Is trading profitable when you do it part-time

Can a part-time trader be profitable at all?

Yes, some are. This report argues that the arithmetic is set against a person who trades on the side, before any skill enters the picture.

Three things sit on the trader's side of the ledger before the market moves. Every sale is taxed at 30 percent on the gain, while a loss is worth nothing to the tax bill. Every round trip pays fees, spread and slippage, none of which is deducted from that gain. And the job needs attention across hours that a person with a career does not have spare.

The sections below take each in turn, with the sums shown, then ask who is on the other side of the trade and what the alternative job looks like. The argument here is about arithmetic and attention, and it passes no judgment on anyone who trades.

What does one round trip cost in crypto in India?

A round trip is one buy and the sale that closes it. In India it costs the 30 percent tax on any gain, cash withheld on the sale, and the market's own friction on both legs. The next four parts price each in turn, then add them up on a ₹10 lakh book traded once a week for a year.

The tax, and what it refuses to count

Section 115BBH of the Income-tax Act, 1961 taxes income from the transfer of a virtual digital asset at a flat 30 percent. Two restrictions come with the rate. The only deduction is the cost of acquisition, which is what you paid for the asset. And no loss can be set off against any other income or carried forward to a later year.

The Income-tax Act, 2025 took effect on 1 April 2026 and carries the regime forward. TaxGuru's review of the new Act places the successor to section 115BBH under section 194 of the new Act. It keeps the same flat 30 percent, the same cost-of-acquisition-only deduction and the same bar on set-off. Patron Accounting's section map says the same: no rate change, no change to the loss rule. The Income Tax Department's own pages could not be opened when this report was written, so these two secondary sources are the ones read.

Profit is worked out transfer by transfer: sale consideration minus cost of acquisition, for each sale. Take two sales. One makes ₹20,000 and one loses ₹20,000. The tax falls on the ₹20,000 gain, which is ₹6,000. The loss offsets nothing. The trader is level before tax and ₹6,000 down after it.

Fees, brokerage and platform charges are not deductible under this regime. They come out of the trader's pocket and leave the taxable figure exactly where it was.

The 1 percent withheld on each sale

Section 194S of the 1961 Act required 1 percent tax deducted at source, TDS, on the consideration paid for the transfer of a virtual digital asset. TDS means the payer holds back a slice of the money before you receive it. The tdsman explainer puts the deduction at the time of credit or payment, whichever comes first. Its worked case: a ₹1,00,000 sale has ₹1,000 deducted before the seller is credited. It also lists a per-year threshold of ₹50,000 for some payers and ₹10,000 for others.

TDS is not counted as a cost in the arithmetic below. Its effect is on cash. On a ₹10 lakh sale, ₹10,000 is held back and the trader redeploys ₹9,90,000. A weekly trader feels that on all 52 sales.

The friction on each leg

Friction is everything a trade pays to happen that is not tax. Three parts make it up. The platform's fee is stated on its page. The spread is the gap between the price a buyer will pay and the price a seller will take. Slippage is the gap between the price you decided on and the price you were filled at, covered in its own section below.

The sums need a number, and this report will not use any platform's actual fee. Assume friction of 0.3 percent on each leg, fee and spread together. It is an assumption for the arithmetic. Change it and the answer moves, but the shape of the answer does not.

A round trip pays it twice: 0.3 percent on the buy and 0.3 percent on the sale, which is 0.6 percent. On ₹10 lakh, that is ₹6,000 per round trip.

The year, in rupees

Start with a ₹10 lakh book. The trader closes the whole position every week, 52 times in the year. To keep the sums readable, treat every sale as ₹10 lakh.

Now give the trader no edge at all, which means nothing for or against. Half of the trades gain ₹20,000 and half lose ₹20,000, which is 2 percent of the book either way. That is 26 winners and 26 losers.

The gross result is 26 × ₹20,000 minus 26 × ₹20,000, which is ₹0.

Friction is 52 round trips × ₹6,000, which is ₹3,12,000.

Tax is 30 percent of the gains. The 26 winners add up to ₹5,20,000, and 30 percent of that is ₹1,56,000. The 26 losers, at ₹5,20,000 in total, earn no relief.

The year ends at ₹0 − ₹3,12,000 − ₹1,56,000, which is a loss of ₹4,68,000, or 46.8 percent of the book. The trader was right exactly as often as wrong and paid out nearly half the capital.

Read the ₹3,12,000 line again. A book that turns over weekly at these costs must find ₹3,12,000 of gross profit, 31.2 percent of its size, before it has made a rupee. That figure is the hurdle the structure sets, and it forecasts nothing.

Source line: Income-tax Act sections as described by TaxGuru and Patron Accounting (both read 2026-09-30), TDS terms as explained by tdsman (read 2026-09-30). The friction rate, the book size and the win and loss sizes are assumptions of this report.

