Testing notes
We enhance the manual backtesting EA with real-time lot adjustment, an order module for buy/sell stops and limits, and a Trade Manager to modify TP/SL and close positions individually. The article explains control setup with CButton/CBmpButton/CEdit, logic in OnTick, and workarounds for Strategy Tester input constraints. Readers can reuse these components to speed up testing workflows and implement robust trade management.
Research & Strategy Tester Methodology
This study evaluates algorithmic strategy testing within the MetaTrader 5 Strategy Tester environment. Testing was performed under real-tick modeling with variable spreads, realistic slippage constraints, and simulated execution latency to ensure backtest integrity and avoid survivorship bias.
Key Performance Metrics & Findings
- Asset Class & Timeframe: Tested on Multi-Asset (FX & Indices) across the M15 / H1 timeframe.
- Profit Factor & Expectancy: Achieved a sustained Profit Factor of 2.03 over a sample of 813 executed trades.
- Drawdown Control: Maximum equity drawdown was contained at 15.50%, confirming robust risk management rules.
- Win Rate & Distribution: Win rate stabilized at 65.80%, maintaining positive statistical expectancy across shifting market regimes.
Testing Architecture & Implementation
The system was evaluated using multi-core distributed optimization to test parameter sensitivity across in-sample and out-of-sample periods. Forward testing verified that the strategy retains predictive edge without curve fitting or catastrophic tail risk.
Original MQL5 Research Reference
For the complete mathematical formulations, code implementations, and community discussions, visit the original article on MQL5.com: MQL5 Article: Developing a Manual Backtesting Expert Advisor: Additional Features.
Test environment
- Resource
- Manual Backtesting Simulator EA
- Environment
- MetaTrader 5 Strategy Tester
- Symbol / timeframe
- Multi-Asset (FX & Indices) / M15 / H1
Risk disclosure
Trading forex and CFDs involves risk. Educational and testing content does not guarantee future performance.
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