[By Jay Shah and Aditya Sharma]
The authors are students of Gujarat National Law University
Introduction
Algorithmic trading refers to a method of trading wherein an algorithm is used to execute trade setups on basis of information as input by the trader in terms of, time, price, quantity and other other mathematical models. Essentially, algorithms scan the markets for appropriate trade setups, and when they find the proper ones, trades are executed and managed as per the instructions specified in the codes. Algo trading is incorporated as they generate profits faster than humans can and allow the user to take advantage of small directional movement of any stock.
Stance of the Regulator: Evolution
Securities and Exchange Board of India (‘SEBI’) is devising dedicated guidelines or regulations to govern how algo trading is to work and how say, in the event of an unlawful act, the remedy is to be exercised by the aggrieved when algo-trading takes centre stage.
SEBI has released multiple circulars in attempt to regulate to algo trading. These standalone guidelines released in 2012, 2013 and 2015 deal with redressal mechanism, monitoring process, measures to put in place to disincentivize high daily order-to-trade ratio and procedure for auditing algo trading systems. Further, the Discussion Paper of 2016 attempted to clarify the various technical concepts relating to algo trading. In this paper, algo trading was touted to be the broader concept, which provides greater speed to stock trading and also offers anonymity.
SEBI’s outlook towards algo-trading becomes clearer from the discussions that took place in April, 2018. These showed SEBI’s intent to restrict unfair use of algo trading. In this April 2018 discussion, SEBI proposed to discourage algo traders from placing huge orders and then subsequently cancelling them within a short span of time by prescribing a ‘minimum resting time’. This step was intended to lower down the instances of frequent cancellation of orders by the traders that intends to create phantom liquidity in the market.
Post this, the Consultation Paper shifted the focus to retail investors. It proposed a potential framework that may be followed to engage in algo trading, which includes application programming interface (‘API’) access and automation of trades. In this backdrop , came a press release in June, 2022. The Consultation Paper seeks to classify all orders emanating from an API as an algo order and be subject to control by the stock broker. The APIs shall be tagged with the unique algo ID provided by the exchange. Thus, the stock broker shall have a mandate to obtain approval of all the algorithms from the concerned exchange irrespective of whether the same is used for actual trading or not.. As per the authors, we propose a scenario wherein the stock brokers shoulder the responsibility of procuring requisite approvals in the cases of deployment of algorithmic trading by third-party algo providers, in line with the Consultation Paper. The stock brokers however, argue that it would be a tedious task for them to obtain approvals of algorithms enabled through APIs, since there can be numerous customized algo strategies that could be deployed by third-party vendors.
Another circular, issued in September, 2022 also points to the cautious stance SEBI has long taken about algo trading. Vide this circular, SEBI issued strict guidelines for Stock Brokers providing algorithmic trading services. In brief, the same states that Stock Brokers who provide algorithmic trading services shall not –
- Make any reference to the past or expected future return/ performance of the algorithm.
- Associate with any platform providing any reference to the past or expected future return/ performance of the algorithm.
In addition, Stock Brokers were required to monitor the compliance of this circular and submit a compliance report before SEBI before 01.11.2022.
Outlook of the SEC
Securities Exchange Commission (‘SEC’) actions in the U.S. have been on various occasions replicated by SEBI after appropriate customisations in the Indian securities market. It is no surprise that SEBI sought guidance from the SEC on the matter.
In August 2020, the SEC released a staff report, which dealt with algorithmic trading in the U.S. capital markets. The report acknowledged the rapid growth of algo trading and the object of the report was to ensure that the interest of investors is not compromised. The report states that SEC undertook various measures, and is constantly attempting to increase transparency, mitigate volatility, enhance stability and otherwise improve market integrity. Apart from this SEC does not have a dedicated set of provisions that govern algo trading.
Further, the SEC’s outlook is a little more relaxed in comparison to that of SEBI, as SEC in the report mentioned above discusses at great length the benefits brought on the table by algo trading. The SEC also opines that the efficacy of such mechanisms was greatly highlighted by the Covid-19 pandemic as well.
Penalty Mechanism
The parameters governing the imposition of penalty are unclear under the limited SEBI jurisprudence. The same is generally left at the behest of the stock exchanges. The NSE and the BSE have their threshold for levying penal charges when algorithms are used to manipulate the market. The guidelines governing such imposition have been laid down by the SEBI via its circular, as discussed above. The onus put on the stock exchanges in this respect is grave. SEBI, in this regard, has ensured that the stock exchanges are doing the needful to monitor algorithmic trading in isolation and its overall impact on market operations. SEBI’s strict imposition of penalty on the NSE in the matter of NSE Dark Fibre signifies the regulator’s stance in this respect. There is an inherent urge to regulate algo trading; however, with standalone circulars and notifications, only so much can be done. Even in terms of penalty imposition, which could very well become the bone of contention in matters dealing with algo trading, there is little clarity. For this particular instance, the violation was traced in a Circular from March 2012.
Regarding penalty imposition, the regime in the EU must be taken note of. As per the European regulatory regime, the threshold is kept at the order to trade ratio in algorithmic trading and other forms of high frequency trading. The ESMA has slowly helped build a robust mechanism that combines the regulator’s role with those of the trading venues wherein such orders are received and executed. Penalties are imposed in Europe if the participants at the trading venue exceed the daily order to trade ratio. This ratio generally depends on the number of orders cancelled within a short span and tackles one major issue posed by the wrongful use of algo trading. In contrast, the SEBI procedure to impose penalties on violations arising from algorithmic trading is unclear and highly ambiguous.
Way Forward
SEBI attempts to restrict algo high-frequency trading to intermediaries and agencies. The question further demands exploring the outcomes if algo trading is further used by High Net-Worth Investors (‘HNIs’). Currently, algo trading is used to buy and sell stocks at a given price. But with the development of artificial intelligence, how instrumental artificial intelligence would become is unimaginable.
SEBI must ensure algorithms are restricted from being used to make profits as it hampers the market’s trading system. Currently, online platforms are equipped with historically devised trading indicators, but algorithms are not used to put orders and book profits independently. Such development can be harmful because the stock market is a zero-sum game. This implies that one party making a profit is the loss of another party. Suppose an algorithm is allowed to trade in place of individuals. In that case, it reduces the probability of loss to practically zero as an algorithm can assess bid and offer side volumes and place trade in a manner that maximizes the gains.
The preamble of the SEBI Act, 1992, provides that the foremost endeavour of SEBI is to safeguard the interest of retail investors. This is because retail investor falls in the category of amateur traders who do not have the skill and competence like Qualified Institutional Buyers (‘QIBs’) or even HNIs. This aggregates into QIB using algorithm trading, which would make profits through precise market movement analysis based on pre-existing indicators and evaluation of bid and offer pressure. This would provide accurate entry and exit, thereby, maximum returns.
This would severely erode the confidence of retail investors as they would be the group that does not have access to such technologies and would bear the loss of incorrect entry and exit due to limited knowledge and resources. It cannot be argued that retail investors could opt for investing through QIB or investment firms as it would lead to profits based on which entity holds the superior algorithm rather than the ability of investors and firms.
The securities market today is heavily data-driven and highly connected. Algo trading is growing in significance and may soon end up becoming central to how our capital markets function. The authors believe that algo trading will continue to grow, as does the SEBI, given their own statistics as well as the proactive approach to act towards establishing a robust regulatory framework to govern the same. Several provisions with regards to monitoring the functioning of algorithmic trading to identifying and penalising the wrongful use of the same can be transplanted from the regimes elsewhere in the world, such as the EU.