The Prop Firm Challenge, Simulated
A prop firm challenge is an evaluation that asks a trader to reach a profit target without breaching a daily loss limit or a total drawdown limit. The rules interact with position size in a way that decides most outcomes before any judgment about the market is involved.
How it works
A challenge is an evaluation with three numbers in it. A profit target you have to reach, a maximum loss you may take in one day, and a maximum drawdown across the whole account. Reach the target without touching either limit and you are given a funded account.
The rules modeled throughout this page are the common shape of the industry rather than any one firm’s: an 8% profit target, a 4% maximum daily loss, and an 8% maximum total drawdown measured from the starting balance. Individual firms vary and their own documents are the authority.
What follows is a simulation, and it is worth being exact about what it is. Nobody outside a firm can measure that firm’s real pass rate, and any figure quoted for one is marketing rather than data. What can be computed precisely is what the rules do, which turns out to be the more useful question.
The arithmetic of the two limits
Start with an account that has no skill in it at all. Every trade risks a fixed fraction of the starting balance and wins the same amount, with probability one half. Expected value before costs is zero, so anything the results show was produced by the rules and the position size.
Run 40,000 of those accounts at 1% risk per trade and 50.2% reach the target. That is what the maths demands — a symmetric barrier at plus and minus eight percent, approached in equal steps, is a coin flip — and getting it back out of the simulation is the check that the model is not quietly inventing an edge.
Now give the account a real edge - 55 wins in every 100 - and vary only the size. Every row below is 40,000 accounts under identical rules; the only thing that changes is how much is risked per trade.
| Risk per trade | No edge: passed | Winning 55 in 100: passed | Ended on the daily cap |
|---|---|---|---|
| 0.50% | 48.6% | 96.1% | 0.0% |
| 0.75% | 49.9% | 90.0% | 0.0% |
| 1.00% | 50.2% | 83.4% | 0.0% |
| 1.50% | 28.0% | 46.2% | 51.7% |
| 2.00% | 28.6% | 40.8% | 56.7% |
| 3.00% | 38.7% | 50.7% | 39.8% |
Between 1.00% and 1.50% the pass rate with a real edge falls from 83.4% to 46.2%. The edge did not change. Nothing about the trader changed. The only difference is the number typed into the size box, and it nearly halved the outcome.
In practice: what the simulation shows
The cliff has a cause and it is arithmetic. At 1% risk with three trades a day, the worst possible day loses 3% — and the cap is 4%. The daily rule is literally unreachable. Every account that fails does so slowly, on the total drawdown.
At 1.5% risk, three losses cost 4.5%. The cap is now reachable in a single session, and it immediately becomes the dominant failure: 51.7% of accounts end there rather than on the drawdown.
A limit you cannot reach is not a constraint; a limit you can reach in one bad morning is the whole game. That transition happens between two position sizes most traders would consider interchangeable.
Smaller size costs time and buys survival. The 0.5% account in the simulation takes far more trades to reach the same target, and reaches it 96.1% of the time with the same edge. The trade being made is patience for probability.
And accounts that breach the daily cap do it quickly. Across 4,000 seeds at 2% risk, the median breaching account lasted 5 trades — under two trading days — and the longest of 2,693 such runs lasted 38.
A trailing drawdown changes the geometry again. Instead of a fixed floor at 8% below the start, the floor follows the account’s high-water mark upward and never comes back down. Profit made and given back is not neutral under that rule — it permanently raises the level at which you fail.
What a pass rate is not
It is not a measure of the trader. Two people with the same edge and different position sizes have different pass rates, and the table above is the size of that difference.
It is not evidence a firm is fair or unfair. The rules are published, the arithmetic is available to anyone before paying, and the simulation here uses nothing a firm has not stated openly.
It is not a forecast of your result. The model assumes a fixed win rate, equal wins and losses, and three trades a day. Real trading has none of those properties, and the reason to run it is to isolate what the rules do rather than to predict anything.
And it is not a claim about anyone’s advertised figures. Nothing on this page is derived from a firm’s marketing, because there is no way to verify it.
How this connects
The simulation is a risk of ruin calculation with two floors. Expectancy decides whether the account drifts toward the target, and the loss limits decide how often an ordinary losing streak ends it first.
The rules change how a plan is written. A trading plan for an evaluation has to state its size in terms of the limits, and a trading journal kept through the attempt shows whether it was followed.
The pressure produces predictable errors. Revenge trading after a bad morning and overtrading as a deadline nears are trading psychology problems the rule structure makes unusually expensive.
Practice first costs nothing. Paper trading under the exact rules shows whether a size survives before any fee is paid.
And automation does not escape the arithmetic. A trading bot tuned on past data to pass one rule set is overfitting by another name, and a backtest of it faces the same limits as any other.
When it fails
The behavior the rules encourage is the one that breaks them. A target with no deadline rewards patience, and a fee already paid rewards haste. Traders resolve that tension by sizing up, which is exactly the variable the table shows is decisive.
A reset restores the account and changes nothing about the odds. Buying a second attempt after a breach purchases another draw from the same distribution, at the same size, with the same rules.
And the simulation charges nothing for trading, which real accounts do. Every round trip pays the spread plus commission. Adding that cost moves every row in the table downward, and it moves the high-frequency rows furthest.
The last failure is treating the funded stage as the finish. The same rules, often tighter, continue after the evaluation, so the size question this page is about does not go away when the challenge is passed.
The original data
135 of the 24,971 videos measured for this site cover prop firm challenges or evaluations, at a median of 11,433 views, and 437 cover prop firms generally. That is one of the largest supplies in the whole corpus, which makes the absence of a published simulation of the rule set more striking rather than less.
The question: Day four, down three percent, cap is four. Stop or trade?
Every figure on this page was computed for it and is reproducible from the stated assumptions. 40,000 accounts per row, an 8% target, a 4% daily cap, an 8% total drawdown, three trades a day, equal wins and losses. Change any of those and the numbers change; the structure — a cliff where daily risk crosses the daily cap — does not.
Related
Prop firms covers the arrangement itself and what is actually being sold. Risk per trade is the variable this page shows to be decisive. And risk management is the wider frame both sit inside.
I would not judge a challenge on an opinion about the industry, because the table on this page is the whole argument. The variable that moves the outcome most is the one you are most tempted to raise.
— Michael Whitman
This page is educational, not financial advice. Test every idea on your own charts before risking money.