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.
27 行
1.2 KiB
Markdown
27 行
1.2 KiB
Markdown
# Trailing Subsystem (Trailing/)
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## Overview
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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.
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## Key Components
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### Trailing.mqh
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- Aggregates all available trailing stop strategies.
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- Includes: ATR-based, MA-based, Parabolic SAR, and None.
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- Entry point for trailing stop logic selection.
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### TrailingATR.mqh
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- **Class:** `CTrailingATR`
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- **Purpose:** Implements trailing stops based on the Average True Range (ATR) indicator.
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- **Key Features:**
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- Configurable ATR multiplier, periods, and shift.
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- Dynamically adjusts stop loss based on market volatility.
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- Inherits from `CExpertTrailing` for integration with the EA framework.
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## Integration Notes
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- Modular design allows for easy switching between trailing stop strategies.
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- ATR-based trailing is suitable for adaptive, volatility-aware risk management.
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- Additional strategies (MA, Parabolic SAR, None) are included via standard MQL5 modules.
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---
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*Documented April 2026. For further details, see the main project documentation.*
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