Start with the arithmetic, because it is the part nobody disputes and the part most people never work through. A trader who loses 20% of an account needs 25% on what is left to get back to where they started. Lose 50% and the requirement is 100%. The recovery curve steepens fast, and it does so exactly when confidence is lowest and position sizing is least disciplined. This asymmetry is the single most useful thing to understand about drawdown, and it explains why professional risk limits look absurdly conservative to a beginner.
Cost drag on a flat strategy
Assume a strategy with genuinely no edge, a coin flip. It still loses money, because every trade pays a spread and a commission, and every overnight hold pays financing. A trader taking several positions a day is paying that cost dozens of times a week against a distribution centred on zero. The result is a slow, steady decline that looks like bad luck and is actually a fee schedule.
The correct comparison is never win rate against 50%. It is expectancy after all costs, on the instruments and hours you actually trade. That means including the wider spread at the session open, the financing on the trades you held over a weekend, and the conversion if your account currency differs from the instrument. Where those costs come from is set out in how brokers make money, and the calculation itself in expectancy explained.
Leverage does not increase returns, it increases variance
High leverage is sold as access. What it does mechanically is let a small adverse move produce a large account move. A trader with an edge and modest sizing survives long enough for that edge to show. The same trader at eight times the size hits a margin call during a normal losing sequence that the strategy was always going to produce, and never reaches the point where the edge pays.
Every strategy has a run of consecutive losses in it. A system that wins 45% of the time will, over a few hundred trades, produce runs of six or seven losers with no failure of the method at all. Size for that run rather than for the average, and the calculation stops being optimistic. Both leverage and risk management rules cover how to set the number.
Trading leveraged products carries a high risk of losing money, and a majority of retail accounts lose on them. Nothing in this article is a prediction that a particular approach will produce a profit, and none of it is investment advice.
The behaviour that turns a small loss into a fatal one
Most accounts are not destroyed by the market. They are destroyed by what the trader does in the twenty minutes after a loss. The sequence is familiar: a stop is hit, the price then moves in the anticipated direction, the trader re-enters at a worse level and at a larger size to recover the loss quickly, and the second trade goes wrong at four times the risk of the first.
That is revenge trading, and it is the mechanism behind most single-day account failures. Its slower cousin is overtrading, where boredom produces positions that were never part of the plan and the costs accumulate on trades the strategy never called for. Neither is a knowledge problem. Both are what happens when there is no written rule that says when the day stops.
Measuring the wrong thing
Traders judge themselves on the outcome of the last trade, which is close to random over any short sample. A good decision can lose and a terrible one can win, and a run of profitable bad decisions is more dangerous than a run of losses because it teaches the wrong lesson.
The alternative is process measurement: was the setup on the plan, was the size correct, was the stop placed before entry, was the exit the one written down. Score those, and the results become readable over weeks instead of years. This is the entire argument for keeping a trading journal, and it is why a trader who has kept one for six months can tell you exactly which of their setups loses money while a trader who has not will describe their edge in adjectives.
The gap between backtest and account
A strategy that looked strong in testing frequently underperforms live, and the reasons are boring rather than mysterious. The test used the mid price and the account pays the spread. The test filled at the stop level and the account was filled worse in fast conditions. The test traded through news releases where a live account would have been requoted. The test was fitted to the same data used to judge it, which is overfitting, the most common way to produce a curve that never repeats.
The other half of the gap is the trader. A backtest never skips a signal because the last one lost, never doubles up, never moves a stop. A tested strategy is the best case, and it is a ceiling, not an expectation. Backtesting basics covers how to test in a way that makes the ceiling closer to honest.
What the surviving accounts have in common
Working with brokers and prop firms means seeing account histories in bulk, and the difference between the accounts that persist and those that do not is visible without any analysis. The persistent accounts show consistent position sizes. A losing trade looks the same size as the one before it and the one after it. The failing accounts show sizing that jumps, usually after a loss, occasionally after a win.
The persistent ones also trade less. Fewer instruments, fewer setups, longer gaps between positions. And they have a defined stopping point, whether that is a daily loss limit or a rule about stepping away after two losers. Prop firms build those limits into their rule sets for their own protection, which is one of the few genuine benefits of trading under a funded account rule set: the discipline is enforced by something other than willpower on a bad afternoon.
None of that guarantees a profit. There is no arrangement of rules that does. What discipline buys is time in the market long enough to find out whether an edge exists, which is the only condition under which the question can be answered at all.
"Nobody blows an account on a bad trade. They blow it on the fourth attempt to make back the first one, at four times the size."
— Alex Onta, Executive Director, SINGUARD
Key Takeaways
- Recovery is asymmetric: a 50% loss requires a 100% gain, which is why professional risk limits look small.
- Costs make a coin-flip strategy a losing one, so measure expectancy after spread, commission and financing.
- Size for the worst realistic run of consecutive losses, not for the average trade.
- Score process rather than outcome, and enforce a stopping rule so a single bad session cannot end the account.
Frequently Asked Questions
What percentage of traders lose money?
Regulated brokers in several jurisdictions are required to publish the share of their retail accounts that lose money on leveraged products, and those disclosures appear on broker websites. Read the figure for the specific broker rather than relying on a general claim.
Is losing money a sign my strategy is broken?
Not by itself. Every strategy produces runs of consecutive losses. The useful checks are whether the losses came from setups on your plan, whether position size stayed constant, and whether the drawdown is larger than the testing suggested.
Does a funded account make losing less likely?
It enforces loss limits that a personal account does not, which prevents a single session from destroying the balance. It does not create an edge, and trading remains high risk under any rule set.
About the Author
Alex Onta is an Executive Director at SINGUARD. He built eTrader, the terminal, the mobile apps, eTrader Broker, Copytrading, Business and Community, along with the worldwide clustered-server infrastructure it all runs on, with his brother Roman Onta helping on the design, and he leads that division today. Together with Roman he builds the Prop Firm CRM, the Broker CRM, Scalegram and CopySignals, and the two of them carry worldwide compliance, payment processing and international business structuring side by side. He lives and works in Dubai for most of the year. Meet the executive duo leading Singuard's five divisions.