forked from animatedread/Warrior_EA
0f0958856c
Replace old ATR_MULTIPLIER, THRESHOLDS_PRESET enums with new STOP_LOSS_MODE, TAKE_PROFIT_MODE, AI_EXIT_MODE enums that support ATR-based, intelligent confidence-scaled, and swing-anchored modes. Also fix LSTM signal identity string.
47 lines
2 KiB
Markdown
47 lines
2 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:** Edge-based, AI-confidence-driven money management (selected via `MM_STRATEGY = INTELLIGENT`; AI lot scaling is always on).
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- **Key Features:**
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- Scales risk% via a quarter-Kelly criterion: uses the empirically calibrated AI/DB
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confidence magnitude as the win-probability estimate (`p`) and the specific trade's
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real reward:risk ratio (bridged from `OpenParams()`) as the payoff ratio (`b`).
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- Only ever scales the configured `Money_Risk_Percent` down from its input ceiling,
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never above it.
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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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