TL;DR

SEBI's own study found that roughly 9 in 10 individual F&O traders lost money in FY22 — not because of a rigged market, but because of five compounding mechanisms: leverage that raises the psychological stakes past what most accounts can absorb, a small set of repeatable behavioral patterns, an illusion of skill in a largely noise-driven short-term market, a cost structure stacked against frequent short-dated options trading, and the simple fact that almost no one reviews their own trade history systematically. None of that is fixed by a better prediction. It's fixed by a better process.

The number SEBI didn't spin

In January 2023, SEBI published a study most brokers would rather you didn't read closely. It looked at individual traders in the equity F&O segment over FY22 and found that roughly 89-90% of them lost money — not underperformed a benchmark, not made a little less than they hoped, but closed the year in the red. The average loss among those traders was substantial enough to matter, not a rounding error that a single good month washes out.

That figure gets quoted constantly and explained rarely. It usually shows up as proof that F&O trading is "risky" and the sentence just stops there, as if the conclusion were self-evident. It isn't. Plenty of genuinely risky activities have better odds than this. When nine out of ten participants in the same game lose money, across a population that includes engineers, doctors, business owners, and people who are demonstrably capable of managing risk in other parts of their lives, the game itself has a shape. That shape is legible in trade-level data, even when it's invisible to any one trader staring at their own account statement.

Five forces stacked against the tradeNot proprietary data — the mechanism behind SEBI's number1LeverageBigger stakes, bigger stress, faster bad decisions2BehaviorRevenge trades, held losers, expiry overtrading3Illusion of skillShort-term noise mistaken for a real edge4Costs and thetaStacked against frequent, short-dated options5No reviewLosses never get systematically diagnosed

Leverage doesn't just multiply your position — it multiplies your nerve

Start with the mechanism that makes everything downstream worse: leverage. F&O lets a trader control a notional position many times larger than the capital actually at risk, and that's the entire commercial appeal of the segment. It's also what turns a market move that would be background noise in a cash-equity account into something that can erase a week of gains in one trade.

The financial version of this math is well understood; most traders can recite that leverage cuts both ways. What's underweighted is the psychological version of the same math. When a ₹50,000 account is effectively steering a ₹5 lakh position, an ordinary 1% move in the underlying isn't a 1% event for the trader — it's a five-figure swing in real money, felt in real time, on a screen that updates every second. That kind of stake compresses decision-making. A plan written calmly the night before doesn't survive contact with a position moving hard against you on size you can't comfortably absorb. This is the on-ramp to nearly everything else on this list: leverage doesn't just create the potential for a bigger loss, it creates the pressure that makes traders abandon whatever plan they had in the first place.

The behaviors that turn one bad trade into a bad month

Under that kind of pressure, a small number of specific, repeatable behaviors show up in trade-level data again and again — and they're worth naming precisely, because "trading psychology" as a phrase tends to flatten them into one vague idea.

Revenge trading is the clearest one: a losing trade followed within minutes by a larger position in the same direction on the same instrument, aimed at winning back what was just lost rather than following any plan the trader actually had going in. It usually fails, because the size and timing of that trade were set by the previous loss, not by any read on the market.

Holding losers too long is the quieter version of the same instinct. Traders exit winning trades fast, to lock in the gain and feel the win, but let losing trades run in the hope they turn around, because closing a loser makes the loss real in a way an open position doesn't yet. Measured across enough trades, this produces a consistent asymmetry — losers get more time and more room to grow than winners were ever given — and that asymmetry alone is enough to turn a strategy with a genuine edge into a net loser.

Expiry-day overtrading layers a third problem on top of both. Weekly options that look cheap in absolute rupee terms feel low-risk, so traders take more of them, more often, right around the point in the week when time decay is working hardest against the buyer. These three patterns each get covered in more depth elsewhere on this blog, but the throughline is the same: none of them are decisions made by a calm trader working a plan. They're decisions made by a stressed trader whose capital is already exposed past what their temperament can comfortably hold.

See these patterns in your own trades

Auraxon flags revenge trades, holding-time asymmetry, and expiry-day overtrading automatically from your logged trade history — no spreadsheet required.

Try Auraxon Free

Why it feels like skill anyway

None of this would matter as much if traders could tell, in the moment, when they actually had an edge and when they didn't. Mostly, they can't — and the reason is structural, not a character flaw.

