F&O traders lose money in India: SEBI explains why

Retail trading in futures and options (F&O) is one of the most discussed topics on Indian finance social media, especially the claim that “9 out of 10 traders lose money”. The recent round of posts is being backed by SEBI’s findings, which show the headline may sound dramatic but is broadly consistent with the data. The regulator’s work also adds detail on where the losses come from and why they persist even as participation changes. A key takeaway is that the issue is not limited to first-time traders. Another is that losses are not only about getting market direction wrong. The combination of short-dated options, heavy turnover relative to capital, and costs creates a difficult math problem for most individuals. Behavioural patterns like revenge trading and overconfidence then amplify the damage. The result is a market where smaller traders often operate with fewer tools than larger participants.

What SEBI data shows about retail F&O outcomes

SEBI’s findings suggest the odds remain poor for individual traders even if aggregate losses have reduced. Nearly nine out of ten individual traders continued to lose money in FY26, according to the study cited in social media discussions. In FY25, 91% of individual retail F&O traders lost money, with net retail losses crossing ₹1.05 lakh crore. Over FY22 to FY24, 93% of retail traders booked aggregate losses exceeding ₹1.8 lakh crore. The studies also point to concentration of losses, not just broad underperformance. Around 23% of traders were responsible for nearly 90% of the losses. Losses were also described as “direction-agnostic”, with individuals losing in options every quarter, even when Nifty rallied 9%. For many readers, the message is that frequency and structure matter as much as market calls.

Fewer participants, lower aggregate losses, but poor odds

One reason aggregate losses reduced was that fewer traders participated after SEBI introduced measures to cool excessive speculation. The regulator’s steps included higher contract sizes for index derivatives, fewer weekly index expiries, and upfront collection of option premiums. These changes were aimed at reducing speculative retail activity and improving investor protection. However, the probability of loss for individuals remained high even after these changes. Social media summaries of the study stress that the issue is more about how traders use the product than how many people trade it. In other words, outcomes did not automatically improve because the market was “cooled”. The remaining active set still showed behaviour heavily skewed toward speculative, short-duration trading. That helps explain why the loss rate remained near the “9 out of 10” level.

Options are the main driver of retail losses

Across the cited findings, options trading accounted for the overwhelming majority of damage. Options accounted for more than 90% of retail losses in the FY22 to FY24 period mentioned in the context. For FY26, around 92% of the aggregate losses incurred by individuals came from options trading. The study also notes that retail participation was overwhelmingly concentrated in option buying. Nearly 97% of traders predominantly followed option-buying strategies, while only around 2% were primarily options sellers. Losses were also heavily concentrated among option buyers, with around 92% of retail losses coming from option buyers. This matters because option buying requires not just a correct direction but also correct timing and a move large enough to overcome the premium paid. SEBI-linked commentary also notes that even when the underlying moves in the trader’s favour, the option may not gain enough to cover the premium.

The near-expiry trap: 0DTE and ultra-short contracts

Short-duration trading is a recurring theme across the discussion. About 59% of index-options turnover in FY26 was in contracts expiring the same day (0DTE). Around 75% was within one day, and about 97% within one week. These contracts are popular because they require less capital and can move sharply. But they also lose value quickly, leaving very little room for error if the move is small or delayed. SEBI-linked commentary highlights that highly short-term trading makes outcomes very sensitive to timing and volatility. In practice, this can turn trading into repeated bets where a position can lose most of its value within hours. The high share of 0DTE volume also explains why many traders report whipsaw outcomes even on seemingly correct market views. The structure creates a steep challenge for consistent net profitability.

Leverage and turnover: losses rise with intensity

Leverage is repeatedly cited as a major reason individuals lose money. Derivatives can expose traders to many times their underlying capital, so relatively small market moves can translate into disproportionately large losses, as noted by Ventura’s head of research Vinit Bolinjkar in the shared context. Social media summaries of the SEBI findings highlight that this is not a “small-trader only” problem. In fact, loss probability increased with turnover, with about 95% of traders with options turnover above ₹10 crore losing money. The study also showed a sharp mismatch between capital base and activity: traders with portfolios under ₹1 lakh traded at 1,665x their portfolio value. A subset with turnover above ₹1 crore was 13% of traders but accounted for 52% of all losses. Separately, 35% of derivatives traders had zero equity holdings, indicating participation without an underlying portfolio base. These details suggest that position sizing and turnover intensity are central to the outcomes.

Behavioural mistakes that compound drawdowns

The posts also point to behavioural mistakes that can magnify losses. Fear of missing out (FOMO) is frequently mentioned as a trigger for entering trades after seeing others post gains. Overconfidence can lead traders to believe they can consistently predict short-term market movements. Revenge trading is another cited pattern, where losses trigger attempts to recover money through larger or more frequent positions. One data point from the context shows that 55% of traders resorted to buying more to offset losses, which aligns with the idea of averaging into losing trades. There is also a “misplaced expectations” problem: 40% of novice traders were attracted by the idea of quick and easy profits. Another cited perception gap is that 48% believed 30% to 50% of traders consistently achieve “good returns” from F&O, which suggests unrealistic benchmarks. Together, these behaviours can push traders toward higher risk at exactly the wrong time.

Strategy gaps: advice, execution, and stop-loss usage

Another thread running through the discussion is a lack of structured process. A cited finding says 32% of novice F&O traders struggle with market analysis, and 13% attribute losses to inadequate trading knowledge. Cumulatively, 45% pointed to lack of sufficient understanding as a major factor behind losses. Execution is also an issue, with 35% of traders not implementing any specific trading strategy. Some reported being unable to execute strategies like straddle and strangle despite theoretical knowledge. Reliance on non-professional advice is common, with 53% relying on family, friends, or trending social media inputs, which can lead to uninformed decisions. Risk controls appear underused: 42% consistently used stop-loss orders in only half their trades, while 16% rarely used them. The context also notes that only 5% used algorithmic strategies provided by specialised companies or websites. In a fast-moving derivatives market, these gaps can become costly.

Costs and option pricing complexity widen the gap

Transaction costs are a significant part of the retail P&L problem in high-turnover strategies. Individual traders incurred about ₹25,000 crore of transaction costs in FY26, according to the shared commentary. That matters because costs can materially widen the difference between gross trading outcomes and realised net returns, especially when trades are frequent. Beyond costs, the option product itself is complex for many participants. Many traders focus only on direction while ignoring timing, volatility, and premium decay. The context also highlights a common outcome: even when the market moves in a trader’s favour, the option may not rise enough to cover the premium paid. In short-dated options, this challenge becomes more severe because time decay is faster. When combined with frequent trading, small edge deficits can quickly compound. This is one reason losses can persist even in broadly rising markets.

Small investors vs prop desks: different tools, same contracts

SEBI’s study also points to who bears the losses and who benefits on the other side. Retail losses in FY26 were concentrated among small investors, with traders holding equity portfolios of less than ₹1 lakh accounting for about 70% of aggregate losses. At the same time, proprietary traders made gross trading profits of around ₹44,000 crore, as cited in the context. The market structure allows both to trade the same contracts, but the tools available to each side are different. Institutional and proprietary desks are described as operating with better systems, faster execution, deeper risk controls, and algorithmic strategies. Retail activity, meanwhile, is heavily concentrated in short-dated option buying with limited capital. The imbalance does not guarantee a loss on every trade, but it helps explain why outcomes are persistently poor in aggregate. It also matches the observation that experience did not improve results meaningfully, with loss rates nearly identical for new traders (87.8%) and experienced traders (87.7%).

Key figures discussed widely from SEBI-linked findings