Guide · Retail derivatives · SEBI F&O losses, FY25

How much do retail F&O traders lose in India, and what separates the minority who do not

The headline is easy to quote and easy to misread. It is not that F&O is uniquely rigged; it is that the retail aggregate is arithmetically negative-sum once frictions are counted, and that a handful of participants absorb what the majority give up. This guide sets out exactly what the SEBI studies measured, why the pool drains the way it does, and the sizing mathematics that decides who is still trading after a bad run. Where a number is illustrative rather than measured, it is labelled as such, and no claim is made about anyone's results.

What the SEBI studies actually measured

Two studies anchor the picture, and conflating them is the most common error in coverage. The earlier one, published by SEBI in September 2024, aggregated three financial years, FY22 to FY24, and reported that 93 percent of individual traders incurred net losses in the equity derivatives segment, with aggregate net losses exceeding ₹1.8 lakh crore across those three years. The newer, single-year update covers FY25: individual-trader net losses of ₹1,05,603 crore, up about 41 percent from ₹74,812 crore the year before, with over 91 percent net loss-making.

Three properties of the methodology matter for reading the number correctly. First, the figures are net, computed after transaction costs, not gross trading profit and loss, so they already fold in the frictions discussed below. Second, the FY25 study drew on the client base of the top thirteen brokers, about 96 lakh unique individual traders, which is why it is treated as representative of the retail population rather than a narrow slice. Third, the studies count individuals, so a person who traded a little and lost a little counts the same as a heavy participant when the loss-making share is quoted; the rupee aggregate, by contrast, is dominated by the largest accounts.

Read the table as two distinct measurements rather than one. The rupee column has risen sharply, up about 41 percent into FY25, while the share of loss-making traders has stayed broadly flat above nine in ten. That combination means the average loss per losing participant deepened even as the proportion losing barely moved, which is what you would expect when turnover rises and the friction bill grows with it.

Why the aggregate is structurally negative-sum for retail

Before any judgement about direction is right or wrong, a high-frequency F&O trade must clear a stack of costs. On the Indian equity-derivatives segment that stack includes securities transaction tax, exchange and clearing charges, goods and services tax on the brokerage and exchange fees, stamp duty on the buy side, a small regulator turnover fee, and brokerage itself, plus the bid-ask spread that is paid silently on entry and exit. None of these depends on being right. All of them scale with how much you trade.

That is the mechanism behind the word net in SEBI's figures. A participant who churns a small account many times a day can pay a friction bill that is a large fraction of the capital at risk over a year, so the break-even bar sits well above zero before a single view is expressed. Layer on that the gains inside the pool are concentrated in a minority, and that the counterparties absorbing much of the flow are proprietary and institutional desks with lower costs and better tooling, and the arithmetic for the median retail participant is adverse by construction. The instrument is not the problem; the cost-weighted turnover is.

The rupee amounts above are illustrative placeholders to show the shape, not published rates, and the real numbers vary with notional, instrument and provider. The load-bearing point survives whatever the exact figures are: a fixed toll is paid on every round trip, so ten round trips a day is that toll ten times over, and the edge required merely to break even climbs with frequency. This is why cost accounting, not signal hunting, is the first discipline a serious participant installs.

Position sizing is the survival lever, not prediction

Given adverse base rates, the question that decides survival is not how often you are right but how much you risk when you are wrong. The relevant idea is risk of ruin: the probability that a sequence of losing trades draws the account down past the point of recovery. It depends far more on the fraction of equity risked per trade than on small differences in hit rate, and it rises steeply, not gently, as that fraction grows.

The following model is illustrative. It assumes a fixed fractional risk per trade and an assumed even edge, and it is used only to show the shape of the relationship. It is not a claim about any strategy, any student, or any real account, and it says nothing about returns.

The practical reading is blunt. If a run of losses can take the account below the level from which it can mathematically recover, then a good method executed at a reckless size still ends at zero. Sizing should therefore be derived from a written rule that fixes the rupees at risk before the trade exists, so that no single position, however convincing, can be the one that ends the account. That upstream discipline, deciding the exit and the size before the entry, is exactly what the method we teach is built around.

Regime and volatility awareness

Base rates are not constant through time. Volatility clusters: quiet stretches give way to stressed ones in which ranges widen, gaps become common, and stops that looked conservative are jumped. A participant who sizes for a calm regime and keeps that size into a stressed one is, in effect, quietly increasing risk per trade at the worst possible moment, because the same number of contracts now spans a much larger potential move.

The disciplined response is to treat the prevailing regime as an input to sizing rather than a detail to ignore. When conditions are stressed, the same rule that fixes rupees at risk implies fewer contracts, not more, and often implies standing aside. This is unglamorous and rarely executed, which is part of why the aggregate looks the way it does. Recognising the regime is a mechanism, not a mood: it is read from how price is actually behaving, and it feeds directly into the size the sizing rule permits.

Process discipline and the trade journal

The final discipline is measurement of one's own behaviour. A documented trade journal that records the plan, the executed size, whether the stop was honoured, and whether the process was followed, then reviewed on a schedule, turns trading from a stream of impressions into a data set that can be audited. The value is not motivational. It is that process failures, an oversized position, a moved stop, an abandoned exit, become visible and countable, so they can be reduced deliberately rather than rediscovered after each drawdown.

Graded honestly, a winning trade taken by breaking the plan is worse than a losing trade taken correctly, because the win teaches the wrong lesson. Framing review around process rather than profit is what keeps the earlier disciplines, cost accounting, sizing, regime awareness, from eroding the moment a few lucky outcomes reward breaking them. The journal is the instrument that keeps the system honest over time.

Why the free-content market leaves the gap

Most freely available derivatives education, on broker-published learning portals and video channels, is competent at vocabulary and mechanics: what a call is, how margin works, how an order is placed. That is necessary and genuinely useful. What it rarely does is integrate cost accounting, position-sizing mathematics, regime-aware sizing and process review into a single sequenced path, because those disciplines are unglamorous, cut across topics, and do not make for a satisfying standalone clip.

The result is a population that is fluent in the instruments and untrained in the survival mechanics, which is close to the exact profile SEBI's figures describe. The gap is not a lack of information; it is a lack of ordered, cumulative practice in the parts that decide whether a trader is still solvent after a bad run. That gap, and the sequence that closes it, is what a structured curriculum exists to address.

Frequently asked questions

Sources

Where the facts come from

• SEBI press release, September 2024. Updated study reporting that 93 percent of individual traders incurred net losses in equity F&O between FY22 and FY24, with aggregate losses exceeding ₹1.8 lakh crore over the three years. Establishes the multi-year baseline. sebi.gov.in
• SEBI research listing. The regulator's research page, where its studies on individual participation in the equity derivatives segment are published. sebi.gov.in research
• FY25 study coverage. Reporting that net losses of individual traders in F&O widened to ₹1,05,603 crore in FY25, up about 41 percent from ₹74,812 crore, with over 91 percent net loss-making, across a base of about 96 lakh traders at the top thirteen brokers. Establishes the current single-year picture. business-standard.com

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• What percentage of Indian traders lose money
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• Trading psychology at scale: why position size changes everything
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