More young people are trading in derivatives, and making losses, SEBI study reveals
SEBI study finds around 89% of traders below 30 were loss-makers in FY26 compared to 81% of participants above 60
A recent study by the Securities and Exchange Board of India (SEBI) has revealed a shift in the demographic profile of the Indian equity derivatives market towards a younger audience. In the fiscal year 2026 (FY26), traders under the age of 30 made up 43% of individual participants, a significant increase from 31% four years prior. However, the younger demographic also exhibited a higher rate of losses, with 89% of traders under 30 being losers compared to 81% of those above 60 years old.
The study also highlighted a broader transformation in the retail derivatives market, which is attracting investors from various backgrounds, including those living in smaller towns and lower-income groups. In FY26, 75% of individual derivatives traders belonged to the annual income category of less than ₹5 lakh, accounting for 43% of turnover but 53% of aggregate losses. Additionally, 88% of traders in this income category incurred losses, compared to 81% of investors with an annual income above ₹1 crore.
Geographically, investors from smaller towns (B30) comprised about two-thirds of individual traders and nearly half of derivatives turnover. Interestingly, B30 investors account for only about one-fourth of individual mutual fund assets, suggesting a higher risk appetite in derivatives compared to their overall investment behavior. The study also revealed that traders with equity portfolios below ₹1 lakh accounted for 51% of turnover but 70% of aggregate losses, indicating a disproportionate loss rate for this group.
Furthermore, the study found that 35% of individual derivatives participants had no underlying equity portfolio at the end of FY26, indicating participation in derivatives without any cash-equity holdings. Overall, the individual trader base contracted by 18% from 1.06 crore in FY25 to 87.5 lakh in FY26. SEBI's analysis aimed to understand how trading outcomes vary with age, income, location, trading activity, and portfolio size, while cautioning against interpreting these relationships as proof of causation.
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