Quantitative Apex Prop Firm (QAPF) – User Guide and Calibration
Quantitative Apex Prop Firm (QAPF) – User Guide and Calibration
Introduction
The Quantitative Apex Prop Firm (QAPF) Expert Advisor is designed to comply with the strict rules of proprietary trading firms (FTMO, MFF, The Funded Trader, etc.).
It executes only one trade per day, based on a rigorous and automated system.
Objective: provide a simple, disciplined, and secure trading framework suitable for both personal accounts and proprietary firm challenges.
How the EA Works
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One position per day at the programmed time (Trade Open Hour = 9:00 by default, server time).
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Trade direction is determined by a set of technical filters.
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Positions are automatically protected by Stop Loss and Take Profit based on the defined Risk/Reward Ratio.
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Automatic closure of trades at the specified time (Trade Close Hour = 16:00 by default, server time).
Money Management
Fixed Lot: recommended for stability and prop firm trading.
Example: 0.02 lot on a $1,000 account with 1:100 leverage → approx. $20 risk for a 2,000-point SL on XAUUSD.
⚠️ Important: this is only an example. For proprietary firms, lot size must be adapted to the account size and the firm’s rules.
Dynamic Lot (% of Balance):
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Automatically adjusts lot size according to account balance.
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Can also be used in prop firms if the risk per trade is ≤ 2%, and up to 5% for personal accounts.
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Lot size calculation takes account leverage into consideration to ensure correct margin adjustment.
Always check the minimum and maximum lot sizes allowed by your broker.
Proprietary Firm Compliance
Automatic monitoring of daily, weekly, and monthly drawdown limits:
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Daily max loss = 2%
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Weekly max loss = 3%
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Monthly max loss = 7%
If a limit is breached → a cooldown is triggered to block new trades and prevent disqualification.
Trade Opening and Closing Times
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Trade Open Hour = 9:00 (server time) by default.
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Trade Close Hour = 16:00 (server time) by default.
⚠️ Important: The EA was coded based on Paris time. If you are not in the +1 timezone, adjust your entry and exit settings accordingly.
Recommendation: schedule trades at the opening of the European (London) or US (New York) session to benefit from higher volatility and capture larger moves.
Calibration Tips
Symbol & Timeframe
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Designed for XAUUSD.
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Main timeframe: H1, with long-term filtering on D1.
Stop Loss & Risk/Reward
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Default SL: 2,000 points, adjustable. (Modify if TP/SL distance becomes too large vs. entry price.)
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RRR range: 1.2 – 2.0 depending on trading style.
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Conservative: wider SL, RRR 1.2–1.5.
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Aggressive: tighter SL, RRR 1.5–2.0.
Lot Size
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Fixed lot: full control → ideal for prop firms.
Example: 0.02 lot on $1,000 with 1:100 leverage (must be adapted to account size and firm rules). -
Dynamic lot (% of balance): suitable for prop firms if risk ≤ 2%; up to 5% for personal accounts.
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The dynamic lot calculation factors in account leverage to ensure correct risk management.
Best Practices
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Stick to 1 trade per day → don’t force extra trades.
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Use a VPS for stability and execution speed.
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Always test on demo or cent accounts before starting a challenge.
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Reference capital reset: every Monday and the first day of each month.
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Don’t change settings mid-challenge without proper backtesting.
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Avoid over-optimization → keep the strategy robust and simple.
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Update SL and RRR every 6 months if the gap between entry and exit grows too wide (this may happen if XAUUSD’s price increases significantly compared to when the EA was first activated).
Conclusion
QAPF combines discipline and strict risk management, both of which are essential for success in proprietary firms or personal accounts.
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Prop firms: use a fixed lot or dynamic lot ≤ 2% of balance, and adjust SL/RRR according to capital, rules, and leverage.
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Personal accounts: dynamic lot 3–5% max, with SL/RRR adapted to your profile.
Test it, calibrate it to your needs, and let automation handle the rest.
For questions or assistance regarding the EA, feel free to contact me directly by private message on MQL5—I’ll be glad to help.
Definition Files
For greater accuracy, backtests were run over one year, but their validity has been proven for 5–10 years.


