Interactive Supply and Demand Zone Manager in MQL5 (Part III): Zone Analysis, Stateful Interaction, and Pending Event Management

We extend the stateful supply and demand framework for MetaTrader 5 with a quantitative admission model and a dedicated interaction engine. Candidate zones are scored by structural symmetry, volume participation, and ATR‑normalized displacement, then classified into objective tiers. Admitted zones follow a deterministic lifecycle that tracks first touch, validates bounces, or confirms breakouts, with full telemetry for analysis and reproducibility.

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 1.58 over a sample of 463 executed trades.
• Drawdown Control: Maximum equity drawdown was contained at 8.50%, confirming robust risk management rules.
• Win Rate & Distribution: Win rate stabilized at 50.80%, 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: Interactive Supply and Demand Zone Manager in MQL5 (Part III): Zone Analysis, Stateful Interaction, and Pending Event Management.