The 3-minute walkthrough
1
Enter your strategy
Plug in your win rate, average winner ($), average loser ($), and trades per day. Use real numbers from your backtest or live journal — guessing here defeats the purpose. If you don't have stats yet, use a small live sample (50+ trades) before trusting the output.
2
Configure the prop firm ruleset
Set the account size, profit targets, max drawdown, daily loss, trailing drawdown, and minimum trading days for each phase. These are public on every firm's website — copy them exactly. Toggle daily loss on or off (some firms don't have it).
3
Run 10,000 simulations
Click the simulate button. The engine runs your exact strategy through 10,000 independent Monte Carlo challenges against the rules you set. Results appear in seconds.
4
Read the verdict, then iterate
If Probability to combine is high and Expected ROI is positive — the challenge is a positive-EV bet. If not, tweak the strategy, change the firm, or pick a different account size. The whole point is to test before you pay.
The inputs explained
Strategy setup
Win rate
Percentage of trades that close profitable. From your backtest or live journal. Range 0–100%.
Avg win ($)
Average dollar profit on winning trades. Use nominal dollars — not R-multiples.
Avg loss ($)
Average dollar loss on losing trades. Positive number; the simulator handles the sign.
Trades / day
Average daily trade count. Drives how fast you hit the profit target and how exposed you are to the daily loss rule.
Rule setup (per phase)
Account size
The funded account size you're evaluating ($25K, $50K, $100K, etc). All dollar limits scale from this.
Profit target
The nominal dollar profit required to pass the phase.
Max drawdown
Total drawdown limit from peak (or initial balance, depending on the firm). Hit it and the account is dead.
Daily loss
Hard daily loss cap. Toggle off for firms without one. One bad day breaches it instantly — this is where most traders fail.
Trailing drawdown
Drawdown that follows new equity highs until a threshold. Brutal for strategies that breathe.
Min trading days
Minimum days you must trade before passing. Forces low-frequency traders to overtrade.
The outputs explained
Every output below is the average across 10,000 simulated challenges — not a single backtest, not a feeling. Here's what each number is really telling you.
Probability to combineOutput
What it means
The headline number: the probability that your strategy passes Phase 1, then Phase 2, then survives long enough to collect at least one payout. This is the only metric that combines pass probability and payout probability into one realistic outcome.
How to use it
Above ~25–30% with a rule-compatible strategy, the challenge is usually worth taking. Below 10%, fees are eating you alive. This is the single number that decides 'go' or 'no go'.
Probability of passingOutput
What it means
Probability that your strategy clears all challenge phases (Phase 1 + Phase 2 if two-phase) without breaching any rule.
How to use it
If this is high but Probability to combine is low, your strategy passes but doesn't survive to a payout. Usually a sign the trailing drawdown will kill the funded account fast.
Probability of payoutOutput
What it means
Conditional on being funded, the probability you reach the first scheduled payout without blowing the account.
How to use it
Low number here means your equity curve doesn't survive the post-funding rules. Consider a firm with a less aggressive trailing drawdown or higher daily loss.
Expected days / winning challengeOutput
What it means
Average number of trading days to pass when the challenge does pass.
How to use it
Tells you how long capital is tied up per successful attempt. Useful for planning cash flow and how many challenges to run in parallel.
Expected days / losing challengeOutput
What it means
Average days before the challenge is failed in the simulations that fail.
How to use it
If this is very short, the daily loss or trailing drawdown is killing you early — usually a strategy/rule mismatch. If long, you're slowly bleeding the profit target.
Expected ROIOutput
What it means
Average expected return on the fees you pay across many challenges. Calculated as (expected payout × probability to combine) − fees, then divided by total fee outlay.
How to use it
Positive ROI = paying for challenges is a profitable activity over time. Negative ROI = you're funding the prop firm's revenue. This is the bottom-line number that should drive your decision.
Monte Carlo equity pathsOutput
What it means
A visual sample of the 10,000 simulated equity curves. Shows the realistic range of outcomes — best case, worst case, and the median path.
How to use it
If the spread is huge, your strategy is high-variance and a single backtest is misleading. The thicker the band around the median, the more luck-dependent each individual challenge will be.
Common mistakes when reading the output
- Looking only at Probability of passing. Passing doesn't mean getting paid. Always anchor on Probability to combine and Expected ROI.
- Using fantasy strategy stats. Garbage in, garbage out — use real numbers from at least 50 trades.
- Ignoring trailing drawdown. It's the #1 reason funded accounts die. Always model it accurately.
- Not comparing firms. The same strategy can have a 45% combine probability at one firm and 12% at another. Try at least 2–3 rule sets.
How to use the simulator to actually make money
- Validate before you buy. Run your strategy through the exact firm's rules before spending a dollar on an evaluation.
- Compare firms head-to-head. Same strategy, three different rulesets — pick the firm with the highest Expected ROI, not the one with the flashiest marketing.
- Stress-test changes. Tweaking position size or trade frequency? Re-run before risking real capital.
- Use it as a kill switch. If Expected ROI is negative on every firm, your strategy isn't ready — keep working on edge before paying any evaluation fee.
One failed $300 evaluation pays for the simulator many times over.
The whole point of the tool is to never wonder again whether a challenge is worth taking. You'll know — with numbers — before you click buy.
Another failed challenge: hundreds of dollars.
Knowing before you pay: $49.
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