Can You Make Money Trading: Conditions and Risks

Can you make money trading? Yes, but only with a positive mathematical expectancy that has been confirmed over a long series of trades and still holds after fees, funding rates and slippage are deducted. Regulator data shows that most active retail traders lose money, and one winning trade proves nothing. Below we break down what makes up the net result and how to tell a system from luck.

This article covers only active trading on spot and futures markets, where the outcome depends on your decisions about entries, exits and risk. Staking and long-term holding are outside this topic; they are covered in a separate piece, Can You Make Money with Cryptocurrency: An Honest Breakdown.

Where a Trader's Profit Can Come From

If you ask how traders make money, the short answer is this. Not by guessing direction, but through an edge, meaning a repeatable situation in which the average result is positive over a large number of trades.

An edge usually comes from three sources.

• Reading the market. The trader sees something in the order book and in time & sales (the tape) that most participants miss, for example a large limit order the price fails to break through several times, or aggressive market buying when the order book has little liquidity. This gives a slightly more likely scenario, not certainty.
• Risk management. Even with a win rate below 50% you can stay profitable if the average winning trade is noticeably larger than the average losing trade. That ratio comes from exit rules, not intuition.
• Behavior. The ability to follow the same rules for the thousandth time while other participants trade on emotion creates a difference in results on its own.

A detail the ads leave out. In the futures market your profit is another participant's loss minus exchange fees, and the other side is often a market maker or an algorithm. According to India's regulator SEBI, in fiscal year 2024 97% of foreign portfolio investors' profits and 96% of proprietary traders' profits in the derivatives market came from algorithmic trading. A retail trader competes with professional infrastructure, so the edge has to be real rather than imagined.

Why One Profitable Trade Does Not Prove You Have a System

Imagine a thousand people each flipping a coin ten times. Roughly one of them gets ten heads in a row and looks like a master. With millions of market participants, someone will inevitably show a run of winning trades with no edge at all. That is why the question of whether trading is profitable cannot be settled by one trade or even one good month.

A system differs from luck in three ways. Entry, exit and position-size rules are written down in advance and do not change mid-trade. The result is collected over a large sample, not the best examples. The statistics cover different market conditions (uptrend, downtrend, range) rather than one convenient period. If even one of these is missing, you have a set of trades, not a system.

Expected Result and the Cost of a Mistake

Mathematical expectancy shows the average result of one trade over many repetitions. The formula is simple:

Expectancy = p × average win − (1 − p) × average loss − costs per trade, where p is the share of winning trades.

Take a hypothetical example in which the probabilities are assumed, not taken from anyone's statistics. Say 45% of trades close with a $30 profit and 55% close with a $20 loss. Entry and exit costs are set at $1.5 per trade (an assumed figure; the real one depends on the exchange, fee tier and volume). The expectancy is 0.45 × 30 − 0.55 × 20 − 1.5 = 13.5 − 11 − 1.5 = 1pertrade.Over100tradestheexpectedresultisabout+100.

Now shift the win rate to 40%. The expectancy becomes 12 − 12 − 1.5 = −$1.5. Five percentage points turned a profitable system into a losing one without changing trade sizes. Higher costs or a worse win-to-loss ratio do the same thing.

The cost of a mistake adds a second layer. In the example above the standard deviation of the total over 100 trades is about 250againstanexpectancyof+100, so a series of 100 trades can easily end in the red even with a working system, purely because of variance. And a drawdown requires a disproportionate recovery. After losing 20% of the account you need to earn 25% to get back to the starting amount; after losing 50%, you need 100%. That is why risk per trade affects the outcome more than it seems.

Fees and Other Costs

Costs rarely look large in the moment, but they accumulate with every trade. On crypto exchanges they include the taker or maker fee on entry and on exit, the spread between the best bid and best ask, slippage on market execution, the funding rate on perpetual futures (a periodic payment between long and short holders) and withdrawal fees.

The higher the trade frequency, the harder costs press on expectancy. In the hypothetical example above, $1.5 per trade took 60% of the gross expectancy. In scalping, where the target per trade is measured in tenths of a percent, the fee can exceed the average profit, and a system with a positive gross result turns out to be a net loser.

The scale of costs is visible in regulator data. According to SEBI, Indian retail derivatives traders spent an average of 26,000 rupees per person on transaction costs in fiscal year 2024, and about 500 billion rupees in total over three years, of which 51% was brokerage and 20% exchange fees. The market is different, but the mechanics are the same. Before launching a strategy it is worth calculating the net result using your exchange's actual fee schedule, and tracking the funding rate on perpetual contracts. In Secret Terminal funding rates are shown directly in the platform interface, which makes this cost easier to keep in view.