Short-term price action in liquid index options is dominated by noise. A run of five or six winning trades on a directional read feels like confirmation of a real insight into the market; at typical retail trade frequencies, it's well within what pure chance produces over the same number of attempts. The trouble is that wins and losses don't arrive with a confidence interval attached to them. A trader on a winning streak credits it to skill and sizes up, meeting the downside of the same variance later with a bigger position. A trader on a losing streak more often blames bad luck, a manipulated move, or a report that "should" have moved the market a different way — rarely the read itself being no better than a coin flip. That asymmetry in how wins and losses get explained is exactly what keeps traders inside a strategy long after the data, if anyone looked at it, would say it has no real edge.

The cost structure is quietly working against you

Even a trader who has genuinely figured out market direction more often than not is fighting a cost structure built for a lower frequency than most retail F&O activity actually runs at.

Every round trip carries brokerage, STT — charged at a materially different rate on options that get exercised, which catches people off guard — exchange transaction charges, stamp duty, and GST layered on top of all of it. None of these looks large on a single trade. Multiplied across dozens of trades a week, particularly in short-dated weekly options, they become a fixed drag that has to be cleared before a strategy even reaches breakeven, separate entirely from whether the market call was right.

Theta decay compounds the problem specifically for option buyers. An option isn't only a bet on direction — it's a bet on direction happening fast enough to outrun time decay that isn't linear, and that accelerates sharply in the final day or two before expiry. A trader can be correctly positioned on where the market is headed and still lose money, because the option bled value to time faster than the underlying moved in their favor. This is a cost structure that rewards precision and patience and punishes frequency. Most retail F&O activity is built around exactly the opposite of what the mechanics actually reward.

Almost nobody looks back systematically

The last piece isn't a market mechanism at all — it's a gap in process. Most losing traders never review their own trade history in any structured way.

Memory is a poor record-keeper for this purpose. It holds onto the big win from three months ago and lets the slow bleed of small losses since then fade into a vague sense of "roughly breakeven." Without a queryable log of every trade's size, timing, and outcome, there's no way to tell a real edge apart from a lucky stretch, no way to notice that losses cluster on expiry days, no way to see that the average losing trade is held three times longer than the average winner. Those patterns sit right there in the data. They're only invisible to a trader relying on impression instead of a record.

What actually changes the odds

None of this means structured review turns a losing trader into a winning one — that claim doesn't survive contact with SEBI's own numbers, and anyone promising it is selling something. What structured review actually does is narrower and more useful: it replaces "I think I sometimes do this" with "I did this on these fourteen specific trades," which is the only starting point from which a trader can fix one identifiable thing instead of vaguely resolving to "trade better."

That's a mechanism, not an outcome. A trader who can see their own expectancy, their own holding-time asymmetry, their own expiry-day pattern is working with information the other 89% mostly never generate about themselves. What they do with it is still up to them. But they're deciding with their eyes open, instead of running the same undiagnosed pattern for another year and calling the result bad luck.

What percentage of F&O traders lose money in India?

SEBI's January 2023 study found that roughly 89-90% of individual traders in the equity F&O segment made losses in FY22, with the average loss substantial enough to matter.

Why do most F&O traders lose money?

No single cause — leverage raises both position size and psychological stress, a handful of behavioral patterns compound losses under that stress, traders overestimate skill in a largely noise-driven short-term market, transaction costs and theta decay work against frequent short-dated trading, and almost no one reviews their own trade history closely enough to catch any of it.

Does leverage by itself explain the SEBI numbers?

No, but it drives a lot of the rest — leverage doesn't just enlarge potential losses, it raises the stakes to a point where traders abandon whatever plan they had, which is when revenge trading, oversized positions, and expiry-day overtrading tend to show up.

Why does frequent short-dated options trading struggle even when the market view is right?

Costs (brokerage, STT, exchange charges, stamp duty, GST) and theta decay both scale with trade frequency and work against the option buyer specifically, so being directionally right isn't enough if the option loses value to time faster than the underlying moves.

What actually improves a trader's odds?

Not a signal or a guarantee — a structured review of your own trade history covering win rate, expectancy, holding-time asymmetry, and expiry-day patterns, which turns a vague impression of your trading into a specific, fixable diagnosis.