- Introduced `TimeframeAggregator` class for real-time aggregation of minute-level data to higher timeframes, enhancing the `IncStrategyBase` functionality.
- Updated `IncStrategyBase` to include `update_minute_data()` method, allowing strategies to process minute-level OHLCV data seamlessly.
- Enhanced existing strategies (`IncMetaTrendStrategy`, `IncRandomStrategy`) to utilize the new aggregation features, simplifying their implementations and improving performance.
- Added comprehensive documentation in `IMPLEMENTATION_SUMMARY.md` detailing the new architecture and usage examples for the aggregation feature.
- Updated performance metrics and logging to monitor minute data processing effectively.
- Ensured backward compatibility with existing `update()` methods, maintaining functionality for current strategies.
- Introduced `IncMetaTrendStrategy` for real-time processing of the MetaTrend trading strategy, utilizing three Supertrend indicators.
- Added comprehensive documentation in `METATREND_IMPLEMENTATION.md` detailing architecture, key components, and usage examples.
- Updated `__init__.py` to include the new strategy in the strategy registry.
- Created tests to compare the incremental strategy's signals against the original implementation, ensuring mathematical equivalence.
- Developed visual comparison scripts to analyze performance and signal accuracy between original and incremental strategies.
