative behaviour by tracking order placement, cancellation, and execution data across markets.

A recent high-profile case highlighting this framework's effectiveness is the Navinder Singh Sarao case. Sarao, a UK-based trader, used an automated program to place and cancel large orders in the E-mini S&P 500 futures market between 2009 and 2014. His actions created a false impression of supply and demand, artificially moving prices in his favour. Sarao’s spoofing activities were linked to the 2010 Flash Crash, where the Dow Jones Industrial Average (DJIA) dropped nearly 1,000 points in minutes before recovering. The CFTC and DOJ swiftly acted, filing charges in 2015 and securing a settlement in 2021. Sarao was ordered to pay $38 million in restitution and disgorgement, banned from trading in U.S. markets, and sentenced to one year of home detention in the UK.

6. THE WAY FORWARD

Despite SEBI’s efforts, its regulatory framework falls short in addressing several key challenges. While its measures primarily target stockbrokers, critical market participants such as asset managers and clearing corporations remain largely unregulated, creating significant regulatory gaps.

Moreover, enforcement loopholes persist, as surprise inspections are conducted only on a sample basis for select entities, leaving room for oversight failures. Similarly, weak auditor safeguards undermine long-term independence, with the framework relying merely on a two-year cooling-off period instead of more robust checks. Creating a dedicated SEBI division staffed with specialized experts would significantly strengthen enforcement, aligning India’s regulatory framework with global standards

Another pressing concern is SEBI’s lagging regulatory technology. In contrast to global exchanges like NASDAQ and Euronext, SEBI has yet to integrate advanced RegTech (Regulatory Technology) solutions such as AI and machine learning for real-time monitoring, limiting its ability to detect and prevent market manipulation effectively.

To bridge these gaps, there is an urgent need for legislative strengthening. Relying on temporary circulars and guidelines is insufficient, so stronger statutory provisions are essential. The liability framework in India regarding digital crimes is already shaky and weak; thus, increasing the burden without proper legislative action may not bring intended consequences upon the guilty parties. A potential remedy to this can be implementing the provision of strict liability from SEC rule 10b-5 to implement automatic fines on people unwilling to disclose their algorithms as required.