Why Do 9 Out of 10 Traders in India Lose Money?

Between FY22 and FY24, 1.13 crore individual traders collectively lost ₹1.81 lakh crore in India's equity F&O segment. ₹1.81 lakh crore was recorded as combined net losses by individual traders over the three years. It was real money lost by market participants, not just a statistic on paper.

SEBI published these findings in a study based on broker-level data from the top 15 brokers covering 90% of individual F&O traders in the country.

One of the key findings was that 91.1% of individual traders incurred losses in FY24. Roughly nine out of ten.

Every year, this statistic gets cited, usually as a warning, a disclaimer, or a footer. "Derivatives are subject to market risk." But the number itself rarely gets explained. Why 91%? What are the remaining profitable traders doing differently? And what exactly is happening to the money of the 91%?

That is what this blog is actually about.

What Traders Commonly Do

The first thing worth understanding is who is actually trading because the picture painted by the data is not what many people imagine when they think of a derivatives trader.

• Over 75% of individual F&O traders in FY24 reported annual incomes of less than ₹5 lakh.

• Nearly half of all traders in FY24 were under the age of 30.

• 72% of traders came from cities beyond the top 30 urban centers.

This means that the bulk of India's F&O participant base is young, not high-income, and spread across smaller towns and cities that got smartphone access and trading apps at roughly the same time.

This is not said to be condescending. It is said because these numbers matter for understanding the problem. A 24-year-old from Lucknow earning ₹4 lakh a year who loses ₹46,000 in a single year of F&O trading, which is the average loss for new traders in FY24 per the SEBI data, has lost more than a month's salary. That is a materially different experience from a high-income trader in Mumbai losing the same amount. The financial impact can be very different across income groups. And yet the participation keeps growing. The number of individual F&O traders nearly doubled from 51 lakh in FY22 to 96 lakh in FY24.

The Reasons

So let's get into the structural reasons as to why most traders lose money.

Reason 1: The product can be structurally challenging for retail traders

99.3% of all F&O traders traded options at least once during the study period. Options, particularly options buying, account for a large share of retail participation in India today. And buying options is one of the most structurally difficult ways to make money in markets.

Here is why:

When you buy an option, you are paying a premium. That premium has something called time value baked into it, which decays every single day the option exists, regardless of what the underlying stock or index does. This phenomenon is called theta decay. If you buy a weekly Nifty option on Monday and the index does absolutely nothing for four days, your option is worth significantly less by Friday. You were not wrong about direction. The market did not move against you. Time simply passed, and the option bled value because of it.

Most retail option buyers do not fully internalise this when they start trading. They think of an option like a lottery ticket, where you either win or you don't, not like a perishable asset that is losing value with every hour that passes. The consequence is that the bar to make money buying options is higher than it looks. The stock does not just have to move in your favour. It has to move in your favour fast enough and far enough to overcome the time decay eating into your premium every day.

This is also why options sellers, who may include institutional or systematic participants, can sometimes have a structural edge. They are collecting the premium you paid. Time working against you means time is working for them.

Reason 2: The other side of the trade is not human

In FY24, proprietary traders booked gross profits of ₹33,000 crore in the F&O segment. FPIs earned ₹28,000 crore. Against this, individual traders collectively lost over ₹61,000 crore before transaction costs even enter the picture.

The study reported high algorithmic participation among FPIs and proprietary traders. These are systems with no emotion, no fatigue, and no need to recover yesterday's losses. They do not engage in revenge trade. They do not hold a losing position because admitting it feels bad.

By comparison, only 13% of individual traders used algorithmic trading, and even that figure may overstate direct individual usage, because it includes cases where a broker's system squared off a position post 3:20 PM for margin reasons, which SEBI counted as an algo trade by the client.

Speed compounds this further. By the time a retail trader has pulled up a chart, read it, and keyed in an order, faster systems on the other side may already have reacted to the same information. Platforms like Sahi offer faster charting tools and multi-window layouts that may help traders monitor markets and place orders more smoothly.

This is not an unfair market. But it is an asymmetric one, and reducing every controllable disadvantage you are handing away is the only sensible place to start.

Reason 3: Transaction costs can be quietly damaging

This cost is often underestimated until it builds up over time.

In FY24, the average individual trader spent ₹26,000 in transaction costs alone. Brokerage, STT, exchange fees, GST, and stamp duty. Over the three-year period, individual traders collectively paid more than ₹50,000 crore in transaction costs.

Transaction Cost Breakdown (FY24)

Transaction Cost Component	Amount (FY24)	Share of Total
Brokerage	₹11,364 crore	51%
Exchange Fees	₹4,469 crore	20%
STT	₹3,454 crore	15%
GST	₹2,868 crore	13%
Stamp Duty	₹199 crore	1%
Total	₹22,451 crore	100%

Here is what this means practically. A trader can have a genuinely positive win rate, meaning they make money on more trades than they lose on, and still end the year in the red if their transaction costs are high enough.

