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Monte Carlo Simulation

Play out thousands of possible futures for your strategy. See the best case, the worst case, and the realistic range — before the market shows you.

Monte Carlo fan chart and histogram
Monte Carlo — fan chart of quantiles, result distribution, and extended statistics.

Why run Monte Carlo?

A single equity curve is just one possible path your trades could have taken. Monte Carlo shuffles your trades thousands of times and shows the full range of outcomes — so you can answer questions like:

Two simulation modes

🎲 Bootstrap

RECOMMENDED

Draws random samples with replacement from your real trades, preserving the actual distribution of wins and losses — including rare fat-tail events.

→ Best for 50+ trades. Shows the real risk of your strategy.

📊 Parametric

Uses your win rate, R:R, and risk per trade to generate synthetic outcomes. Good for stress-testing new parameters you haven't traded yet.

→ Best for < 20 trades or testing new rules.

What you get

Each run produces a Fan Chart with five quantile lines (5%, 25%, 50%, 75%, 95%), plus a Result Distribution histogram of final balances. The median is the thick green line — the "most likely" path.

Extended Statistics

Sixteen metrics that go far beyond the basics:

Median Balance
Half of simulations ended above this, half below.
95% CI
Confidence interval (P5–P95). Where 90% of outcomes land.
Win Probability
% of simulations that ended with a profit.
Std Deviation
How widely outcomes spread around the mean.
VaR 95%
Maximum expected loss in the worst 5% of scenarios.
CVaR 95%
Average loss in the worst 5% — always worse than VaR.
Ruin Probability
% of simulations that wiped out the account. Target: 0%.
Max DD (worst)
Worst peak-to-trough drawdown across all runs.
Sharpe Ratio
Return per unit of risk. > 1 is good, > 2 is excellent.
Sortino Ratio
Like Sharpe but only penalizes downside volatility.
Recovery Factor
Average return divided by average drawdown.
Time to Double
% of simulations that doubled the starting balance.

Leverage

Set a leverage multiplier and the simulation scales both profits and losses — proportionally. A 2.0× leverage doubles VaR, CVaR, and maximum drawdown, while doubling expected returns. Use it to model margin strategies or to stress-test your risk.

Let AI read the results

After a run, open the AI Assistant and ask it to analyze the simulation. It walks through every metric, warns you about leverage risk, and gives concrete recommendations. See the AI Assistant page for details.

💡 Tip: Always check Ruin Probability first. If it's above 5%, reduce your risk per trade before looking at returns — a blown-up account doesn't recover.
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