🚀 Advanced MQL5 Trading System

A professional-grade, modular algorithmic trading system for MetaTrader 5, specifically designed for Gold (XAUUSD) scalping strategies.

🏆 Features

Core Architecture

• Modular Design: Clean separation of concerns with dedicated engines
• Professional Grade: Production-ready code with comprehensive error handling
• Zero-Division Protection: Robust mathematical calculations with safety checks
• Advanced Risk Management: Multi-layered risk controls and position sizing
• Configuration-Driven: All parameters externalized for easy tuning
• Comprehensive Risk Management: Multi-layer risk controls and position sizing
• Advanced Market Analysis: Multi-timeframe technical analysis
• Performance Monitoring: Real-time system health and performance tracking

System Architecture

MQL5_Trading_System/
├── MQL5/
│   ├── Experts/
│   │   └── main_controller.mq5          # Central system controller
│   └── Include/
│       ├── Config/
│       │   └── settings.mqh             # System configuration
│       ├── Engines/
│       │   ├── market_engine.mqh        # Market data & indicators
│       │   ├── risk_engine.mqh          # Risk management
│       │   ├── execution_engine.mqh     # Order execution
│       │   └── data_engine.mqh          # Data logging
│       ├── Strategies/
│       │   └── strategy_scalper.mqh     # Scalping strategy
│       └── Utils/
│           └── data_structures.mqh      # Core data structures
└── Python_Analysis/
    └── .env                             # API keys & analysis config

Core Components

1. Main Controller (main_controller.mq5)

• Purpose: Central "operating system" that orchestrates all components
• Responsibilities:
  • System initialization and cleanup
  • Tick-by-tick event processing
  • Health monitoring and error handling
  • Component coordination

2. Market Engine (market_engine.mqh)

• Purpose: Centralized market data and technical indicator calculations
• Features:
  • Multi-timeframe analysis (M5, M15, H1)
  • 15+ technical indicators (RSI, ADX, ATR, EMA, BB, Stochastic, etc.)
  • Market condition analysis
  • Optimized to prevent redundant calculations

3. Risk Engine (risk_engine.mqh)

• Purpose: Final gatekeeper for all trade signals
• Features:
  • Portfolio-level risk management
  • Dynamic position sizing based on ATR
  • Daily/hourly trading limits
  • Correlation risk assessment
  • Market condition filters

4. Execution Engine (execution_engine.mqh)

• Purpose: Direct broker communication and order management
• Features:
  • Robust error handling and retry logic
  • Slippage and latency tracking
  • Position management (modify, close, trailing stops)
  • Execution performance metrics

5. Data Engine (data_engine.mqh)

• Purpose: Comprehensive logging for analysis and ML training
• Features:
  • Structured CSV logging
  • Trade decision logging (approved and rejected)
  • Performance metrics tracking
  • File rotation and management
  • Export functionality for analysis

6. Scalper Strategy (strategy_scalper.mqh)

• Purpose: High-frequency scalping strategy implementation
• Features:
  • Multi-condition signal generation
  • Confidence scoring
  • Market session filtering
  • ATR-based stop loss/take profit

Configuration System

All system parameters are centralized in settings.mqh:

Risk Management

#define MAX_RISK_PER_TRADE          0.5      // Max risk per trade (%)
#define MAX_DAILY_DRAWDOWN          5.0      // Max daily drawdown (%)
#define MAX_CONCURRENT_TRADES       3        // Max simultaneous trades

Strategy Settings

#define ENABLE_SCALPER_STRATEGY     true     // Enable/disable scalper
#define SCALPER_MIN_ATR            0.0003    // Minimum ATR for scalping
#define SCALPER_TAKE_PROFIT_MULT   2.0       // TP multiplier of ATR

Logging Configuration

#define LOG_FILE_NAME              "trade_log.csv"
#define LOG_LEVEL_DEBUG            true      // Debug logging level

Data Structures

The system uses standardized data structures for communication:

MarketSnapshot

Contains complete market state including:

• Current prices (bid, ask, spread)
• Technical indicators across multiple timeframes
• Market condition flags
• Volume and volatility metrics

TradeSignal

Contains complete signal information:

• Strategy identification
• Entry/exit prices
• Risk parameters
• Confidence scoring
• Market context

RiskAssessment

Contains risk analysis results:

• Portfolio and position risk
• Approval status
• Risk limits checking
• Rejection reasons

Installation and Setup

1. MQL5 Setup

1. Copy the entire MQL5 folder structure to your MT5 data directory
2. Compile main_controller.mq5 in MetaEditor
3. Review and adjust settings in settings.mqh as needed
4. Attach the EA to a chart with appropriate parameters

