Think of trading and the mind goes to movies like The Big Short or The Wolf of Wall Street…Young, sharply dressed traders making big-ticket purchases and orders for their clients while feverishly tracking market indices makes for an adrenalin-pumping job. But the trading desk of today looks quite different. Machines have started assuming a bigger and more prominent role in aiding trades.

Algo Trading V/S AI Trading:

This practice is widely referred to as algorithmic trading, where a pre-programmed automated machine executes trade orders. According to Mordor Intelligence, algorithmic trading accounted for 60-73% of equity trading in the USA. Globally, the US financial markets are the largest and most liquid. Machine-driven trading has been around since the 1970s in the USA and has many benefits – faster order processing with lesser scope for errors, trade execution at the best price and low transaction costs.

Over time, AI trading has started gaining popularity. AI trading and algo trading are very different but often used interchangeably. Algo trading, as mentioned earlier, refers to the deployment of an algorithm to run trades. But it is a human being that sets these conditions – be it time, price, quantity, transaction costs. But AI trading is a step ahead for it involves an AI analysing a large amount of data to arrive at the most optimal conditions for trading and setting the conditions in play for trade. The level of human interference in AI trading is far lesser as time goes by, as the AI is constantly learning from data every hour of every trading day. If anything, AI trading is an indication of where the stock market is headed in the near future.

In India, algorithmic trading isn’t altogether new either. In 2008, the Securities & Exchange Board of India issued a circular that Indian exchanges were being opened to algorithmic trading with the introduction of Direct Market Access, which meant institutional investors could trade without human intervention for the first time. The percentage of equities being traded via algorithms went up from 10% in 2011 to 50% by 2019. By 2010, SEBI approved the launch of Smart Order Routing for investors to place their trades with the confidence of getting the best price possible from exchanges. This was followed by the NSE offering Tick by Tick data and Co Location servers to members.

So far, global markets have thrived on algo trading for it opens up markets, improves market quality, gives traders the best price, limits risk for traders and improves scope for increasing market liquidity. While the constant generation and withdrawal of orders is something SEBI plans to observe more closely, it has improved market liquidity and transaction execution.

What Could Go Wrong?

But, with all machines, there are bound to be challenges. Algo trading too comes with its share of risks. One of the most infamous incidents was the Flash Crash of 2010 in the USA when nearly $6 trillion worth stock indices including the Dow Jones, Nasdaq Composite and S&P500 collapsed and recovered rapidly. Five years later, an investigation led by the US Department of Justice revealed fraud and market manipulation as causes to this free fall. Specifically, spoofing algorithms were used to manipulate the market and outpace other participants in the trade. Now, spoofing is banned. Another incident was when US-based Knight Financial Group launched a new algorithmic trading software. But it was losing $13 mn every minute and when the software was finally shut, more than $607mn was lost. Back in India, in 2012, Emkay Global Financial Services placed a series of incorrect orders, sending the NSE in a tumble as trade halted for 15 mins, pulling the Nifty index down by a precipitous 900 points and eroding investor wealth to the tune of INR 10 lakh crore.

These incidents notwithstanding, there are immense benefits to using algo trading, AI trading and machines to monitor and drive trades. With the opening of APIs by new-age, tech savvy brokers like Zerodha and Upstox and opening up algo trading to retail investors, there’s a huge opportunity to a greater subsection of the Indian population to trade. Most founders of companies specializing in developing investing solutions believe India can very soon rival the USA in terms of volumes generated through algo trading.

Why Regulation?

But this relies on a regulatory framework, something that even seasoned investors and brokers are advocating strongly. With retail investors now being given access to algo trading, there is rising consensus for regulations in order to avoid defaults, poor risk assessment and generally, bad trades. While a company like Zerodha has opened its API to outsiders, there’s a fee per month and the company decides who to grant API access to. Even if a person can afford the fee, the API integration isn’t permitted on the Zerodha trading platform. The co-location server controversy which found the NSE giving preferential treatment to some of its members for server co-location is facing ire for having flouted norms continually in the past and SEBI not doing enough to police its actions.

It shouldn’t have to take a massive market crash or some kind of dubious scam for the entire practice to get villainized. Regulations work as guard rails for tech like algo trading to reap benefits in a market-friendly manner.