Interactive Supply and Demand Zone Manager in MQL5 (Part IV): Trading Supply and Demand Zones

We extend the supply and demand framework with a strategy layer that converts zone interactions into decisions. Qualified zones pass sequential checks for interaction proximity, approach behavior, higher‑timeframe alignment, and price action before execution is handed to a dedicated trade manager. This architecture improves control, maintainability, and future extensibility without changing the underlying zone engine.

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 2.40 over a sample of 530 executed trades.
• Drawdown Control: Maximum equity drawdown was contained at 11.20%, confirming robust risk management rules.
• Win Rate & Distribution: Win rate stabilized at 49.50%, 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: Interactive Supply and Demand Zone Manager in MQL5 (Part IV): Trading Supply and Demand Zones.