Скачать или смотреть SEBI has an algo trading plan for retail investors

SEBI has an algo trading plan for retail investors

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India has nearly 10 crore retail investors. That’s one in every five households across the country!

Many of these investors are everyday folks like us, juggling full-time jobs. So while the stock market might lure us with the prospect of making some cool profits, keeping track of price tickers all day is tough and sometimes even impractical. That could often mean higher chances of losses or stepping away from markets altogether.

Enter algorithmic trading, or algo trading, which is a game-changer for situations like these. Think of it like having a computer trade for you. You set rules for price, timing and volume, and it executes trades automatically. For instance, if you’re interested in textile stocks, you could program an algorithm to buy stocks in this sector when prices rise 5% over a week, assuming that demand is strong, or sell when they drop by 5%. The best part? You don’t have to stay glued to the screen. It’s all automated.

But here’s the thing. Despite all the buzz around algo trading, Indian retail investors have largely been left out of it. That’s because institutional investors have enjoyed greater freedom since algo trading launched in 2008. But retail investors only got a set of these regulations in 2021. These rules placed the responsibility for algo trading on brokers, meaning retail investors had to rely on pre-built algorithms provided by brokers, which were executed exclusively on their servers.

And this setup wasn’t ideal. Just think about it. A glitch in the broker’s system, a loophole in their strategy or even manipulation from their end could lead to massive losses for retail investors. Unregulated algo providers also offered risky services, leaving investors with no way to address grievances. SEBI seemed to catch on to these problems and naturally it cracked down.

But it didn’t stop there. It also realised that simply clamping down on algo trading wasn’t the solution. It needed to go a step further, regulate the space and take charge of overseeing it.

And there’s enough reason that nudged it to think on these lines. A recent study revealed that individual traders lost over ₹61,000 crores in the equity F&O segment in FY24, while large entities using trading algorithms, like proprietary traders and foreign investors, walked away with gross profits of ₹33,000 crores and ₹28,000 crores, respectively.

Clearly, retail investors were fighting a losing battle against sophisticated algorithms. And that’s exactly why SEBI is now working to make algo trading more accessible to retail investors, in a safer and well-regulated environment.

And SEBI’s suggestions are simple.

And these regulations are actually an upgrade from their 2021 version.

And this thoughtful regulation could transform India’s markets for the better. For context, today, around 50% of traders in India use algorithms, compared to 60–70% in markets like the US and Europe. And making algo trading more accessible could bring more accurate and cost-effective trades.

Moreover, algorithms can analyse and execute trades at lightning speed and eliminate emotional biases like fear or greed that we humans have, reducing the chances of poor decisions. So yeah, this truly feels like a step forward.

It’s not all smooth sailing, though.

One potential hurdle lies in the requirement for stock exchanges to approve every trading algorithm. According to the Indian Association of Investment Professionals, a similar rule in SEBI’s 2021 regulations could make things tricky. Because trading strategies need to adapt quickly to changing market conditions. And by the time an exchange approves a strategy, it might already be outdated and the trading opportunity could slip away.

So this time, SEBI has suggested fast-track registration for certain algos, aiming for quicker approvals. But the turnaround time is still up to the exchanges, so we’ll have to see how well it works in practice.

And even with these regulations, algo trading isn’t immune to Black Swan events — those rare, unpredictable shocks. Take the example of textile stocks we mentioned earlier. If an algo is programmed to buy when prices rise 5% in a week, an unexpected event, like the Bangladesh crisis pushing textile stocks up by 20% overnight, could throw it off. The algorithm might be in a situation where it’s unable to handle such wild swings and end up buying or selling at the wrong time, causing poorly timed trades and huge losses.

That’s where stock exchanges could step in. If they not only back-test algorithms with past data but also stress-test them for extreme scenarios, much like they do with equity derivatives like F&O, it could reduce risks and improve preparedness.

For now, though, these rules are just part of a consultation paper SEBI floated last week. And we’ll only have to wait and see how things shape up after the feedback rolls in.