Block a user
a25499e016
Refactor backtesting logic to include slippage estimation, enhancing trade execution realism. Update load_data function to accept a CSV file parameter. Improve summary output with slippage metrics and adjust main script for new slippage configuration. Correct typos in project documentation.
289d11b0a8
Refactor main script and introduce CLI for OHLCV Predictor. Consolidate functionality into a new package structure, enhancing modularity. Update README to reflect new features and usage instructions, including the requirement for a companion feature list JSON. Add configuration classes for better parameter management and streamline data loading and preprocessing.
70da858aac
Update inference documentation and main script for improved usability. Revise README for clarity on data requirements and minimal usage. Adjust main.py to ensure proper handling of test predictions and add checks for local variables before plotting.
add3fbcf19
Add evaluation module with walk-forward CV and metrics computation. Enhance feature engineering with additional OHLCV features and rolling statistics. Update main script to integrate walk-forward CV for feature importance and pruning.
21b14d4fe4
Enhance backtesting functionality by adding date range parameters to load_data, improving ATR calculation, and refining trade logic with meta Supertrend signals. Update README with detailed usage instructions and requirements. Add CSV logging for trade results and performance metrics. Include ta library as a dependency in pyproject.toml.
a419764fff
Enhance CustomXGBoostGPU for inference by making training data optional and adding model loading functionality. Update feature engineering to support caching and improve data handling. Introduce a new inference example and README for better usability in other projects.
b56d9ea3a1
Remove print statements for loading cached features and replace pandas-ta with ta library for technical indicators in feature engineering and calculations. Simplify Supertrend implementation using ATR and moving averages.
3e08802194
Add comprehensive rules for project management, including global development standards, architecture guidelines, code review processes, context management, task generation, and iterative workflows. Establish documentation standards and refactoring protocols to enhance maintainability and prevent technical debt.
56dca05a3e
Initial project setup with Python version 3.12, main script for backtesting trading strategies, and configuration files for project management. Added necessary dependencies and documentation structure.
65f30a4020
Enhance backtesting framework with static task processing and progress management. Introduced static task processing for parallel execution, improved error handling, and added a progress manager for better task tracking. Updated BacktestRunner to support progress callbacks and optimized worker allocation based on system resources. Added new configuration files for flexible backtesting setups.
be331ed631
Remove unused GSheetBatchPusher class and xgboost model file to streamline codebase and eliminate deprecated components.
6c5dcc1183
Implement backtesting framework with modular architecture for data loading, processing, and result management. Introduced BacktestRunner, ConfigManager, and ResultProcessor classes for improved maintainability and error handling. Updated main execution script to utilize new components and added comprehensive logging. Enhanced README with detailed project overview and usage instructions.
02e5db2a36
Added comprehensive rules for global development standards, architecture guidelines, code review processes, context management, PRD creation, documentation standards, enhanced task list management, task generation, iterative workflow, project-specific rules, refactoring practices, and task list management. These rules aim to improve code quality, maintainability, and integration of AI-assisted development.
65f30a4020
Enhance backtesting framework with static task processing and progress management. Introduced static task processing for parallel execution, improved error handling, and added a progress manager for better task tracking. Updated BacktestRunner to support progress callbacks and optimized worker allocation based on system resources. Added new configuration files for flexible backtesting setups.
be331ed631
Remove unused GSheetBatchPusher class and xgboost model file to streamline codebase and eliminate deprecated components.
6c5dcc1183
Implement backtesting framework with modular architecture for data loading, processing, and result management. Introduced BacktestRunner, ConfigManager, and ResultProcessor classes for improved maintainability and error handling. Updated main execution script to utilize new components and added comprehensive logging. Enhanced README with detailed project overview and usage instructions.
02e5db2a36
Added comprehensive rules for global development standards, architecture guidelines, code review processes, context management, PRD creation, documentation standards, enhanced task list management, task generation, iterative workflow, project-specific rules, refactoring practices, and task list management. These rules aim to improve code quality, maintainability, and integration of AI-assisted development.
0bbb0e52af
Did feature selection, moved from RMSE to MAE for accuracy testing (maybe not a good idea after all), fine tuned hyperparameters a bit (need to do more)
082a2835b6
Implemented Supertrend indicators for feature engineering in main.py, including caching of computed features. Updated plotting functions in plot_results.py to save charts in a dedicated directory and added new functions for directional accuracy and prediction transition heatmaps.
ada6150413
Added multiple technical indicators for feature engineering, including ADX, TRIX, Vortex, KAMA, Force Index, EOM, MFI, ADI, TEMA, StochRSI, and Awesome Oscillator. Improved NaN handling and implemented leave-one-out feature evaluation with results saved to CSV.
ced64825bd
reverted to sequential computing for features, added one distribution visualization graph