This article has been written by Ms. Drishti Rawat, a second-year student at National Law University, Delhi.

Abstract

Algorithmic trading has become a pivotal part of financial markets but also poses risks like volatility and manipulation. This article examines the regulatory approach taken by the Securities and Exchange Board of India (SEBI) to govern algorithmic and high-frequency trading in stock markets. The paper traces how SEBI’s guidelines have evolved since 2008 to promote the efficiency of automated trading while also addressing emerging challenges. The objectives behind SEBI’s regulations are analyzed including market integrity, investor protection, transparency, accessibility, resilience and risk management. The core components of the regulatory framework are highlighted including testing and certification of algorithms, risk controls like price/order limits, circuit breakers, disclosure requirements and equitable access norms. The article assesses the impact of SEBI’s adaptive regulations in enhancing overall market quality. However challenges remain in detecting novel manipulation tactics, and concerns around regulatory arbitrage persist. The paper emphasizes that sustained policy research and public-private partnerships are imperative to optimize the benefits of algorithmic trading in India while strengthening safeguards against systemic threats arising from technological disruptions.  

Introduction 

Algorithmic trading refers to the use of sophisticated mathematical models and algorithms to make trading decisions and execute orders without any human intervention. It involves the use of advanced technologies like artificial intelligence, machine learning and big data analytics to analyze market data and identify lucrative trading opportunities. Over the past decade, algorithmic trading has gained immense popularity among institutional investors and has become an integral part of global financial markets. 

However, the proliferation of algorithmic trading has also raised concerns about its potential risks like flash crashes, unfair trade practices and market manipulation. This has led to increased scrutiny by regulators who want to reap the efficiencies of algo trading while also safeguarding market integrity. In India, the Securities and Exchange Board of India (SEBI) has introduced several regulations to govern algorithmic and high-frequency trading. This article examines SEBI’s regulatory framework for algorithmic trading and how it aims to ensure fairness and transparency in the stock market. 

SEBI Regulations for Algorithmic Trading 

SEBI first introduced guidelines for algorithmic trading in March 2008 to regulate the use of sophisticated automated trading platforms. Since then, SEBI has continually refined and updated its regulatory framework to keep pace with technological advancements and address emerging risks. The key regulations include: 

• Securities and Exchange Board of India (Stock Brokers and Sub-Brokers) Regulations, 1992 – Requires algorithmic traders to have appropriate risk control mechanisms, infrastructure, qualified personnel, etc. 
• SEBI Circular on Algorithmic Trading (March 2020) – Lays down guidelines for testing, certification and use of trading algorithms. Mandates source code audit, submission of algorithms to exchanges, real-time monitoring, etc. 
• SEBI guidelines on co-location (September 2020) – Aim to minimize latency benefits and ensure fairness in high-frequency trading. 
• SEBI guidelines on Alternative Trading Systems (November 2022) – Regulates systems where buying/selling happens without human intermediation. Introduces registration requirements for such platforms.

SEBI’s Evolving Regulatory Framework 

SEBI first introduced guidelines for algorithmic trading in March 2008 to regulate the use of automated trading platforms. The initial framework mandated approvals, system capability assessments and risk controls for algos. Over the years, SEBI expanded the scope and depth of its regulations to keep pace with the rapid technological changes in trading.  

Key expansions include the guidelines on co-location in September 2012, to create transparency in high-frequency trading from colocated servers at exchange premises. In March 2014, detailed risk management norms for algo trades were specified related to order-to-trade ratio, randomization, repeating orders etc. Regulations for direct market access through authorized vendors were introduced in 2016. 

The latest SEBI circular on algo trading in March 2020 significantly enhanced the framework. It mandated testing, audit and certification of algorithms by SEBI-registered agencies. Detailed records and audit trails were stipulated along with data security and system capability standards. Restrictions were placed on unattended algos. With its November 2022 guidelines on Alternative Trading Systems, SEBI has brought platforms using AI and ML algorithms under regulation. 