What is slippage, and why does it grow when it matters most?

Slippage is the difference between the price you meant to trade at and the price you actually got. It arises for two reasons. An order takes time to reach the market. And a large order uses up the buyers or sellers standing at the best price, then walks down to the next.

Work it once. A trader decides to sell 10 units of a coin quoted at ₹1,00,000 each, a ₹10 lakh position. The buyers at that price want only part of it. The rest fills lower, and the average fill is ₹99,500 a unit. The slippage is ₹500 a unit, which is 0.5 percent. On 10 units that is ₹5,000, paid on one sale, and it appears on no fee schedule.

It is larger in a thin market, where few orders stand near the price. It is larger in a fast market, where the price has moved again before the order arrives. The two tend to arrive together, and they are also the moments a trader most wants to act. The companion piece on liquidity and what it looks like on a bad day covers the mechanism from the other side.

Slippage is the reason the 0.3 percent friction above is a plain-day number. On a bad day it can be a multiple of that, and the trader cannot choose the day.

What hours does the job need?

A market that never closes has no end to its working day. Covering it takes shifts: 24 hours × 7 days is 168 hours a week. A desk that does this for a living staffs it with people whose only job is the market.

Give a person with a career the most generous reading. They work 50 hours a week and sleep 8 hours a night, which is 56. That leaves 168 − 50 − 56 = 62 hours. Commuting, meals, family and everything else come out of those 62. Whatever is left is what the market gets, and the market is never closed.

Written as a job spec, trading asks for the following. A working day matched to the market's hours. Attention unbroken through the moments that matter, which the market picks. A written rulebook for entry, exit and size, and the discipline to follow it when a position is losing. Capital that can absorb a run of losing weeks without changing the trader's life. A person with another job can meet some of these and cannot meet the first two. The companion piece on the two job descriptions of investing and trading sets the full spec out side by side. The one on intraday trading alongside a job takes the hours problem on its own.

A missed hour is not neutral. An alert that arrives during a meeting, a position left open over a long flight and an exit that waits for the evening are each a decision made late. Late decisions fill at worse prices, which feeds straight back into slippage.

How many decisions a week, and what win rate pays for them?

Each trade is at least two decisions, when to get in and when to get out. A trader making five trades a week makes about 260 a year, and every decision carries a chance of being wrong. The question is how often the trader must be right for the costs to be covered.

Use the same numbers as before. Winners gain 2 percent of the book and losers lose 2 percent. Friction is 0.6 percent per round trip. Tax takes 30 percent of a winner's gain and gives nothing back on a loser.

A winning trade nets 2 percent − 0.6 percent friction − 0.6 percent tax, which is 0.8 percent of the book. A losing trade nets −2 percent − 0.6 percent friction, which is −2.6 percent.

Break-even needs the share of winners, call it p, to satisfy 0.8p = 2.6 × (1 − p). That gives 3.4p = 2.6, and p = 0.765. About 76.5 percent of trades must win just to finish level.

Check it on the 52-trade year. Forty winners and 12 losers is a 76.9 percent win rate. Gross is 40 × ₹20,000 − 12 × ₹20,000, which is ₹5,60,000. Friction is ₹3,12,000. Tax is 30 percent of the ₹8,00,000 in winners, which is ₹2,40,000. The year nets ₹5,60,000 − ₹3,12,000 − ₹2,40,000 = ₹8,000. At 40 wins from 52 attempts, the trader barely breaks even.

Nothing here says how often anyone actually wins. The figure is the hurdle, and it depends on the assumptions: smaller friction lowers it, losers larger than winners raise it. The structure asks for a very high hit rate before it pays anything, and that rate has to hold across hundreds of decisions made in spare hours.

Who is on the other side of the trade?

Every fill has a counterparty, and in active markets many of them are doing this as a full-time business. The clearest public evidence on who wins and loses comes from equity derivatives in India, not crypto, and it is worth stating precisely for that reason.

SEBI's Department of Economic and Policy Analysis published a study of individual traders in the equity derivatives segment in August 2026, covering FY25 and FY26. Its headline figures, read from the report itself:

• 87.7 percent of individual traders made a net loss in FY26, against 90.9 percent in FY25 and 91.1 percent in FY24.
• Aggregate net losses of individual traders were ₹91,685 crore in FY26, down from ₹1,11,788 crore in FY25. Over FY22 to FY26 the total came to about ₹3.85 lakh crore.
• The average loss per individual trader was about ₹1.17 lakh in FY26.
• Before transaction costs, 82.1 percent of traders made a loss. After costs it was 87.7 percent. SEBI's own reading is that costs pushed some traders with small gross profits into net losses.
• Individual traders paid about ₹25,000 crore in transaction costs in each of FY25 and FY26.
• In FY26, proprietary traders recorded the highest gross trading profit of any category, about ₹44,000 crore. The report adds that algo entities made 99 percent of the profits of foreign portfolio investors and proprietary traders. An algo entity is one that placed at least one algorithmic order in the year.

