Derivatives Trap: Indian Retail Investors Are At The Mercy Of Techno-Giants

Indian markets regulator Securities & Exchange Board of India (SEBI) passing an order barring Jane Street Capital, a New York-based trader, shouldn’t come as a surprise to anyone.

A study released by the regulator in September 2024 showed that India’s trigger-happy retail traders lost around Rs 1,81,000 crore or $22 billion in futures options between 2021 and 2024. Moreover, only 7.2% of the retail traders made a profit in the derivatives segment.

In 2023-24, some 91% of retail traders made losses while trading in derivatives adding up to around Rs 52,000 crore.

The Glaring Divide

Most of the profits were generated by larger entities that used trading algorithms, with 97% of foreign investors' profits and 96% of proprietary traders' profits coming from algorithmic trading, SEBI said.

The proportion of retail traders below 30 years of age rose to 43% in fiscal year 2024, and most individual traders belonged to low-income groups, earning less than Rs 5,00,000 annually, SEBI said.

Not surprisingly, India is the world's largest derivatives market, accounting for nearly 60% of global equity derivative trading volumes of 7.3 billion trades in April, a Reuters report quoting the Futures Industry Association said.

And yet the people behaved as if Jane Street dropped out of the sky.

But Jane Street only painfully highlights the stark gap between the knows and know-nots.

Worse, Jane Street exposes the cruel role that technology plays in depriving the least smart and savvy of their savings and transferring them to the rich and techno-literate.

Jane Street’s description of itself should tell you why.

It says it hires researchers and traders whose ideas and algorithms are informed by a deep mathematical fluency, and technologists who understand their systems from the hardware on up.

Moreover, Jane Street says or perhaps boasts that it builds low latency networks, hack compilers and designs distributed systems. And wraps up by saying that deep learning is the future of quantitative trading.

Lamb Vs Wolves

On the other side, a recent viral video showed an Uber driver claiming to have lost Rs 2.5 lakh in options trading last year.

He also added helpfully that he did not lose any money in stocks. Instead all of it was lost in options trading. Which he also said he would get back into. The only difference, he would do so when he had enough capital.

His annual income: around Rs 2.5 lakh.

The Uber driver, whose video I saw, seemed to take it all in his stride and seemed to be sharing a life experience rather than pouring out his woes.

Good for him. But it is not just Jane Street’s hyper-smart quant Wall Street traders he is ranged against.

There is another layer, right at home.

These are the smart techies sitting in glass and steel complexes in Bengaluru behind slick stockbroking apps, constantly smoothening out chinks in user experience so an options trader, whether sitting in a car, train or just walking can do deals on the go.

Meanwhile, their marketing colleagues create attractive “how to invest” videos and social content that lures mostly first time traders into trading apps all year round and click by click.

Together the apps herd unsuspecting traders like the Uber driver into an arena where quite literally the wolves of Wall Street like Jane Street Capital are waiting.

The Uber driver, or the millions like him or the 91%, never stood a chance.

The game was always in favour of the Jane Street’s, whose existence hopefully the Uber driver will now learn about and understand his limits.

What Are The Guardrails?

The Take has argued in the past for more friction in trading.

While the regulators have responded with several moves to reduce trading speculation and to tighten the flow of unsecured loans that could fund it, the steps have clearly not been enough.

Regulators also tend to focus on overall systemic stability, which isn’t significantly affected by retail investors losing their shirts, because the amounts involved are still relatively small.

The social impact of course is something else.

The Uber driver has a phone hooked to the dashboard.

The phone connects him with passengers on an app. A swipe presumably takes him to the trading screen of a broking app.

This is a story that plays out one way or the other across more than 800 million smartphones in India.

Some gamble on IPL scores. Others gamble with options trading.

The common factor is access and the lack of awareness of what lies on the other side.

The slicker the app, the faster the wealth destruction.