The use of algorithms and application programming interfaces (APIs) to automate stock market trading in India can put human traders at a disadvantage, says a study. Algorithmic trading (algo trading) involves the use of advanced software programs to automate market trades at high speeds that conventional human-executed trades cannot match.
Experts say that for algorithmic trading engines, speed of execution, availability of real-time market data and minimum latency have become key success factors as already milliseconds can make a difference.
Krishna Prasanna, professor at the department of management studies (DoMS) at IIT Madras, said the use of algorithms in trading by PATs and BATs causes a simulated price disparity which, in turn, robs the market of its natural liquidity.
“Typically, algorithmic traders enter orders and subsequently cancel them very quickly. Now, looking at the placed orders, the price of a stock moves, based on which human traders would also place their orders. But the algo traders have already canceled their own orders. This happens within minutes. Our major finding saw how this activity from PATs drains out market liquidity,” he explained.
The professor pointed out that in the stock market, liquidity refers to the efficiency at which an equity can be bought and subsequently sold, without drastically affecting its market price. “When BATs put a lot of orders, this essentially simulates liquidity in the market, when it is not there. PATs and BATs often play hide and seek in the market, because in India, some institutions do both forms of trading. In such a situation, orders placed by BATs crowd out those placed by PATs.”
As study, the study found that algorithmic trading can put the individual, human trader at a disadvantage of losing out to more efficient technologies such as the automation algorithms in stock market trading.
Rahul Jain, president and head of personal wealth at Edelweiss Wealth Management, believes it is theoretically possible for retail investors entering this segment to get misguided. This is because the regulation framework is not strong enough. Jain said the aspect of establishing a grievance redressal mechanism in the market towards algorithmic traders could be a crucial aspect for retail investors to come to India.
“If a redressal mechanism is put in place, miscreants in the industry will go down, which is important. Regulations will increase the confidence of retail investors who wish to take up algorithmic trading to enhance their trading practices. If this happens, then large retail investments can start flowing into the market.”
Prasanna highlighted that no stock exchange, in India or elsewhere, would want to peg back algorithmic trading entirely as everyone wants liquidity. He believes effective regulation could reduce the feeling among retail investors of not having enough fair opportunity to compete with algorithmic traders in the market. “Western markets have a clear classification of who are PATs and who are BATs. In India, the same institution does all the activities, since it is not very well classified. A conglomerate behavior is clearly there in India, which is something that will require a certain degree of regulation,” the professor said.
Jain says that once Sebi introduces regulations to control technology-driven market trades, there could be an initial impact. “It can an impact at the start as it would require firms to go through processes and get approvals,” he said. “But, if the processes are convenient, then it is certainly scalable. Such regulations would protect market suitability for retail clients, as well as redressal procedures.”