Monte Carlo Trade Simulator
Free Monte Carlo trade simulator: reshuffle your edge thousands of times to see the realistic range of returns and the drawdowns a single backtest hides.
Your backtest is one lucky (or unlucky) ordering of trades. This simulator reshuffles it thousands of times to show the realistic range of returns — and the drawdowns you could actually hit.
QuantDojo · Free tool
Monte Carlo Trade Simulator
Your backtest is one path. Re-shuffle thousands of them to see the realistic range of outcomes — and the drawdowns you could actually hit.
How it works: each run plays out your trades in random order — a win compounds +avg win × risk%, a loss − avg loss × risk%. The spread across thousands of runs is the truth your single equity curve hides.
Educational tool — not financial advice. Assumes trades are independent with fixed win/loss sizes; real returns have streaks, fat tails and changing conditions, so treat this as a floor on the risk, not a ceiling.
Is your backtest lying to you?
Get The Honest Backtest Checklist — the exact red flags that expose an overfit strategy before you risk a cent, plus one rigorous idea a week.
Free forever. Unsubscribe anytime. We test what others sell — no hype. · Prefer to read it now? →
How to use the Monte Carlo trade simulator
Enter your edge — win rate, average win and loss in R, and risk per trade — then the number of trades per run and how many runs to simulate. Hit Run. The simulator reshuffles your trades thousands of times and reports the distribution of outcomes, not a single lucky path.
The headline figures: the median return, the 5th–95th percentile band (your realistic range), the share of runs that end profitable, and the drawdown you should expect — including the worst case. A strategy that looks great on one equity curve often has a 95th-percentile drawdown that would have shaken you out.
Frequently asked questions
What does a Monte Carlo simulation tell a trader?
It turns one backtest into thousands of plausible alternatives by varying the order of trades. That reveals the range of returns and drawdowns you could realistically experience — information a single equity curve hides.
Why is my worst-case drawdown so much larger than my backtest's?
Because your backtest is just one ordering of trades. Reshuffle them and losing streaks cluster differently; the worst arrangements produce far deeper drawdowns. Position for those, not for the lucky path.
Does Monte Carlo prove my strategy works?
No. It quantifies risk given your inputs — it cannot tell you whether the edge is real or overfit. For that you need out-of-sample, multiple-testing-corrected validation.
Monte Carlo shows the range; it cannot tell you the edge is real. Validate that with quantcheck.