What percentage of traders lose money?

There is no single official number, and the popular line that “90% of traders lose 90% of their money in 90 days” does not come from any study we could find. What exists are several large studies. Each measures something different, so read the wording carefully, but they all point the same way:

  • EU CFD accounts: when the EU securities regulator ESMA restricted CFDs for retail clients in 2018, the figures it cited showed that 74% to 89% of retail CFD accounts lost money, depending on the country, with losses per client of €1,600 to €29,000, as France’s regulator, the AMF, summarised them.
  • Brazilian day traders: a 2019 study by Fernando Chague, Rodrigo De-Losso and Bruno Giovannetti followed everyone who began day trading Brazil’s equity futures market between 2013 and 2015 and kept at it for at least 300 days. 97% lost money, and only 0.4% earned more than a bank teller’s pay, about US$54 a day.
  • Taiwanese day traders: using every trade on the Taiwan Stock Exchange from 1992 to 2006, Brad Barber, Yi-Tsung Lee, Yu-Jane Liu and Terrance Odean found that fewer than 1% of day traders could predictably and reliably beat the market after fees (Journal of Financial Markets, 2014).
  • US investors who trade a lot: studying 66,465 households at a large discount broker from 1991 to 1996, Brad Barber and Terrance Odean found that the households that traded most earned 11.4% a year while the market returned 17.9% (Journal of Finance, 2000).
Retail trader
An individual who trades their own money through a broker, as opposed to a professional firm, a fund or a market maker.
CFD (contract for difference)
A leveraged contract that pays the change in an asset’s price without owning the asset, sold to retail clients by many forex and multi-asset brokers.

Why do day traders lose money? Costs are paid on every trade

Every round trip pays the bid-ask spread, any commission and exchange fees, and slippage: the gap between the price you planned and the price you got. On one trade these are cents. Over hundreds of trades they are often bigger than the edge itself, and a “commission-free” broker still leaves you the spread.

What matters is the cost measured in R, the amount you risk per trade. The same $0.04 a share is 0.04R with a $1.00 stop, 0.20R with a $0.20 stop and 0.40R with a $0.10 stop. That is why fast day trading and scalping, with tight stops and small targets, need a much bigger edge before costs than swing trading does. The trading expectancy lesson shows how to measure it from your own fills.

Turn your phone sideways to read the image. Tap to close.

A line chart of the result per trade in R against the stop distance, from $0.10 to $1.00 a share, for a hypothetical setup with an edge of +0.125R before costs and $0.04 a share in round-trip costs. A dashed line marks +0.125R before costs. The curve after costs starts at −0.275R with a $0.10 stop, is −0.075R at $0.20, crosses zero at $0.32, and reaches +0.045R at $0.50 and +0.085R at $1.00. A note says the tighter the stop, the bigger the same costs are in R.

No tested edge: why most strategies have negative expectancy

An edge is a positive average result per trade after costs, shown over a large sample. Most beginners never measure it. They trade a setup that looked convincing on a few charts, a rule from a video, or a mix that changes every week, so they cannot know whether its expectancy is positive, and once costs are paid the default result of trading without an edge is slightly negative.

A tested edge means written rules, a backtest with realistic costs, a check that the rules did not simply fit past noise (backtest overfitting), and then a forward test on new data or a paper trading account. Skipping these steps does not make a loss certain, but it makes skill impossible to tell from luck. That is what the Taiwan study shows: many traders have one good year, very few have a predictable one.

Edge (trading edge)
A positive expected result per trade after all costs, shown over a large sample of trades taken by the same written rules.
Expectancy
The average profit or loss per trade, usually in R: win rate × average win − loss rate × average loss.

Leverage and position size: how small mistakes become big losses

Leverage multiplies the move, not the skill. At 30:1 leverage, a 3.3% move against the position equals the whole margin; at 10:1 it takes a 10% move. Many CFD, forex and options accounts begin with leverage that turns one ordinary bad day into a large share of the account, which is part of why the CFD loss figures above are so high. Leverage and margin explains how margin calls work.

Position size does the same in a cash account. A trader who risks 5% of the account per trade loses about 23% in five losses in a row; at 1% the same streak costs about 4.9%. Losing streaks are normal even for a good method, so the size of each loss decides whether you last long enough to find out if the method works. The position size calculator turns a stop and a risk percentage into a share count, and risk management adds daily and weekly loss limits.

The behaviour loop: overtrading, revenge trading and moved stops

Costs, leverage and size explain the arithmetic; behaviour explains why the arithmetic gets worse. Barber and Odean linked the poor results of the most active households to overconfidence: trading more meant paying more costs without earning more. The usual loop is a loss, a bigger trade to win it back, a stop moved further away, and then a bigger loss.

These habits have their own lessons. Trading psychology covers fear, FOMO, revenge trading and loss aversion, and common trading mistakes lists the ten most frequent errors with a fix for each. The fix that matters most here is mechanical: a written plan, a fixed risk per trade and a daily loss limit that ends the session.

A worked example: how a small edge turns into a loss (hypothetical)

Hypothetical: a day trader takes 100 trades in XYZ, 500 shares each, with a $0.20 stop, so 1R is $100. 45 trades reach the target for an average of +$0.30 a share (+1.5R), and 55 hit the stop at −$0.20 (−1R). Before costs that is a real, if small, edge. Here is where it goes:

  • Before costs: 45 × $150 − 55 × $100 = $6,750 − $5,500 = +$1,250, or +0.125R per trade.
  • Spread: $0.02 a share per round trip × 500 shares × 100 trades = $1,000.
  • Commissions and fees: $0.01 a share per round trip = $500.
  • Slippage on entries and stops: $0.01 a share on average = $500.
  • After costs: $1,250 − $2,000 = −$750, or −0.075R per trade. The method was right often enough to win before costs and still lost money.

Turn your phone sideways to read the image. Tap to close.

A waterfall chart for 100 hypothetical XYZ day trades of 500 shares with a $0.20 stop. A green bar rises to +$1,250, the result before costs. Three red steps take it down: spread −$1,000, commissions and fees −$500, slippage −$500. The last bar, the net result, ends at −$750, below the zero line. A note reads: an edge of +0.125R before costs becomes −0.075R after costs.

How long does it take to become a profitable trader?

There is no honest number. Anyone who promises profitability in 90 days or a year is guessing, and the evidence is not encouraging: the Brazilian study found no evidence that day traders improved with practice, and in the Taiwan data more than 75% of day traders quit within two years, while many who stayed kept trading despite long records of losses (Barber, Lee, Liu, Odean and Zhang, 2017).

Measure evidence instead of time. Before you risk more, you want at least 100 trades taken under the same written rules, on paper or at a very small size; an expectancy after real costs that stays above zero once its error range is counted; a maximum drawdown you could live with; and a record of following your own rules on almost every trade. If a long, honest sample says the numbers are negative, learning that early is the cheapest outcome. If you are already down a lot, what to do after a big loss has a step-by-step plan.