Over the past decade, SEBI has continually fine-tuned its policies in line with domestic and global developments. The timeline of key algo trading regulations is as follows: 

• March 2008 – Initial guidelines  
• September 2012 – Co-location norms 
• March 2014 – Risk management enhancements  
• February 2016 – Direct market access through APIs 
• March 2020 – Certification, testing and transparency requirements 
• November 2022 – Regulations for AI/ML-based Alternative Trading Systems   

This adaptive approach has allowed SEBI to harness technological progress while safeguarding market quality. 

Key Objectives of the Regulatory Framework 

SEBI’s regulations on algorithmic trading are designed to meet the following key objectives: 

1. Market Integrity: Prevent unfair trade practices like market manipulation, spoofing, layering, etc. by implementing checks such as price and volume limits, randomisation, etc. 
2. Investor Protection: Safeguard investors against volatile price swings and flash crashes which may occur due to flawed algorithms. Introduce circuit breakers and trading halts. 
3. Transparency: Promote pre-trade and post-trade transparency by mandating order logs, time stamps, disclosures, audit trails, etc. 
4. Accessibility: Ensure a level-playing field by minimizing latency arbitrage and keeping technological access open and equitable. 
5. System Resilience: Build stable and robust trading systems that handle millions of orders without glitches or outages. Implement rigorous testing. 
6. Cyber Security: Secure trading systems and algorithms against hacking, phishing and other cyber threats which may endanger market infrastructure. 
7. Risk Management: Enforce stricter risk controls, position limits, and margin requirements to curb excessive speculation and build shock resilience. 

Key Regulations and Guidelines 

To achieve the above objectives, SEBI has introduced several specific regulations and risk management requirements for algorithmic trading: 

• Testing, Audits and Certification: 

SEBI mandates rigorous testing and certification of all algorithmic trading systems brokers and traders use. The algorithms must be thoroughly tested in simulated environments provided by the exchanges to identify any flaws or vulnerabilities. Back-testing using historical data is made compulsory. Once tested, the systems have to be certified by registered exchanges or certification agencies authorized by SEBI. Annual audits are required to ensure compliance on an ongoing basis. 

• Logs, Records and Data Submission: 

To aid surveillance, SEBI requires algorithmic traders to maintain detailed audit trails and submit extensive data to the exchanges. This includes half-yearly system audit reports, logs of algo strategies deployed, records of key personnel involved, time stamps, order logs, trade logs, risk management controls in place etc. Any changes made to the algorithms also need to be reported. Such records enable SEBI to reconstruct market events if required and take punitive action in case of unfair trading practices. 

• Pre-trade Checks and Risk Controls: 

SEBI prescribes real-time pre-trade risk management by exchanges. This involves checks on order quantities/prices, randomizing order entry times, implementing price collars and bands, stipulating order-to-trade ratios etc. Exchanges can activate kill switches to disable disruptive algos. Dynamic position limits, leverage thresholds, and margin requirements are enforced. The objective is to put sand in the wheels – introduce friction and minimize volatility induced by unrestricted algos. 

• Monitoring Positions, Margins, Volumes: 

SEBI requires exchanges to monitor in real-time, the positions, margins and leverage build-up by algorithmic traders. Any abnormal spikes in trading volumes or order-to-trade ratios must trigger alerts for detailed investigation. Algo traders executing a large number of orders without the intention to trade could point to possible manipulation. To detect such practices, SEBI has introduced a large position reporting system requiring disclosure beyond specified thresholds. 

• Equitable Access Models:

To provide equitable access, SEBI has stipulated norms for optimal queue lengths, random sequencing and priority-based access models for co-located servers. This reduces latency arbitrage and levels the playing field. 

• Trading Halts and Circuit Breakers:

SEBI has empowered exchanges to impose index-based circuit filters and coordinated trading halts during periods of excess volatility typically triggered by algorithms. This acts as a breaker to interrupt vicious cycles and curb flash crashes or rallies. 

• Limits on Unassisted Algo Trades:

SEBI restricts certain complex algo strategies like high-frequency tick trades to only liquid securities and derivatives. Unassisted algo trades without any human supervision are prohibited in other segments to minimize risks. 

