forked from animatedread/Warrior_EA
AI Expert Advisor
- MQL5 86.1%
- HTML 7.3%
- C 3.8%
- C++ 2.6%
| Filename | Latest commit message | Latest commit date |
|---|---|---|
000c45fdbb
A multi-chart comparison is only valid if every chart is identical except the axis under test, and a drifted setting was previously invisible: the model filename carries a HASH, so two charts that should match and do not look merely "different" with no indication of which field moved. Each signal now logs its effective config plus the raw fingerprint string, unconditionally (not gated on VerboseMode). The six lines diff directly, so an accidental divergence in study period, feature set, focal gamma or anything else feeding training shows up at startup rather than as an unexplained result hours later. Both builds compile 0 errors, 0 warnings. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> |
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| .claude | ||
| .clinerules | ||
| AI | ||
| Database | ||
| DirectML | ||
| Enumerations | ||
| Expert | ||
| Market Descriptions | ||
| Marketing/Logo | ||
| Money | ||
| Panel | ||
| references | ||
| Signals | ||
| Structures | ||
| System | ||
| Trailing | ||
| Variables | ||
| .gitignore | ||
| AI_NETWORK.md | ||
| cpu_directml.log | ||
| DATABASE.md | ||
| opencl.log | ||
| profiling.csv | ||
| README.md | ||
| REFACTOR_NOTES.md | ||
| SIGNALS.md | ||
| Warrior_EA.md | ||
| Warrior_EA.mq5 | ||
| Warrior_EA.mqproj | ||
| Warrior_EA_System_Overview.md | ||
Warrior_EA Project Overview
Description
Warrior_EA is a modular, AI/ML-ready MetaTrader 5 Expert Advisor designed for robust, production-grade trading. It integrates traditional and AI-driven signals, advanced money management, trailing stops, and a database/statistics subsystem for adaptive optimization.
Key Features
- AI/ML Integration: LSTM, PAI, and CONV neural network signals, with configurable feature pipelines and training options.
- Traditional Signals: Modular support for classic indicators (MA, MACD, RSI, etc.) and price action patterns.
- Money Management: Fixed lot, fixed risk, and intelligent/adaptive strategies.
- Trailing Stops: ATR-based, MA-based, Parabolic SAR, and more.
- Database/Statistics: Tracks trades, signals, and performance for optimization and research.
- Configurable Inputs: All major features and strategies are user-configurable via Inputs.mqh.
- Robust Initialization: Retry logic and error handling for all critical subsystems.
- Production-Ready: Designed for institutional and advanced retail use, with a focus on maintainability and extensibility.
Directory Structure
- AI/: Neural network and ML logic
- Database/: Database and statistics management
- Enumerations/: Enum and type definitions
- Expert/: Main EA orchestration and custom logic
- Money/: Money management strategies
- Signals/: Signal generation (AI and traditional)
- Structures/: Data structures for signals and trades
- System/: Utility and infrastructure modules
- Trailing/: Trailing stop strategies
- Variables/: Global input parameters and runtime variables
Getting Started
- Configure your desired strategies and features in
Variables/Inputs.mqh. - Compile
Warrior_EA.mq5in MetaEditor. - Attach to a chart and enable Algo Trading.
- Monitor logs and database/statistics for performance and optimization.
Modernization & AI/ML Roadmap
- Migrate all hard-coded signals to a configurable, feature-driven pipeline.
- Expand AI/ML subsystem with new models and training options.
- Enhance database/statistics for deeper analytics and automated optimization.
- Introduce unit and integration tests for all modules.
Documented April 2026. For subsystem details, see each directory's README.md and AI_NETWORK.md.