Monte Carlo Simulator Help

What Is This?

This Monte Carlo simulator helps you estimate the probability of passing a prop firm evaluation based on your actual trading results. It runs thousands of simulated accounts using your real trade data, randomly sampling trades to see how often you'd hit the profit target vs. blow the drawdown limit.

Step 1: Set Your Risk Per Trade

Before uploading, specify how much dollar risk per trade was used in your data. For example, if your strategy risks $400 per trade, enter 400.

This is critical because the Simulate Risk/Trade setting scales your results proportionally:

• If your data used $400 risk and you simulate at $200, all P&L values are halved (more conservative)
• At $600, they're multiplied by 1.5x (more aggressive)

Step 2: Upload Your Trades

Export your trades from NinjaTrader as a CSV file and upload it. The tool reads the Profit column and Entry Time to calculate your trade statistics and average trades per day.

Edge Confidence Analysis

After uploading your trades, an Edge Confidence Analysis panel appears automatically. This answers a critical question before you even run the Monte Carlo: "Is my edge statistically real, or could these results be random luck?"

Expectancy Test (t-test)

Tests whether your average P&L per trade is significantly different from $0.

• t-statistic: Measures how far your average P&L is from $0, relative to the variability in your trades. Think of it as a "signal-to-noise ratio" — higher means your edge is clearer above the randomness.

• p-value: The probability your results happened by pure luck. Below 0.05 = less than 5% chance it's random. Below 0.01 = strong evidence of a real edge.

Win Rate Test (Binomial)

Tests whether your win rate is statistically better than a coin flip (50%). This is especially educational — a 65% win rate over 20 trades is NOT statistically significant, but 65% over 200 trades IS. Sample size matters enormously.

95% Confidence Intervals

Shows the likely range of your true expectancy and profit factor using bootstrap resampling (1,000 iterations).

• If the entire range is positive (expectancy) or above 1.0 (profit factor), that's a good sign
• If the range includes negative values or below 1.0, your edge is uncertain

Sample Size Guidance

Shows your current confidence level and how many more trades you'd need for 90%, 95%, or 99% confidence. This helps you understand when you have "enough" data to trust your results.

Verdict Badges

EDGE CONFIRMED Strong statistical evidence (p < 0.01) and confidence intervals support a genuine edge

LIKELY EDGE Good evidence (p < 0.05), though more data would strengthen confidence

INCONCLUSIVE Promising but not proven; keep trading and re-evaluate

NOT PROVEN Results could easily be random chance; need more trades

NO EDGE Expectancy is negative or zero

Step 3: Configure Your Prop Firm Rules

• Starting Balance: Account size (e.g., $50,000 or $150,000)
• Profit Target: Amount needed to pass (e.g., $3,000 or $9,000)
• Max Drawdown: Maximum loss allowed before failing (e.g., $2,500 or $5,000)
• Trailing Drawdown: When checked, the drawdown floor rises with your equity high (most prop firms use this)
• Max Trades: Stop simulation after this many trades if neither pass nor fail

Robustness Settings (Optional)

• Skip Trades %: Randomly skips a percentage of trades to simulate missed fills, platform issues, or times you're away. A robust strategy should still pass even if you miss 10-15% of trades.
• P&L Variance %: Adds random noise (±%) to each trade's profit/loss to simulate slippage and fill variation. Real trading rarely matches backtest results exactly.

Common Prop Firm Rules (Optional)

• Sample By Day: Instead of sampling random individual trades, this picks a random entire trading day from your history each step. This keeps "good day / bad day" clustering intact (more realistic for many systems).
• Daily Loss Limit: If enabled, the simulator stops trading for the rest of the day once the day's cumulative P&L hits the negative limit. Many prop firms enforce this.
• Minimum Trading Days: Some evaluations require you to trade at least N distinct days. With this on, the simulator won't count as a pass until both the profit target is reached and the minimum days condition is met.
• Consistency Rule: If enabled, the sim fails when any single day profit exceeds the specified percentage of the profit target (example: 40% means no day can make more than 40% of the target).
• Trailing Mode: For trailing drawdown, some firms trail on intraday peak (tight), others effectively trail on end-of-day or realized-only behavior (looser). Use this to test both styles.

Interpreting Results

• Pass Rate: Percentage of simulated accounts that hit the profit target. Above 70% is good; above 85% is excellent.
• Fail Rate: Percentage that hit the drawdown limit and blew up.
• Still Trading: Accounts that neither passed nor failed within the max trades limit.
• Trades to Pass/Fail: How long it typically takes. The "Est. Date" column shows calendar dates accounting for weekends and holidays.
• Equity Paths: Visual sample of how accounts progress. Green = passed, Red = failed, Yellow = still trading.

Strategy Analysis

Beyond pass/fail rates, the simulator provides additional metrics:

• Kelly Criterion: Calculates the optimal percentage of capital to risk per trade based on your win rate and reward:risk ratio. Full Kelly is mathematically optimal but aggressive; Half Kelly is more conservative and commonly recommended. Values under 10% suggest a modest edge; values over 20% indicate a strong edge (but verify with more data).
• Max Drawdown (Simulated): Shows the peak-to-trough drawdown you can expect across simulations. 68% of sims shows the drawdown that 68% of accounts stayed within (similar to 1 standard deviation). 95% of sims shows the drawdown only 5% of accounts exceeded. Use this to mentally prepare for how deep the dips might get.
• Streak Analysis: Shows the average longest losing and winning streaks across all simulations, with standard deviation. If your avg losing streak is 6.5 ±2.1, expect runs of 4-9 consecutive losses regularly. Knowing this helps you stay disciplined during inevitable rough patches.

Tips

• Run with 10% skip and 10% variance for a more realistic estimate
• If pass rate drops dramatically with robustness settings, your edge may be fragile
• More trades in your data = more reliable simulation (100+ trades recommended)
• The simulation assumes your strategy continues performing like the uploaded data — past results don't guarantee future performance

How This Differs from StrategyQuant Monte Carlo

Tools like StrategyQuant X (SQX) use Monte Carlo to test strategy robustness — they randomize parameters, skip trades, reorder history, and add noise to detect curve-fitting. If your strategy fails SQX Monte Carlo, it likely won't perform in live trading.

This tool does something different. It assumes your edge is real and asks: "Given these actual results, what's my probability of passing a prop firm evaluation before blowing the drawdown limit?"