2. Python Analysis Setup

1. Install required Python packages:

   pip install pandas numpy scikit-learn matplotlib seaborn

2. Configure API keys in Python_Analysis/.env
3. Use logged data for performance analysis and ML model training

3. Account Configuration

The system includes both demo and real account configurations:

• Demo Account: For testing and development
• Real Account: For live trading (use with extreme caution)
• Switch between accounts by modifying ACTIVE_ACCOUNT_TYPE in .env file

Risk Management Features

Multi-Layer Risk Controls

1. Position Level: Individual trade risk limits
2. Portfolio Level: Total exposure limits
3. Daily Level: Daily loss limits
4. System Level: Emergency stop mechanisms

Dynamic Position Sizing

• ATR-based position sizing
• Account balance consideration
• Risk percentage limits
• Market volatility adjustment

Market Condition Filters

• Spread checking
• Volatility filters
• Session timing
• News avoidance (configurable)

Logging and Analysis

Comprehensive Data Logging

Every trading decision is logged with:

• Complete market state at decision time
• Signal parameters and confidence
• Risk assessment details
• Execution results and slippage
• System performance metrics

Log Files Generated

• trade_log.csv: Complete trading activity
• performance_log.csv: Performance metrics
• error_log.csv: System errors and warnings
• market_data_log.csv: Market snapshots (optional)

Analysis Capabilities

The logged data enables:

• Strategy performance analysis
• Market condition correlation studies
• Machine learning model training
• Risk assessment optimization
• System performance monitoring

Strategy Framework

Scalper Strategy Features

• Multi-Condition Signals: RSI, EMA, Stochastic, ADX, Bollinger Bands
• Confidence Scoring: 0-100% confidence with weighted factors
• Market Session Awareness: Different behavior during Asian, London, NY sessions
• Volatility Adaptation: ATR-based entry and exit levels
• Risk-Reward Optimization: Configurable R:R ratios

Adding New Strategies

The modular design allows easy addition of new strategies:

1. Create new strategy class in Strategies/ folder
2. Implement CheckSignal() method
3. Add strategy instance to main controller
4. Configure enable/disable flags in settings

System Monitoring

Health Checks

• Connection monitoring
• Engine health verification
• Strategy performance tracking
• Resource usage monitoring

Performance Metrics

• Execution success rates
• Slippage and latency tracking
• Signal generation statistics
• Risk management effectiveness

Emergency Procedures

• Automatic emergency stop on critical errors
• Position closure on system shutdown
• Safe mode operation during health issues

Security Considerations

API Key Management

• All sensitive credentials stored in .env files
• Separate configurations for demo and real accounts
• Regular key rotation recommended

Trading Safety

• Demo account default configuration
• Multiple confirmation layers for real trading
• Risk limits to prevent catastrophic losses
• Emergency stop mechanisms

Performance Optimization

Efficient Indicator Calculation

• Single indicator handle per timeframe
• Batch data retrieval with CopyBuffer()
• Cached calculations to avoid redundancy
• Memory management with proper cleanup

Execution Optimization

• Minimal latency order execution
• Slippage tracking and optimization
• Connection monitoring and retry logic
• Batch logging to reduce I/O operations

Troubleshooting

Common Issues

1. Compilation Errors: Ensure all include paths are correct
2. Indicator Initialization: Wait for sufficient historical data
3. Connection Issues: Check broker connection and trading permissions
4. Log File Access: Ensure MT5 has write permissions for log directory

Debug Mode

Enable debug logging in settings.mqh:

#define LOG_LEVEL_DEBUG            true

System Status Monitoring

Monitor console output for:

• System initialization messages
• Health check results
• Error notifications
• Performance statistics

License and Disclaimer

This trading system is provided for educational and research purposes.

IMPORTANT DISCLAIMERS:

• Trading involves substantial risk of loss
• Past performance does not guarantee future results
• Test thoroughly on demo accounts before live trading
• Never risk more than you can afford to lose
• The authors are not responsible for any financial losses

Support and Contributing

For support, bug reports, or feature requests, please:

1. Test the issue on a demo account first
2. Provide detailed logs and system information
3. Include steps to reproduce the problem
4. Specify your MT5 version and broker details

Version History

Version 1.0.0

• Initial release with complete modular architecture
• Scalper strategy implementation
• Comprehensive risk management system
• Full logging and analysis framework
• Multi-timeframe market analysis engine

---

Remember: Always test thoroughly on demo accounts and never risk money you cannot afford to lose. Trading is risky and this system does not guarantee profits.