Monte Carlo Drawdown Simulator
A backtest shows you one sequence of trades. Monte Carlo simulation reshuffles that sequence thousands of times to show the range of drawdowns the same strategy could plausibly produce - which is usually worse than the single backtest suggests. Enter your strategy's statistics and run it.
Why Monte Carlo matters
Two strategies with identical backtests can carry very different risk, because a backtest is a single draw from a distribution. Reshuffling trade order reveals the drawdowns hiding in that distribution: a system that showed 8% max drawdown in one backtest will often show a 95th-percentile drawdown two to three times larger across simulations. If that number breaches your account - or your prop firm's limit (check it with the daily loss calculator) - the position sizing is wrong, not unlucky.
This is the same idea Nebula applies automatically: every champion strategy on Pro and Ultimate ships with a Monte Carlo robustness report alongside its walk-forward, out-of-sample results, so you see the distribution before anything touches a live terminal. More on the method in overfitting and walk-forward testing, explained.
Frequently asked questions
Why is the simulated drawdown worse than my backtest?
Because your backtest is one ordering of wins and losses out of billions. Monte Carlo shows the spread of orderings; most strategies' worst plausible streaks simply haven't happened yet in the tested window.
What win rate and R multiple should I enter?
Use out-of-sample figures if you have them - in-sample statistics are usually flattered by overfitting. If you only have a backtest, treat the outputs here as a best case.
How many trades should I simulate?
Match your expected trade count for the period you care about - e.g. a year. Longer horizons produce deeper worst-case drawdowns.
More free tools: risk of ruin · position size · drawdown recovery · all tools.
Educational tool, not financial advice. Simulated results are not predictions. Trading involves risk.