Monte Carlo Testing: The “Truth Serum” for Your Trading Strategy
By Andrew Lockwood Updated January 2026
If you’ve ever wondered why some prop traders pass evaluations and keep collecting payouts while others fail every challenge, the answer often isn’t luck. It’s stress testing.
In the prop trading classroom, we often see traders with “perfect” backtests fail in live conditions. Why? Because market data is historical, but trading is random. The traders who last are the ones who treat their strategy like a science experiment, not a guessing game.
The Problem with Standard Backtesting
Before flying a new plane, a pilot spends hours in a simulator. Backtesting is your simulator. However, a standard backtest usually runs trades in a specific historical order (e.g., January to December 2025). This creates a dangerous illusion known as Curve Fitting.
• The Trap: Your strategy might look profitable just because it caught a lucky trend in March, even if it would have failed in a choppy market in August.
• The Reality: To survive in prop trading, you need to know how your strategy handles chaos, not just comfort.
What is Monte Carlo Simulation?
Monte Carlo simulation is the “Truth Test” for any strategy. Instead of testing your strategy in one straight timeline, Monte Carlo takes your historical trade results and scrambles the order thousands of times.
Why “Sequence Risk” Matters for Prop Firms
In a personal account, you might survive a 20% drawdown if you eventually recover. In a Funded Trading Plus evaluation, hitting the Maximum Drawdown limit means losing the account.
• Scenario A (Standard Backtest): Win, Win, Loss, Win. (Result: Profitable).
• Scenario B (Monte Carlo Shuffle): Loss, Loss, Loss, Win. (Result: Account Failed).
Monte Carlo reveals the probability of hitting that “Scenario B” streak. If your simulation shows a 30% chance of hitting the drawdown limit, your position sizing is too big, even if the strategy is profitable.
How to Run a Monte Carlo Test (Using Free 2026 Tools)
You don’t need expensive institutional software to do this anymore. As noted in our PropIQ Education, you can now use tools like Excel or even AI.
The “DIY” Excel Method
1. Export Data: Take your backtest results (wins/losses in percentages) and put them in a spreadsheet column.
2. Randomise: Use the =RAND() function to shuffle the order of your trades.
3. Repeat: Run this calculation 100 or 1,000 times to see your “Worst Case” equity curve.
The ChatGPT Method (New for 2026)
As mentioned in our latest updates, AI has democratized quantitative testing.
• Step 1: Copy your list of trade outcomes (e.g., +2%, -1%, +3%, -1%).
• Step 2: Paste them into ChatGPT or a similar LLM.
• Step 3: Ask the AI: “Run a Monte Carlo simulation on these results. Shuffle the order 1,000 times and tell me the maximum drawdown percentage in the worst-case scenario.”
This simple step can save you the cost of an evaluation fee by revealing hidden weaknesses in your system.
Actionable Steps: Before You Buy an Evaluation
1. Pick a Strategy: Whether it’s the ICT Fair Value Gap or an Open Range Breakout, ensure you have at least 100 trades of data.
2. Stress Test It: Run the simulation. If the “worst case” drawdown exceeds 4% or 5%, reduce your risk per trade.
3. Prove It: Only when your simulation survives the “bad luck” scenarios should you enter a challenge.
Get Direct Feedback from Andrew Lockwood
Andrew Lockwood is now offering personalised mentoring sessions designed to help you structure your testing and risk management. Click here for Mentoring Details to book a session and have your strategy reviewed by a veteran of the London Futures Exchange.
Ready to test your proven strategy? View our Available Programs and choose the risk model that fits your data.
Education Disclaimer
All strategy education provided by Funded Trading Plus, including videos, guides, and written materials, is for educational purposes only. Any strategies or trade examples shown are based on simulated trading environments and are not guarantees of success, profit, or passing an evaluation.
Trading outcomes depend on individual decision-making, discipline, and changing market conditions. The performance of any strategy can vary and may result in simulated losses or program failure.
Nothing in this material should be taken as financial advice or an encouragement to trade or invest real money. Trading and simulated trading both carry risk, and past simulated performance does not guarantee future results.
Before making any trading or financial decisions outside a simulated environment, you should seek independent financial advice.
About Andrew Lockwood
Andrew Lockwood is a seasoned professional trader with over 40 years of experience in financial markets. Starting his career on the floor of the London International Financial Futures Exchange (LIFFE) in the 1980s, Andrew has traded through multiple market cycles and volatility regimes. Today, he specialises in prop trading strategies, focusing on technical setups, risk management, and trader psychology. As the founder of PropIQ and a leading mentor, Andrew is dedicated to training the next generation of prop traders with proven, real-world trading methods.