SEBI also collects international studies. One it cites followed people who began day trading equity-index futures in Brazil. Among those who kept going for more than 300 days, 97 percent made a net loss, and the study found that staying longer did not improve results.

Two cautions belong beside these numbers. They describe equity futures and options, a leveraged product with expiry dates, and they should not be carried over to crypto as if they were a crypto statistic. And they describe what happened, not what any one trader will do. What they do show is who sits on each side. Individuals are on one side, with costs that push more of them into loss. Firms with better tooling are on the other.

Source line: SEBI, Profitability of Individual Traders in the Equity Derivatives Segment (FY25 to FY26), August 2026, page and full text read 2026-09-30.

What does the investor's job look like instead?

It is short. An investor decides an allocation once, writes down the weights and the date they will be checked, and lets a schedule carry the rest.

Qatobit is a crypto index investing platform. An investor holds a curated basket of digital assets, designed and rebalanced monthly by Qatobit on a published methodology, rather than picking coins and timing entries. Each index is a permanent allocation product, not a trading instrument. The investor makes one decision, the thesis that fits their risk appetite and horizon, and everything downstream of that decision runs on the methodology.

The tax treatment follows the same shape. The sale of a basket is the investor's taxable event, and a monthly rebalance inside an index is not. Inside a basket, a loss on one token offsets a gain on another, because the taxable event is the sale of the basket rather than the sale of each coin. Someone holding the same coins directly gets nothing of the sort: every winner is taxed and every loser is stranded. The 30 percent under section 115BBH and the 1 percent TDS on a transfer still apply when the basket is sold. So does the statute's bar on carrying a loss forward.

Compare the two specs. The trader needs a market's hours, a hit rate near 76.5 percent on the example's terms, and a rulebook enforced under stress. The investor needs a thesis, a horizon and a rebalance date. The second list is the one a person with a career can actually keep. To invest in QSI Growth, or in any of the four QSI indices, is to take the second job description.

Where this leaves a part-time trader

The arithmetic above has three working parts. A 30 percent tax that counts gains and ignores losses. A cost on every leg that the tax does not recognise. A win rate the structure demands before it pays anything. Each can be altered by better assumptions, and none can be removed by effort alone.

A reader can test their own version in ten minutes. Take your weekly trade size and multiply it by your real friction on both legs. Multiply that by the round trips in a year and compare the result with the gains you realised. Then tax the winners at 30 percent and give the losers no credit. The figure that remains is yours.

The tax mechanics behind each line have their own guides. Start with how crypto gains are taxed in India. Then read how TDS on crypto works under section 194S and what the 30 percent covers and what it does not. For what a position size has to survive, read what a drawdown is and how a position is sized to survive one.

Frequently asked questions

Is trading profitable?

Some traders are profitable, but the structure favours the other side. In SEBI's study of equity derivatives, 87.7 percent of individual traders made a net loss in FY26. In crypto in India, the 30 percent tax on gains has no loss set-off, and every leg carries a cost. Together they lift the win rate a trader needs to about 76.5 percent in this report's worked example.

Is part-time trading profitable?

Part-time trading faces the same arithmetic as full-time trading, with fewer hours to meet it. On the assumptions used here, a weekly trader on a ₹10 lakh book who wins exactly as often as they lose ends the year ₹4,68,000 down. A market that never closes takes 168 hours a week to cover, and a person with a career has about 62 of them free.

What is slippage in trading?

Slippage is the gap between the price you decided on and the price you were filled at. It grows in thin and fast markets. Selling 10 units quoted at ₹1,00,000 and filling at an average of ₹99,500 costs ₹5,000, or 0.5 percent, on that one sale.

How is crypto trading taxed in India?

Income from the transfer of a virtual digital asset is taxed at a flat 30 percent under section 115BBH of the Income-tax Act, 1961. Only the cost of acquisition is deductible. A further 1 percent TDS under section 194S applies on the transfer. The Income-tax Act, 2025, in force from 1 April 2026, carries the regime forward under successor sections.

Can crypto trading losses be set off?

No. Under section 115BBH no loss can be set off against any other income or carried forward to a later year. A ₹20,000 gain and a ₹20,000 loss on two separate sales leave a tax bill of ₹6,000, which is 30 percent of the gain alone.

What is the difference between trading and investing?

Trading is a job defined by the market's hours, a high hit rate and a rulebook kept under stress. Investing is a job defined by an allocation, a horizon and a rebalance date. A QSI index is a permanent allocation product, not a trading instrument, rebalanced monthly on a published methodology.

Crypto investments are subject to market risk. Not financial advice.