8157c42314
- Updated README.md with project overview, key features, directory structure, getting started guide, and modernization roadmap. - Added AI_NETWORK.md detailing the neural network and AI/ML infrastructure, including architecture, components, usage patterns, and next steps. - Introduced DATABASE.md for the Database module, outlining key components, design highlights, usage patterns, and future enhancements. - Created README.md files for Enumerations, Expert, Money, Signals, Structures, System, Trailing, Variables directories, detailing their purpose, key components, and integration notes. - Documented the Signals subsystem, emphasizing modularity, extensibility, and AI/ML readiness. - Added comprehensive descriptions for individual signal modules in Signals/ directory. - Established clear integration notes and recommendations for future improvements across all modules.
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1.2 KiB
Trailing Subsystem (Trailing/)
Overview
The Trailing/ directory contains logic for trailing stop management in the Warrior EA. It supports multiple trailing stop strategies, including ATR-based, MA-based, Parabolic SAR, and none (disabled). Each strategy is modular and configurable.
Key Components
Trailing.mqh
- Aggregates all available trailing stop strategies.
- Includes: ATR-based, MA-based, Parabolic SAR, and None.
- Entry point for trailing stop logic selection.
TrailingATR.mqh
- Class:
CTrailingATR - Purpose: Implements trailing stops based on the Average True Range (ATR) indicator.
- Key Features:
- Configurable ATR multiplier, periods, and shift.
- Dynamically adjusts stop loss based on market volatility.
- Inherits from
CExpertTrailingfor integration with the EA framework.
Integration Notes
- Modular design allows for easy switching between trailing stop strategies.
- ATR-based trailing is suitable for adaptive, volatility-aware risk management.
- Additional strategies (MA, Parabolic SAR, None) are included via standard MQL5 modules.
Documented April 2026. For further details, see the main project documentation.