Warrior_EA/Money/README.md

Money Management Subsystem (Money/)

Overview

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.

Components

Money.mqh

• Aggregates all money management strategies.
• Includes: MoneyFixedRisk, MoneyFixedLot, MoneyIntelligent.
• Entry point for money management logic selection.

MoneyFixedLot.mqh

• Class: CMoneyFixedLot
• Purpose: Fixed lot size per trade.
• Key Features:
  • User-defined lot size (m_lots).
  • Validates lot size against symbol min/max/step constraints.
  • Simple, robust, suitable for static position sizing.

MoneyFixedRisk.mqh

• Class: CMoneyFixedRisk
• Purpose: Risk-based position sizing.
• Key Features:
  • Calculates lot size based on account balance and risk percentage (m_percent).
  • Ensures risk per trade is controlled.
  • Handles both long and short positions.
  • Validates margin and volume constraints.

MoneyIntelligent.mqh

• Class: CMoneyIntelligent
• Purpose: Edge-based, AI-confidence-driven money management (selected via MM_STRATEGY = INTELLIGENT; AI lot scaling is always on).
• Key Features:
  • Scales risk% via a quarter-Kelly criterion: uses the empirically calibrated AI/DB confidence magnitude as the win-probability estimate (p) and the specific trade's real reward:risk ratio (bridged from OpenParams()) as the payoff ratio (b).
  • Only ever scales the configured Money_Risk_Percent down from its input ceiling, never above it.
  • Suitable for advanced, AI/ML-driven strategies.

Integration Notes

• All strategies derive from a common base (CExpertMoneyCustom).
• Designed for modularity and easy extension.
• Can be further enhanced with AI/ML-driven logic for dynamic risk and position sizing.

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Documented April 2026. For modernization and AI/ML integration, see AI_NETWORK.md and project roadmap.