Why Do Most Day Traders Lose Money?
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Updated 12 November 2026
Most day traders lose money because leverage makes small mistakes large, costs are paid on every trade, and the other side of each trade is often a professional. On top of that, few traders keep to a plan through losing periods. At IG, 74 % of retail CFD accounts lose money, according to the broker's own risk warning.
Key facts
- 74 % of retail client accounts lose money when trading CFDs with IG (IG Sweden risk warning, read 26 October 2026).
- Across EU brokers, 74 to 89 % of retail CFD accounts typically lost money, according to ESMA (press release, 27 March 2018).
- Of people in Brazil who day traded equity futures for at least 300 days, 97 % lost money and 0.4 % earned more than a bank teller (Chague, De-Losso and Giovannetti, FGV, 2020).
- In the results we publish, 14 of 34 months were negative and the longest losing streak was 4 months, December 2023 to September 2026 (aa_live, 1 October 2026).
How many day traders actually lose money?
A clear majority, in every source that measures it. Brokers in the EU must state the share of their retail CFD accounts that lose money, and ESMA found 74 to 89 % across EU brokers in 2018. IG's Swedish site said 74 % when we read it on 26 October 2026.
Research on day traders who keep going gives an even harder picture. A study from Fundação Getulio Vargas followed everyone in Brazil who started day trading equity futures between 2013 and 2015 and kept at it for at least 300 days. In Day Trading for a Living? the authors found that 97 % lost money and only 0.4 % earned more than a bank teller, about US$54 a day.
| Source | Who was measured | Share that lost money |
|---|---|---|
| IG risk warning | Retail CFD accounts at IG | 74 % (read 26 Oct 2026) |
| ESMA | Retail CFD accounts at EU brokers | 74 to 89 % (2018) |
| Chague, De-Losso and Giovannetti | Day traders in Brazil active 300 days or more, 2013 to 2015 | 97 % |
Why does leverage make day trading so hard?
Because leverage turns a small market move into a large move in your account, in both directions. With CFDs on a major index, a retail client in the EU puts up 5 % of the position value as margin, so a 1 % move in the index is a 20 % move on that margin.
ESMA introduced those limits in its measures on CFDs for retail clients in 2018, at most 20:1 for major indices and gold. The rules also close positions when equity falls to half the margin. A day trader who sizes up after a few good trades can therefore be closed out by one ordinary bad day.
Our article on risk management, stop loss and volatility explains how position size and stop distance decide how much one trade can cost.
How much do costs take from a day trader?
More than most expect, because they are paid on every trade, whether it wins or loses. The spread is the gap between buy and sell price, and a day trader who opens and closes many positions pays it each time. Positions held overnight also pay financing.
The effect grows with the number of trades. Our own algos placed on average 7.7 orders per day from December 2023 to September 2026, according to our live results page. At that pace even a small cost per trade adds up to a real sum over a year, so a rule has to win by more than its costs to come out ahead.
Who is on the other side of a day trader's trade?
Often someone faster, better informed or better capitalised. Every short-term trade has a counterparty, and in liquid markets much of the volume comes from banks, market makers and funds with their own systems and lower costs.
A retail day trader is not forbidden from winning against them, but starts with a handicap. The authors of the Brazilian study conclude that it is close to impossible for individuals to make a living from day trading against that competition, and they found no sign that traders got better with experience.
Why do day traders break their own rules?
Because losing periods are unavoidable and hard to sit through. Even a method that works over time has strings of losing trades and losing months, and in the middle of one it is tempting to move the stop loss, double the size to win it back, or stop trading just before the recovery.
This is how we think about it, not a study. A plan only helps if it is followed on the bad days too, and the bad days are when people change it. That is one reason we write our rules as code, where the stop loss is set on every trade before it opens.
What do losing periods look like in our live data?
They look long and frequent, even in results that went up over time. The figures below are recalculated from the monthly balances in our live data per 30 September 2026, after fees.
| Measure | Our published results | Period |
|---|---|---|
| Negative months | 14 of 34 | Dec 2023 to Sep 2026 |
| Longest losing streak | 4 months | Sep to Dec 2025 |
| Sum of all losing months | −181,513 kr | Dec 2023 to Sep 2026 |
| Largest decline from peak | −23.5 % | Feb to Apr 2024 |
| Decline from the May 2025 peak | −19.6 %, not yet back at the peak | May 2025 to Sep 2026 |
| Result January to September 2026 | −433 kr (−0.2 %) | Jan to Sep 2026 |
The account was below its May 2025 peak for 16 months in a row at the end of September 2026. A person trading by hand would have had to keep the same plan through all of that. Past results, live or backtested, do not predict future returns, and the next losing period can be longer or deeper.
Since October 2026 our main product is A+ Algo Portfolio V2.0, which does not have a live record of its own yet. The live figures in this article come from the algos we ran from December 2023 to September 2026. Every algo and year is listed on A+ Algos in numbers.
Does an algo stop you from losing money?
No. An algo trades the same CFDs with the same leverage and the same costs, so it can lose money just as a person can. What it changes is the rule-breaking, because it places the same stop loss and the same size on every trade, also in the fourth losing month.
That only helps if the rules themselves are sound. If you want to see how an algo behaves in your own account before you decide anything, our guide on how to install a ProRealTime algo shows the setup step by step.
FAQ
What percentage of day traders lose money?
It depends on the market and the group measured, but every source points to a majority. At IG, 74 % of retail CFD accounts lose money (read 26 October 2026). ESMA reported 74 to 89 % across EU brokers in 2018. A Brazilian study of persistent day traders found 97 % lost money over the period studied.
Is it the leverage or the trader that causes the losses?
Both. Leverage makes every mistake larger, and costs are paid whether the trade wins or not. The trader then adds mistakes such as moving the stop loss or trading too large after a loss. With 5 % margin on a major index, a 1 % move in the market is a 20 % move on the margin, so there is little room for either.
Can you day trade without losing money?
Some do over a given period, but no method removes the risk. Our own published results had 14 negative months out of 34 from December 2023 to September 2026, and 2026 was −0.2 % to the end of September. Trading CFDs involves high risk, and you should only use money you can afford to lose.
Is algo trading a way to avoid the mistakes day traders make?
It avoids some of them. An algo does not move its stop or trade bigger to win back a loss, because the rules decide size and exit in advance. It does not remove market risk, costs or the risk that the rules are weak. You can test one free for 14 days before you decide anything.
Summary
Most day traders lose money because leverage, costs and stronger counterparties work against them, and because losing periods make people break their own plans. At IG 74 % of retail CFD accounts lose money, and even our own published results show 14 losing months out of 34.
If you want to see how rule-based trading behaves next to your own, you can test one of our algos free for 14 days.
See the results live. Every month since December 2023 we publish the result of our algos after fees on the live results page. Our algos for IG are on ProRealTime algos.
Trading CFDs involves high risk and you can lose money. Past results, live or backtested, do not predict future returns.