What Studies Show and What They Do Not Prove

The largest recent study of retail traders was published by India's regulator SEBI on September 23, 2024. The country is India, the market is exchange-traded equity futures and options, the period is three fiscal years from FY22 to FY24, and the sample is more than 10 million unique individual traders. The result for the period was this. 93% of participants ended it with a loss, the average loss was about 200,000 rupees per person including fees, and total losses exceeded 1.8 trillion rupees. Only 1% of traders earned more than 100,000 rupees net. At the same time, more than 75% of loss-making traders kept trading after several years of losses.

What this proves. For the mass retail participant, active derivatives trading is loss-making on average, and the loss is built from both market losses and costs. Profit is concentrated among a small share of participants and among professional players with algorithms.

What this does not prove. The study is not about cryptocurrency and not about any specific person. It does not say that earning is impossible; a profitable minority is there. It does not measure skill, preparation or discipline, so it does not answer what separates the 1% from the 93%. We are not citing a comparable regulator study of the retail crypto market here, so the figures cannot be transferred to crypto directly; only the mechanics of costs and variance carry over.

The US regulator CFTC, in its advisory on the risks of virtual currency, gives no statistics but states a principle. There is no such thing as a guaranteed investment or trading strategy, and leverage amplifies losses just as it amplifies gains, up to losing more than the initial investment. The regulator advises risking only money you can afford to lose.

Public success stories are told by the survivors. Those who lost their deposit rarely run a trading channel, so the visible picture is skewed toward profitable examples regardless of their actual share.

What Conditions Make Practice Meaningful

The conditions for meaningful practice fit in a table.

On demo accounts. A demo is useful for learning the interface and the mechanics of your rules, but it has limits. The simulation does not reproduce the order book queue, slippage or execution delays, and above all there are no real emotions on a demo, which is what most often causes rules to be broken. So after the demo a sensible step is practice with a small real amount within an acceptable loss, for example from $10, taking into account the exchange's minimum order size and the fact that at such an amount fees will make up a noticeable share of the result. The goal of this stage is to test rule execution, not to earn.

Written rules are easier to keep in one document. How to build one and stick to it while trading is covered in A Trader's Trading Plan: How to Build It and Stick to It. A journal is convenient to keep where you trade. Secret Terminal has a built-in journal with trade statistics for this, and the data is stored locally on your computer.

When Trading Is Not Suitable as a Source of Income

Trading is not suitable as a source of income in several situations.

• You need a fixed monthly income. A system's results are distributed unevenly, profitable and losing months alternate, and a planned amount by the first of the month is not guaranteed even by a working strategy.
• You trade with borrowed money or money needed for living expenses. Pressure for results breaks rule execution and turns a system into a chaotic set of trades.
• The deposit is small and expectations are big. Raising leverage does not solve the capital problem; it only speeds up the account's movement in both directions and brings liquidation closer.
• There is no time for testing. Without several hundred trades under the same rules you have no data, only impressions.
• You are not ready to accept losing streaks. Even a positive system can produce 5–10 losing trades in a row, which is statistically normal but psychologically hard.

A look at ads that guarantee income. A typical ad promises "a steady 10% a month" or "signals with 90% accuracy". You can test it with four questions. First, over what period and on what sample of trades was the result obtained; a screenshot of one week does not count as an answer. Second, what was the maximum drawdown, because there is no return without drawdown. Third, who bears the risk, because if the author sells a subscription or earns a referral commission, they make money from you regardless of your result. Fourth, how is a fixed percentage even possible when the regulator states plainly that there are no guaranteed strategies. A fixed return contradicts the very nature of a series of trades with variance, so any guarantee points either to ignorance of the math or to a bet on your ignorance.

FAQ

• Can you live only on trading income?

  Only with a positive expectancy confirmed over years and with capital that lets you live on part of the profit without touching the base. Trading income is uneven, so you need a reserve covering several months of expenses and readiness for periods without profit.

• Why can't anyone promise a fixed percentage?

  Because a trading result behaves like a random variable with variance, not like a deposit rate. Even with a positive expectancy a given month can be a loss, and no honest system rules that out. A promise of a fixed percentage means the author either did not calculate variance or is deliberately hiding it. The CFTC says plainly that a claim of no risk of loss is a reason not to invest.

• How long does it take to test a system?

  A rough guide is this. Several hundred trades under the same rules and at least a few months to capture different market phases. In day trading, hundreds of trades accumulate faster; in swing trading it can take a year or more. It is better to split testing into stages: a test on historical data, a demo to practice the mechanics, then a small real amount. While the sample is small, the spread of the expectancy estimate is so wide that a positive sign may be random.

• How does luck differ from an edge?

  Luck does not repeat by rules; an edge does. A lucky trade arises without a predefined condition and does not reproduce over the next hundred trades. An edge is described by a condition (for example, the price reaction to a large limit order in the order book), recorded in the plan, and gives a positive expectancy over a large sample after costs. If you cannot explain before opening a trade why it should work, it was luck.

If you want to test your trading without illusions, start with a written trading plan and a regular review of your trades, for example in the Secret Terminal journal, where the statistics show the facts rather than the feelings.