forké depuis animatedread/Warrior_EA
| Fichier | Dernier message de commit | Date du dernier commit |
|---|---|---|
- Introduced `FeatureScale.mqh` with `FeatSquash` function for stateless feature scaling. - Added `RegimeMath.mqh` class for regime arithmetic, including efficiency and variance calculations. - Documented the Mind trading logic in `MIND.md`, detailing the trading process and modes. - Created `VOLNORM_PLAN.md` and `VOLNORM_RESULTS.md` for tick-volume normalization testing. - Implemented `read_book.py` for analyzing trade book data and correlations. - Developed `volnorm.py` for testing tick-volume normalization with new and old methods. |
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| .. | ||
| README.md | ||
| WarriorEnums.mqh | ||
Enumerations Documentation
GlobalEnums.mqh
Defines the ENUM_SIGNAL enumeration for trading signal states:
Buy: Indicates a buy signal.Sell: Indicates a sell signal.Neutral: Indicates a neutral/no-action signal.Undefine: Indicates an undefined or uninitialized state.
InputEnums.mqh
Defines a large set of enumerations for configuration and input parameters used throughout the EA. These include:
- Custom menu and property enums for UI/configuration.
- Period presets (e.g., 5, 10, 14, 20, 30, 50, 100, 200) for indicator calculations.
- Training years presets for ML/AI training window selection.
- ATR multipliers for volatility-based calculations.
- Threshold presets for signal/trigger sensitivity.
- Risk/reward ratio presets for money management.
- Bars expiration settings for trade/session logic.
- Entry multipliers for order sizing.
- Trailing strategy types (none, ATR-based, SAR, MA, etc.).
- Money management strategies (fixed risk, intelligent, fixed lot, etc.).
- Day-of-week and session enums for time-based logic.
- ITF (Intraday Time Filter) settings.
- Hourly session presets (H1-H23) for time filtering.
Purpose: These enumerations provide a strongly-typed, maintainable way to configure and control the EA's behavior, supporting both traditional and AI/ML-driven logic. They enable dynamic feature selection, risk management, and strategy configuration, and are essential for modular, testable code.
Modernization Note:
- Enumerations should be referenced in configuration UIs and parameter files to enable dynamic, user-driven feature pipelines.
- Consider extending enums to support new AI/ML features and dynamic input selection as the EA evolves.