What happens to individual traders
SEBI has measured it four years running. Around nine in ten individual traders lose money in equity derivatives, the aggregate loss reached ₹1,05,603 crore in FY25, and the average loss per person was ₹1,10,069.
Chapter 10 · Advanced
Nine chapters of mechanics. This one is the evidence, and it is the chapter this subject exists for.
What SEBI measured
A study of profits and losses made by individual traders in the equity derivatives segment for FY 2024-25, covering the top 13 stock brokers, with "a combined client base of around 96 lakh unique traders in EDS as against around 107 lakh unique traders across market".
So roughly nine-tenths of everyone trading derivatives in India. Not a sample of volunteers, not a survey — actual profit and loss, after transaction costs, from broker records.
The figures
SEBI's Table 11, read on 1 October 2026:
| Year | Net profit (₹ crore) | Traders (lakh) | Loss makers | Average per person |
|---|---|---|---|---|
| FY22 | −40,824 | 42.7 | 90.2% | −₹95,517 |
| FY23 | −65,747 | 58.4 | 91.7% | −₹1,12,677 |
| FY24 | −74,812 | 86.3 | 91.1% | −₹86,728 |
| FY25 | −1,05,603 | 96.0 | 91.0% | −₹1,10,069 |
SEBI's own summary: "nearly 91% of individual traders incurred net loss in EDS in FY 2025", and "the net losses of individual traders widened by 41% to ₹1,05,603 crore in FY25 from ₹74,812 crore in FY24 (after accounting for transaction costs)."
Read the table slowly
Four observations, each worth more than any opinion.
The loss rate is stable at about nine in ten. 90.2%, 91.7%, 91.1%, 91.0%. Four different years — different market conditions, different levels, different news — and the proportion barely moves. This is not a bad year. It is the steady state.
The aggregate loss grew every year, from ₹40,824 crore to ₹1,05,603 crore. More than double in three years.
The number of traders more than doubled, from 42.7 lakh to 96 lakh. More people arrived, and the proportion losing did not improve.
The average loss per person is around ₹1 lakh a year. For FY25, ₹1,10,069 each, across ninety-six lakh people.
That last number deserves a pause. It is not a rounding error on a portfolio. For a very large number of those people it is a meaningful fraction of annual income.
Why it is this way
Nothing in the previous nine chapters is surprised by this table.
The segment is close to zero sum before costs (chapter 1). One side's gain is the other's loss. There is no earnings growth underneath it to lift everyone.
It is negative sum after costs (chapter 11). Brokerage, exchange fees, stamp duty and securities transaction tax leave the system on every trade. The aggregate must be negative by at least the costs, and SEBI's figures are stated after transaction costs.
The other side is usually a professional. The counterparty to an individual's option trade is frequently an algorithmic desk with better information, better execution and lower costs.
Leverage accelerates whatever the expectancy is (chapter 5). A slightly negative expectancy, geared ten times and repeated weekly, arrives quickly.
Bought options decay (chapter 7) and sold options have a tail (chapter 9). Both sides have a structural problem, which is why the loss rate does not depend on which side people pick.
The table is what those five facts look like across ninety-six lakh people.
What SEBI did about it
Chapter 4 listed the measures: larger contracts, fewer expiries, upfront premium collection, more tail risk coverage on expiry day, intraday position monitoring.
The reported effect, over December 2024 to May 2025: the number of unique individual investors trading in the segment was down 20% year on year, and individuals' turnover in premium terms down 11%. Quarterly, unique individual traders fell from about 61.4 lakh in FY25:Q1 to about 42.7 lakh in FY25:Q4.
Fewer people. SEBI also notes losses remained higher than at the start of the year, so the measures changed participation more than outcomes.
What this does and does not prove
It does not prove nobody can make money. About 9% did. Some of those are skilled; some had a good year.
It does prove the base rate. Before you form a view about your own prospects, this is the population you are joining, and the honest starting assumption is the average outcome rather than the exceptional one.
It does prove the losses are not a few extreme cases. Nine in ten is not a tail. It is the distribution.
The useful question is not "can anyone win?" It is: what specifically do I have that the 91% did not? If the answer is enthusiasm, time, or a system that has worked for three months, that is the same answer most of the 91% would have given.
The honest conclusion
For almost everyone reading this, the correct use of derivatives is to understand them and not to trade them.
That is not a moral position. It is what four consecutive years of audited, after-cost, whole-population data says, published by the regulator, with no interest in discouraging a market it also regulates.
The point
SEBI's study of about 96 lakh traders found 91% lost money in FY25, with an aggregate loss of ₹1,05,603 crore and an average of ₹1,10,069 each — and the loss rate has sat near nine in ten for four consecutive years. It is the base rate, not a bad year, and it follows directly from the mechanics in the preceding chapters.
Check yourself
4 questions. Every answer is explained afterwards, including the ones you get right — guessing correctly is not the same as knowing. Score 70% or more and the chapter is marked done.
Question 1 of 4
0 of 4 answered. You can submit with questions unanswered — they simply score zero.
Now do it with your own numbers
Take the FY25 figures below and work out the total profit made by the winning 9% of traders, given the aggregate net loss and the number of traders. Then ask who that money came from.
The aggregate is net. The winners' gains and the losers' losses are both inside it, and the costs have already been taken out of both.