Impact and Challenges 

SEBI’s regulations have enhanced transparency, fairness and stability in algorithmic trading. However, challenges remain in the detection of complex manipulated strategies, keeping regulations updated and managing technological risks like glitches and cybercrimes. There are also concerns regarding regulatory arbitrage, where traders may shift to less regulated markets. Regulators have to ensure security as well as flexibility to foster financial innovation. 

Overall, SEBI’s framework has been lauded for balancing efficiency with appropriate safeguards. However, sustained research and policy evolution are needed to fully harness the benefits of algorithmic trading while minimizing the emerging risks it poses in the 21st-century digital marketplace. 

Conclusion 

Algorithmic trading holds the promise of quicker, more efficient and low-cost trading but also requires robust surveillance to prevent market abuse and ensure investor protection. Through proactive and adaptive regulations, SEBI has aimed to secure the integrity and stability of markets in the face of technological disruption. Its guidelines on risk controls, transparency and equitable access have made Indian markets more resilient to the challenges posed by algo-trading. Nevertheless, regulators need to continuously refine their approach in sync with financial innovation to fully realize the gains of algorithmic finance while upholding market fairness and systemic stability. 

References 

1. This article was originally written by Securities and Exchange Board of India published on Securities and Exchange Board of India (SEBI), (2020), Circular on Algorithmic Trading website. The link for the same is herein: https://www.sebi.gov.in/legal/circulars/jun-2020/guidelines-for-order-to-trade-ratio-otr-for-algorithmic-trading_46925.html
2. This article was originally written by the Securities and Exchange Board of India (Stock Brokers and Sub-Brokers) Regulations, 1992 published on the Securities and Exchange Board of India website. The link for the same is herein: https://www.sebi.gov.in/legal/regulations/feb-2022/securities-and-exchange-board-of-india-stock-brokers-regulations-1992-last-amended-on-february-23-2022-_56447.html
3. Algorithmic Trading and Information: SEBI’s Regulatory Response, The Journal of Business Perspective; Harsh Dave, 2277-7830; Edition: Volume 25 Issue 4
4. Algorithmic trading and market regulation in India, The IUP Journal of Applied Economics; Aakanksha Jalan; 0972-5924; Edition: Volume 18 Issue 4.
5. The economics of high-frequency trading: Taking stock, Annual Review of Financial Economics; Albert J. Menkveld; 1941-1367; Edition: Volume 8.
6. This article was originally written by the Securities and Exchange Board of India Guidelines for Regulation of Alternative Trading Systems published on the Securities and Exchange Board of India website. The link for the same is herein: https://www.sebi.gov.in/legal/circulars/nov-2022/guidelines-for-regulation-of-alternative-trading-systems_65017.html
7. This article was originally written by Dr. Vishal Kutchu published on Gavesana Journal of Management, Vol. 10. Issue 2 journal. The link for the same is herein: https://vjim.edu.in/i/wp-content/uploads/2019/08/Gavesana-July_December_2018-issue2.pdf#page=88
8. This article was originally written by the Securities and Exchange Board of India, Norms for algorithmic trading regarding co-location published on the Securities and Exchange Board of India website. The link for the same is herein: https://www.sebi.gov.in/legal/circulars/apr-2018/measures-to-strengthen-algorithmic-trading-and-co-location-proximity-hosting-framework_38605.html
9. This article was originally written by the Securities and Exchange Board of India, Risk Management Framework for Algorithmic Trading published on the Securities and Exchange Board of India website. The link for the same is herein: https://www.sebi.gov.in/legal/circulars/mar-2014/risk-management-framework-for-algorithmic-trading-algo-by-stock-brokers_28181.html
10. This article was originally written by the Securities and Exchange Board of India, Risk Management Framework for Algorithmic Trading published on the Securities and Exchange Board of India website. The link for the same is herein: https://www.sebi.gov.in/legal/circulars/feb-2016/direct-market-access-facility_32672.html