Commit graph Warrior_EA/Signals/Wyckoff/WyckoffFeed.mqh
Author SHA1 Message Date
AnimateDread
e9c562b39f Add Feature Scaling and Regime Math Classes; Implement Mind Trading Logic
- 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.
2026-09-30 18:36:33 -04:00
AnimateDread
47a5ef338b Refactor Warrior EA: Integrate custom signal modules, enhance voting mechanism, and improve management features
- Replaced standard library signal modules with custom implementations to allow for named patterns and improved voting.
- Added new input parameters for module weights, allowing for optimization of individual signal contributions.
- Enhanced the management of trades with new options for breakeven and management cut.
- Introduced a mechanism for dynamic ranking of signal weights based on historical performance.
- Improved initialization logic to ensure proper registration of filters and handling of trading conditions.
- Added detailed logging for trading permissions and account status during initialization.
2026-09-13 14:32:40 -04:00
AnimateDread
ac57a720e0 wip: snapshot before the KISS restructure
Everything from tonight, committed so the restructure that follows is
recoverable: the graded stdlib vote, the Wyckoff modules and feed, the
ALGLIB serializer workaround, the restored DB queue, and the Simple/
prototype that is about to be folded into the real filetree.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-09-11 06:16:08 -04:00