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.
45 行
1.8 KiB
Markdown
45 行
1.8 KiB
Markdown
# Money Management Subsystem (Money/)
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## Overview
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The Money/ directory contains all money management logic for the Warrior EA. It provides multiple strategies for position sizing, ranging from simple fixed lots to adaptive, streak-based approaches. Each strategy is encapsulated in its own class and can be selected/configured as needed.
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## Components
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### Money.mqh
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- Aggregates all money management strategies.
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- Includes: MoneyFixedRisk, MoneyFixedLot, MoneyIntelligent.
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- Entry point for money management logic selection.
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### MoneyFixedLot.mqh
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- **Class:** `CMoneyFixedLot`
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- **Purpose:** Fixed lot size per trade.
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- **Key Features:**
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- User-defined lot size (`m_lots`).
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- Validates lot size against symbol min/max/step constraints.
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- Simple, robust, suitable for static position sizing.
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### MoneyFixedRisk.mqh
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- **Class:** `CMoneyFixedRisk`
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- **Purpose:** Risk-based position sizing.
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- **Key Features:**
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- Calculates lot size based on account balance and risk percentage (`m_percent`).
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- Ensures risk per trade is controlled.
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- Handles both long and short positions.
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- Validates margin and volume constraints.
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### MoneyIntelligent.mqh
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- **Class:** `CMoneyIntelligent`
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- **Purpose:** Adaptive, streak-based money management.
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- **Key Features:**
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- Dynamically adjusts lot size based on trade history (winning/losing streaks).
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- Configurable aggressiveness via `m_factor`.
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- Integrates risk-based sizing and optimization.
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- Suitable for advanced, AI/ML-driven strategies.
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## Integration Notes
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- All strategies derive from a common base (`CExpertMoneyCustom`).
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- Designed for modularity and easy extension.
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- Can be further enhanced with AI/ML-driven logic for dynamic risk and position sizing.
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---
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*Documented April 2026. For modernization and AI/ML integration, see AI_NETWORK.md and project roadmap.*
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