Release v1.0.2

Release v1.0.2

I am excited to announce the release of version 1.0.2 of the Genetic Algorithm for Trading Strategy Optimization project.

What's New

• Improved performance in multi-process parallel computation
• Enhanced dynamic strategy generation
• Bug fixes and stability improvements

Key Features

This release maintains all the core features of our project:

• Genetic algorithm optimization for trading strategies
• Optimization of strategy parameters and trading pair selection
• Support for setting maximum open trades
• Multi-process parallel computation
• Dynamic strategy generation and evaluation
• Saving of best individuals from each generation
• Configurable optimization parameters
• Optional data downloading before running the algorithm
• Checkpointing and ability to resume from the latest checkpoint

Installation

Please refer to the README.md file for detailed installation instructions.

Usage

Basic usage:

python main.py

For more options and examples, please check the Usage section in the README.md file.

Community

Join our community channels for updates, discussions, and support:

• GeneTrader Telegram Channel
• GeneTrader Algorithm Group

Feedback and Contributions

We welcome your feedback and contributions. Please submit issues or pull requests on our GitHub repository.

Disclaimer

This project is for educational and research purposes only. It does not constitute investment advice. Users are responsible for any risks associated with using this project for actual trading.

v1.0.1 - Universal Strategy Optimization

Release Date: 2024-09-21

This release introduces a universal strategy optimization feature, allowing users to optimize any custom strategy.

New Features

• Added a universal strategy optimizer interface
• remove template.py

Bug Fixes

• Fixed an issue where strategy execution failed under specific conditions

v1.0.0

GENETRADER v1.0.0

We're excited to announce the first official release of GENETRADER, an innovative trading strategy optimization tool using genetic algorithms.

Features

• Genetic algorithm-based strategy optimization
• Backtesting framework integration
• Customizable trading parameters
• Support for multiple trading pairs and timeframes
• Detailed performance metrics and visualization

Installation

1. Clone the repository:

   git clone https://github.com/your-username/genetrader.git
   cd genetrader
   

2. Install dependencies:

   pip install -r requirements.txt
   

Usage

1. Configure your trading parameters in config.json

2. Run the optimization:

   python main.py
   

3. View results in the results directory

Documentation

For detailed usage instructions and API documentation, please refer to our Wiki.

Changelog

Added

• Initial implementation of genetic algorithm
• Backtesting integration with [Your Backtesting Framework]
• Support for [list of supported trading pairs]
• Performance visualization using [Your Visualization Library]

Changed

• N/A (First Release)

Fixed

• N/A (First Release)

Known Issues

• [List any known issues or limitations]

Upcoming Features

• Web interface for easier configuration and result viewing
• Support for more exchanges and trading pairs
• Advanced genetic operators for improved optimization

We welcome contributions and feedback from the community. Please report any issues or suggestions on our GitHub Issues page.

Thank you for your interest in GENETRADER!