EA Portfolio Simulator — Test Every EA Combination on One Account

True shared-balance simulation. Free, web-based, runs in your browser. Upload MT4 or MT5 backtest reports and get accurate portfolio performance in seconds.

Every Expert Advisor looks good in isolation. The backtest shows a smooth equity curve, a manageable drawdown, and an attractive profit factor. But the moment you run multiple EAs on the same account, reality diverges from the individual backtests — sometimes dramatically.

An EA portfolio simulator answers the question individual backtests can’t: what actually happens when these EAs trade together on a shared account?

FXOptimize is a free, web-based EA portfolio simulator that tests every possible combination of your Expert Advisors using true shared-balance simulation. Upload your MT4 or MT5 backtest reports and get accurate portfolio performance in seconds.

What Is EA Portfolio Simulation?

EA portfolio simulation is the process of combining multiple Expert Advisor backtests into a single account simulation to see how they perform together. Unlike viewing individual backtests side by side, a proper portfolio simulation accounts for:

• Shared account balance: All EAs trade from the same pool of capital
• Concurrent positions: Multiple EAs may have positions open at the same time
• Margin interaction: Open positions from one EA affect available margin for others
• Lot size dependencies: If EAs scale lots by balance, one EA’s losses affect another EA’s sizing
• Drawdown stacking: When multiple EAs lose simultaneously, the combined drawdown can be far worse than any individual drawdown

The goal is to find the combination of EAs that produces the best risk-adjusted returns — not just the highest profit, but the best balance between returns and drawdown.

Why Individual Backtests Don’t Tell the Full Story

Consider three EAs, each backtested individually:

• EA Alpha: 85% annual return, 18% max drawdown
• EA Beta: 62% annual return, 12% max drawdown
• EA Gamma: 74% annual return, 15% max drawdown

Looking at these numbers, you might expect a portfolio of all three to have roughly 221% annual return with a max drawdown somewhere around 18% (the worst individual drawdown). After all, diversification should help, right?

In reality, the combined portfolio’s max drawdown could be 35% — or worse — if the EAs’ drawdowns overlap. And the combined return won’t be 221% either, because the shared balance means each EA is effectively trading with a smaller portion of the account.

This is why you need a simulator, not a spreadsheet.

How Drawdown Stacking Works in EA Portfolios

Drawdown stacking is the phenomenon where multiple EAs experience losses at the same time, and the combined loss is greater than any individual EA’s max drawdown.

It happens more often than most traders expect. Market-moving events — NFP releases, central bank decisions, geopolitical shocks — tend to affect all currency pairs simultaneously. If your EAs trade correlated pairs or use similar entry logic, their drawdowns will cluster.

Here’s the math that makes it dangerous: if EA Alpha draws down 15% and EA Beta draws down 12% at the same time on a shared account, the combined drawdown isn’t 15% (the max individual). It’s approximately 25% (compounded on the same balance). Add a third EA drawing down 10% in the same period, and you could be looking at 40%+.

A proper expert advisor portfolio simulator reveals these stacking events that are invisible when looking at individual backtests.

Pareto Optimization for EA Portfolios

When you have 8 EAs, there are 255 possible combinations (2⁸ - 1). With 12 EAs, that’s 4,095 combinations. Testing each one manually is impractical. This is where Pareto optimization comes in.

Pareto optimization finds the set of Pareto-optimal (or “non-dominated”) portfolio combinations. A combination is Pareto-optimal if no other combination is better on all criteria simultaneously.

For example, Portfolio A with 80% return and 15% drawdown is Pareto-optimal if no other portfolio has both higher return AND lower drawdown. Portfolio B with 90% return and 20% drawdown is also Pareto-optimal — it’s better on return but worse on drawdown.

FXOptimize automatically calculates the Pareto frontier across all possible EA combinations, showing you the optimal trade-off between return and risk. You choose where on that frontier you want to be based on your risk tolerance.

17 Risk Metrics Explained

FXOptimize calculates 17 risk metrics for each portfolio combination. Here’s what each one tells you:

Correlation Analysis: The Hidden Portfolio Risk

Two EAs can both be profitable individually yet be terrible together — if they’re highly correlated. Correlation analysis reveals which EAs actually provide diversification and which are essentially duplicating the same trades.

FXOptimize calculates Pearson correlation on daily returns between every pair of EAs in your portfolio. The result is displayed as a color-coded heatmap:

• Green (< 0.3): Low correlation — these EAs genuinely diversify each other
• Yellow (0.3 – 0.6): Moderate correlation — some overlap, some diversification
• Red (> 0.6): High correlation — these EAs tend to win and lose at the same time

The best portfolios combine EAs with low correlation to each other. This reduces drawdown stacking because when one EA is losing, the others are more likely to be winning (or at least not losing as much).

Monte Carlo Stress Testing

Your backtest represents one specific sequence of trades. But what if the trades happened in a different order? What if there were more losing streaks? Monte Carlo simulation answers these questions by:

1. Randomizing trade order: Shuffling the sequence of trades thousands of times to see the range of possible outcomes
2. Calculating confidence intervals: What’s the worst-case drawdown at 95% confidence? At 99%?
3. Stress testing robustness: If your portfolio only works with one specific trade sequence, it’s fragile

A robust portfolio should show acceptable performance across most Monte Carlo simulations, not just the historical sequence. If Monte Carlo reveals that 10% of simulations produce 50%+ drawdowns, you know the portfolio is riskier than the backtest suggests.

How FXOptimize’s Simulator Works

The simulation process:

1. Parse: Upload MT4/MT5 backtest HTML reports — the parser handles both formats automatically
2. Normalize: Trade data from different formats is normalized into a common structure
3. Combine: All trades are placed on a single timeline, sorted chronologically
4. Simulate: The event-based engine replays all trades with a shared balance, calculating lot sizes, margin, and equity at each step
5. Optimize: All 2ⁿ combinations are evaluated, and the Pareto frontier is calculated
6. Analyze: 17 risk metrics, correlation matrix, and Monte Carlo results are generated

All of this runs in your browser. No data is sent to any server. The simulation typically completes in seconds, even for large portfolios.

Who Needs an EA Portfolio Simulator?

An EA portfolio simulator is essential if you:

• Run 2 or more EAs on the same trading account
• Want to know the real combined drawdown before going live
• Are selecting which EAs to include from a larger collection
• Need to right-size position scaling for a multi-EA account
• Want to optimize for risk-adjusted returns, not just total profit
• Are comparing your portfolio’s performance against other portfolio tools