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© Indic Pacific Legal Research LLP.

For articles published in VISUAL LEGAL ANALYTICA, you may refer to the editorial guidelines for more information.

Writer's pictureParvathy Arun

The 'Algorithmic' Sophistry of High Frequency Trading in India's Derivatives Market

The author is a Research Intern at the Indian Society of Artificial Intelligence and Law as October 2024.

 

A recent study conducted by the market regulator of the country, the Securities and Exchange Board of India (SEBI), shed light on tectonic disparities in the market space concerning equity derivatives. Per the study, the utilisation of algorithm trading for the purposes of proprietary trading and that of foreign funds resulted in gross profits that totalled an amount of ₹588.4 billion ($7 billion) from having traded in the equity derivates of Indian markets in the Financial Year that ended on March’24.[1]


However, it was noted that in a disparate stark contrast, several individual traders faced monumental consequential losses.


The study further detailed that almost 93% of the individual traders had suffered losses in the Equity Futures and Options (F&O) Segment, in the preceding three years, that is, from the financial years of 2022 to 2024; the aggregate losses totalling to an amount exceeding ₹1.8 lakh crore.

Notably, in the immediately preceding Financial Year [2023 – March 2024] alone, the net losses incurred among individual traders approximated an amount of ₹75,000 crore.


The findings of SEBI underscore the challenges faced by individual traders when the former is having to compete against a more technologically furthered, well-funded entity in the market space of derivatives. The insight clearly contends that institutional entities that have inculcated algo-trading strategies have a clear competitive edge over those who lack the former, i.e., individual traders.



Understanding the Intricacies of Algorithm Trading


Figure 1: High-Frequency Trading, explained and depicted.
Figure 1: High-Frequency Trading, explained and depicted.

High-Frequency Trading refers to the over-arching aspect of algorithm trading which is latency sensitive and done through the medium of an automated platform, that essentially focuses on trading. The same is facilitated through advanced computational systems that are technically capable of executing large orders ate a more efficient speed in order to achieve optimal prices at a level humans cannot match.


The dominancy of algorithms in the domain of the global landscape of financial markets, have had an exponential growth the past decade. High-frequency trading (HFT) algorithms, aim at the execution of trades within fractions of a second.


This high-speed computational system places institutional investors at a more profitable and higher pedestal than individual traders, who typically place reliance on manual trading strategies and consequently have an evident lack access in sophisticated analytics and real-time processing trading systems.

Furthermore, HFT allows traders to trade a larger amount of shares frequently, by processing differences within marginal prices in split of a second, thereafter ensuring accuracy in the executing of a trade and enhancement of market liquidity.


The premise is also paralleled in the Indian equity derivatives market with HFT firms reaping substantial profits. The study conducted by the India’s market regulator evidently sheds light on the comparable gains and losses among institutional traders and individual traders respectively. The insight expounds upon the sophistries on the competitive dynamics of the country’s derivatives market, and its superficial regulation over manual trading and computational trading.


The Competitive Landscape of the Derivatives Market: The Odds Stacked Against Individual Traders


The study revealed a disadvantageous plight of retail traders, with every nine out of ten retail traders having incurred losses over the preceding three FY. This thereafter raises the contentious debate surrounding viability of individual traders and market dynamics in the landscape of derivatives market. The lack of the requisite support and resources to individual traders would make the sustainability of the former difficult, especially with the backdrop of a growing trend in algorithm trading. HFT has been subjected to critique by several professionals, with the latter holding the former in contempt for unbalancing the playing field of derivatives market. Other disadvantageous impediments brought firth by such trading mechanism include:


  • Market Noise

  • Price volatility

  • Strengthening of the mechanism of surveillance

  • Heavier imposition of costs

  • Market manipulation and consequent disruption in the structure of capital markets


The Need to Regulate the Technological 'Arms Race' in Trading


Given the evident differences in mechanisms of trading, there arises a pressing need for improving tools of trading and ensuring easier access to related educational resources for individual investors.


SEBI, the capital market regulator of India, has the prerogative obligation to regulate such disparities. In 2016, a discussion paper was released by the former that attempted to address the various issues relating to HFT mechanisms.

The same was done with the premise of instituting an environment of equitable and fair marketspace for every stakeholder therein involved. SEBI proposed the institution of a “Co-Location facility” done on a shared-basis that do not allow the installation of individual servers. This proposed move aims to potentially reduce the latency of having access to the trading system, and attempting to provide a tick-by-tick feed of data, that would be given free of cost to all trading stakeholders.


SEBI further proposed a review mechanism over the requirements of trading with respect to usage of algo-trading softwares. The same is furthered by mandating stock exchanges for strengthening the regulatory framework of algo-trading, and consequently lead to the institution of a simulated environment of market for an initial test of the software, prior to its real-time application.[2]


Figure 2: SEBI's Algo-trading Regulatory Proposals
Figure 2: SEBI's Algo-trading Regulatory Proposals

To add, SEBI has also undertaken a slew of measures to regulate the algo-trading and HFT. This includes[3]:


  • Minimum time of rest for orders of stock

  • Institution of a mechanism of maximum-order-message to measurements of trade, ratio

  • Randomisation of the orders in stock and a review system on the tick-by-tick feed of data

  • Institution of congestion charges to reduce the load on the market


Thus, despite the rather unregulated stride on HFT in India, SEBI in vide has an overarching authority over the same through the provisions of SEBI Act, 1992. However, the same is prevailing in a rudimentary existence and thereafter, continues to usher in an age of unhealthy competitiveness among the traders in a capital market.



 

References


[1] Newsdesk, High Speed Traders reap $7bn profit from India’s options market, https://www.thenews.com.pk/print/1233452-high-speed-traders-reap-7bn-profit-from-india-s-options-market (last visited on 6 Oct, 2024).

[2] Amit K Kashyap, et. al., Legality and issues relating to HFT in India, Taxmann, https://www.taxmann.com/research/company-and-sebi/top-story/105010000000017103/legality-and-issues-related-to-high-frequency-trading-in-india-experts-opinion (last visited on 6 Oct, 2024).

[3] Id.

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