Every trade has a cost attached to it. The more frequently you trade, the more you pay. SEBI's data shows that the proportion of loss-makers was actually highest among the most active traders; 95% of "high-value" traders who did over ₹1 crore in options premium turnover made net losses, compared to 91.5% of small-size traders.

More trading is not better trading. In most cases, it is measurably worse.

Reason 4: Losses make people trade more

This is one of the most revealing behavioural trends in the SEBI data.

76.3% of traders who made losses in both FY22 and FY23 continued trading in FY24 anyway. Out of 24.4 lakh traders who lost money in two consecutive years, 18.6 lakh of them came back for a third year. And of those persistent traders, only 8.3% managed to turn profitable in the third year.

This may reflect a common behavioural tendency seen after trading losses. When you lose money, the instinct is to get it back, specifically from the place where you lost it. This creates a feedback loop where losses lead to more trading, which leads to more transaction costs, which leads to more losses, which leads to more trading. The data captures this perfectly. New traders in FY24 lost an average of ₹46,000. Regular traders, the ones who had been doing this for all three years, lost an average of ₹1,50,000. Experience made things worse because it was happening without a structural change in approach. Some platforms also offer features such as a Kill Switch, which can pause trading activity for the day and may help reduce impulsive overtrading.

The table below from the SEBI report shows this clearly:

Trader Type	No. of Traders	Avg Loss Per Person	% Loss-Makers
New Traders (first time in FY24)	41.9 lakh	₹46,139	92.1%
Regular Traders (all 3 years)	22.4 lakh	₹1,50,477	88.7%
Others	21.9 lakh	₹99,078	91.4%

The regular trader losing ₹1.5 lakh per year is not more reckless than the new trader. They are simply more exposed. More time in the market, more transaction costs, more cycles of loss and attempted recovery, without the one thing that could actually change the outcome: a disciplined risk framework.

Reason 5: Some higher-risk demographics may have fewer financial buffers

The SEBI data has one finding that deserves more attention than it typically gets. The proportion of young traders under 30 jumped from 31% of all F&O traders in FY22 to 43% in FY24. Nearly 93% of these young traders lost money. And 76% of individual F&O traders reported annual income of less than ₹5 lakh.

A common profile reflected in the data includes traders who are: young, lower income, from a smaller city, trading options on a phone, without a written plan, without defined stop losses, and without a clear understanding of theta decay or the algorithmic systems on the other side.

The income data adds another painful layer to this.

Income-wise Distribution

Income Bracket	No. of Traders	% Loss-Makers	Avg Loss Per Person
Below ₹5 lakh	65.4 lakh	92.2%	₹65,500
₹5L to ₹25L	19.2 lakh	88.3%	₹1,52,500
₹25L to ₹1 crore	1.1 lakh	75.0%	₹2,58,000
Above ₹1 crore	0.3 lakh	85.2%	Profit of ₹95,900

The only income category that made net profits in aggregate was the very high income bracket, traders declaring over ₹1 crore annually. Every other income group lost money, and the highest percentage of loss-makers, 92.2%, was in the lowest income bracket. The people who could least afford to lose were losing at the highest rate.

So what might the profitable minority be doing differently?

In FY24, 12.7 lakh individual traders made profits. Their average profit was ₹1.03 lakh per person. They were trading in the same market, during the same volatile years, against the same algorithmic counterparties, with access to the same information as the 91% who lost.

SEBI's data does not tell us exactly what they did differently. However, the numbers suggest that disciplined risk management, lower costs, stronger execution habits, and more consistent processes may have played a role. On a platform like Sahi, users may get chart-based execution and multi-window tools. Pricing is currently listed at ₹10 per executed order after the free period, which is lower than brokers' charging ₹20 per order.

(Snap of trading from charts on Sahi.com)

They were also more likely to belong to higher income and older age brackets, which may indicate greater capital buffers and more market experience. And they were more likely to have survived multiple market cycles, not because they never had bad trades, but because their bad trades were small enough that they could absorb them.

The question that separates the 9% from the 91% is not which trades they pick. It is how much they lose when they are wrong. And that is one area a trader can often control, regardless of who is on the other side of the trade. Defining a maximum loss before entry, sizing positions around stop-loss levels rather than conviction, and using tools such as Sahi's Stop Loss, Auto SL, and Trailing SL to help automate discipline can make a meaningful difference over time.

The ₹1.81 lakh crore in combined losses may not have been driven by stock selection alone. Position sizing, timing, transaction costs, and execution discipline may also have played a role. Many traders enter positions without clearly defining how much they are willing to lose on a trade. If that is not decided before entry, the market often decides it later, sometimes at a higher cost than expected.

Disclaimer: The information in this blog is for educational purposes only and does not constitute investment advice. Please consult a SEBI-registered investment advisor before making investment decisions.