A Monte Carlo simulator takes your strategy's statistics and replays them in random order, over and over, to show the range of outcomes those numbers can really produce. The same 45% win rate at 2R can end a hundred trades up 60% or down 20% — this tool makes that spread visible before real money teaches it to you.
Each faint line is one simulated account; the white line is the median run. Risk of ruin = share of the 1,000 accounts whose peak-to-trough drawdown reached your ruin threshold. Position size is a fixed percentage of current balance, matching auto lot-sizing in the simulator.
What the simulator actually does
Every run simulates one account taking your number of trades. Each trade wins with your win-rate probability; a win adds risk% × R to the balance and a loss subtracts risk%, compounding as the balance moves — exactly what fixed-fractional position sizing does in live trading. It does this 1,000 times and reads the distribution:
- Risk of ruin — the share of runs whose drawdown from any peak hit your ruin threshold. Set it to 50% for a personal account, or 10% to mimic a prop-firm drawdown rule.
- 5th / 95th percentile finals — the realistic bad case and good case. If the 5th percentile is unacceptable, the risk per trade is too high for your edge.
- Longest losing streak — the median and worst streak across all runs, so a real streak doesn't surprise you into revenge trading.
The lesson it teaches fastest
Keep the win rate and R:R fixed and raise only the risk per trade. At 1% risk, a bad streak is a dent; at 5% risk, the same streak is a crater, because losses compound down faster than wins compound up. This is the 1% risk rule shown as a picture instead of a lecture — and it is why risk of ruin rises so violently with position size while the edge itself hasn't changed at all.
Where the inputs should come from
Guessing your win rate makes the simulation decorative. Get the real numbers by backtesting: a large enough sample of trades in the simulator gives you a measured win rate, average R, and risk settings — then this tool shows you the variance those numbers carry. The session report's consecutive-loss probabilities and max drawdown are the same mathematics applied to your actual results.
A simulation is not a forecast. It assumes every trade is independent and your stats stay constant — real markets shift, and your execution shifts with them. Treat the output as a stress test of your risk settings, not a promise about future returns.
Embed this simulator on your site
The Monte Carlo simulator is free to embed in any article or tools page. Paste this snippet where you want the widget to appear (the credit line below the frame is the only thing we ask you to keep):
All seven widgets in the free tools collection can be embedded the same way.
If you want pre-computed results rather than your own inputs, the risk of ruin table publishes the output of this same simulation across twenty common strategy profiles.
Monte Carlo simulator FAQ
What is a Monte Carlo simulation in trading?
A Monte Carlo simulation replays your strategy's win rate and risk-reward hundreds or thousands of times in random order to show the full range of equity curves those same numbers can produce. Your one backtest is a single draw from that range - the simulation shows you the good runs, the bad runs, and how deep the drawdowns can get with identical settings.
How do I calculate my risk of ruin?
Risk of ruin is the probability that normal losing variance drives your account down to a level you would consider blown - for example a 50% drawdown, or the 10% limit on a prop-firm account. This simulator estimates it directly: it runs 1,000 simulated accounts with your win rate, risk-reward, and risk per trade, and reports what percentage of them hit your ruin threshold.
Why do two runs with the same win rate look so different?
Because wins and losses do not arrive evenly spaced. A 45% win rate over 100 trades will routinely produce streaks of six or more consecutive losses, and where those streaks land shapes the whole curve. That variance is why a strategy with a real edge can still feel broken for weeks - and why risking too much per trade turns survivable streaks into account-enders.