As retail participation in the futures and options (F&O) segment continues to surge, the odds remain heavily stacked against individual traders, with institutional and algorithmic players capturing a big share of market profits, according to Archit Gupta, chief executive of ClearTax.
Citing Securities and Exchange Board of India () data, Gupta told Mint in an interview that while individual traders collectively lost ₹74,812 crore in FY24, proprietary trading desks and foreign portfolio investors (FPIs) together booked over ₹61,000 crore in gross profits, the majority of which came through algorithmic trading.
He pointed out that the rapid rise in index options trading, with average daily premium turnover surging from ₹4,359 crore in FY20 to ₹64,881 crore in FY25 has intensified the structural disadvantages faced by retail traders. In addition to market competition, retail participants also have to bear securities transaction tax (STT), brokerage charges, exchange fees, GST and slab-rate taxation on their net trading profits.
Who is at fault? Poor behaviour or algorithmic trading
According to Gupta, retail traders lose money in derivatives mainly due to two factors: trading behaviour and structural disadvantages. However, he noted that their impact is not equal.
A September 2024 SEBI study found that over 9 out of 10 individual traders in the equity F&O segment continue to incur significant losses. Despite the setbacks, more than 75% of loss-making traders continued trading in . Additionally, over 75% of individual F&O traders in FY24 had declared an annual income of less than ₹5 lakh. This trend persisted the following year as well. A July 2025 SEBI study showed that 91% of the 9.6 million individual participants ended up with net losses.
“Most of these losses come from easily observable habits: trading too much, trying to win back losses quickly, taking on positions too big for their account size, holding on to losing trades while selling winners too soon, ignoring trading costs, and trading without stop losses,” Gupta pointed out.
Speaking about algorithmic systems, Gupta said they operate in fractions of a second, place their servers inside exchange premises for faster execution, and often pay significantly lower trading costs than retail investors. All these factors give them an edge over individual traders.
How are algorithms primarily making profits?
According to Gupta, algorithmic profits in Indian markets come from three main areas that work together: Acting as a middleman (liquidity provision), finding pricing gaps (statistical arbitrage), and moving faster than everyone else.
“The biggest source of these returns is market making. Algorithms constantly offer to buy and sell active contracts, pocketing the tiny price difference (the bid-ask spread) on every single trade,” he said.
The second major driver is statistical arbitrage. Here, algorithms look for brief moments when related assets are priced incorrectly. For example, a slight mismatch between Nifty futures and the actual Nifty index, or an option price that strays from its normal mathematical value.
In this case, Gupta noted that the computer program instantly trades both sides to lock in a profit for when the prices eventually realign. Doing this successfully requires massive computing power, perfect real-time data, and extreme speed – resources that everyday retail investors simply do not have.
“Both of these strategies rely heavily on high-frequency trading infrastructure. These trading programs operate in fractions of a second because their computers are housed in the exact same building as the. This physical closeness lets algorithms see price changes and place orders before a regular retail trader’s screen can even refresh,” he said.
Can a manual retail trader maintain an edge without automation?
Although a manual retail trader cannot beat a computer algorithm in speed, trading costs, or data processing, they can instead focus on the specific areas where algorithms are naturally weaker. Here are some ways shared by Gupta through which retail traders can stay ahead:
- Change your time horizon: Algorithms are much less effective over a period of days or weeks, where big-picture factors like the broader economy, company earnings, and government policies matter more than raw speed. Hence, a retail traders who move away from rapid daily options trading and hold futures or longer-term options for days or weeks enter a space where algorithms have less of a natural advantage.
- Use defined-risk strategies: Instead of making aggressive, highly risky bets, use strategies like spreads, iron condors, or calendar spreads, as they put a strict cap on potential losses, and reduces the hidden costs of trading, and requires fewer trades to make a profit.
- Try to control your trade sizes: The most underrated advantage a retail trader can have is the discipline to risk approximately 2% to 5% of their total capital on a single trade, instead of a 20% to 30%. He advised traders to keep their bets small.
- Try to generally trade less often: The small portion of retail F&O traders who actually make money trade much less frequently than those who lose money. The high costs of trading alone make rapid, manual trading mathematically impossible for a retail trader to sustain over time.