From ee1185c7ba492fdcd101ace65337df92d6fccd6f Mon Sep 17 00:00:00 2001 From: laura-abro Date: Wed, 23 Apr 2025 12:43:41 -0300 Subject: [PATCH] Create Prometheus-generated README file --- README_Prometheus.md | 412 +++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 412 insertions(+) create mode 100644 README_Prometheus.md diff --git a/README_Prometheus.md b/README_Prometheus.md new file mode 100644 index 0000000..f178284 --- /dev/null +++ b/README_Prometheus.md @@ -0,0 +1,412 @@ +# VSVTrend: An Adaptive Intelligent Trading Strategy for TradingView + +## Project Overview + +VSVTrend is an advanced trading strategy developed for TradingView using Pine Script, aimed at creating a sophisticated, adaptable trading indicator for financial markets. The project focuses on developing a high-accuracy trading strategy that can be used across various financial instruments and timeframes. + +### Core Purpose +The primary objective of VSVTrend is to create a robust, intelligent trading strategy that minimizes false signals and provides traders with a flexible, data-driven approach to market analysis. It aims to solve common challenges in trading strategy development, such as: +- Reducing false trading signals +- Providing adaptive risk management +- Offering customizable trading parameters + +### Key Features +- **Adaptive Trading Signals**: Utilizes Supertrend indicator with configurable parameters +- **Flexible Strategy Control**: + - On/Off toggle for the entire strategy + - Optional Supertrend filter + - Customizable ATR (Average True Range) period +- **Risk Management**: + - Configurable Stop Loss (1.5% default) + - Configurable Take Profit (3% default) +- **Backtesting Support**: Full compatibility with TradingView's strategy testing framework +- **Machine Learning Integration**: Preliminary AI/ML module for false signal detection + +### Unique Selling Points +- Open-source and community-driven approach +- Works across multiple timeframes +- Designed for continuous improvement through community feedback +- Balances technical indicators with potential machine learning enhancements + +## Getting Started + +### Quick Start for TradingView + +#### Prerequisites +- TradingView account with Pine Script access +- Basic understanding of trading strategies + +#### Using the VSVTrend Strategy + +1. Open TradingView and navigate to the chart of your desired asset +2. Open the Pine Editor (View > Pine Editor) +3. Copy and paste the entire content of `VSVTrend.pine` +4. Click "Add to Chart" to apply the strategy + +#### Strategy Configuration + +The strategy offers several customizable inputs: + +- **Strategy ON/OFF**: Toggle the entire strategy +- **Supertrend Filter**: Enable/disable the Supertrend filter +- **ATR Period**: Adjust the Average True Range period (default: 10) +- **Factor**: Modify the Supertrend calculation factor (default: 3.0) +- **Stop Loss**: Set stop loss percentage (default: 1.5%) +- **Take Profit**: Set take profit percentage (default: 3.0%) + +#### Basic Usage + +- The strategy generates long and short entries based on the Supertrend indicator +- Entries are made with 10% of account equity per trade +- Automatic take profit and stop loss are applied to manage risk + +#### Important Notes + +- Always backtest the strategy thoroughly before live trading +- Performance may vary across different assets and timeframes +- Use the strategy responsibly and manage your risk + +## Installation and Setup + +### Prerequisites +- TradingView Pro or Pine Editor access +- Basic understanding of Pine Script +- Trading account with compatible broker + +### Installation +1. Open TradingView Pine Editor +2. Copy the entire contents of `VSVTrend.pine` +3. Paste the script into a new Pine Script strategy +4. Customize strategy parameters as needed: + - `show_strategy`: Toggle strategy on/off + - `use_supertrend`: Enable/disable Supertrend filter + - `atrPeriod`: Set Average True Range period (default: 10) + - `factor`: Adjust Supertrend sensitivity (default: 3.0) + - `sl`: Stop Loss percentage (default: 1.5%) + - `tp`: Take Profit percentage (default: 3.0%) + +### Configuration Options +- **Strategy ON/OFF**: Control overall strategy activation +- **Supertrend Filter**: Toggle additional trend confirmation +- **ATR Period**: Adjust Average True Range calculation length +- **Stop Loss/Take Profit**: Set risk management percentages + +### Compatibility +- Pine Script Version: 5 +- Compatible with all TradingView timeframes +- Works best with liquid trading instruments + +### Deployment +1. Validate strategy parameters +2. Run backtesting to verify performance +3. Enable paper trading for risk assessment +4. Consider gradual live trading implementation + +### Recommended Workflow +1. Start with minimal position sizing +2. Extensively backtest across different market conditions +3. Monitor and adjust parameters based on performance +4. Implement proper risk management + +### Notes +- This is an experimental strategy +- Always use stop losses and proper risk management +- Past performance does not guarantee future results + +## Dataset + +### Data Overview +The project uses trading data for strategy development and testing. Key dataset characteristics include: + +#### Source +- Internal trade log sample: `data/sample_tradelog.csv` +- Derived from financial market trading data compatible with TradingView + +#### Structure +The sample trade log contains historical trading information used for: +- Model training +- Performance analysis +- Signal validation + +#### Data Requirements +- Compatible with multiple timeframes +- Supports various financial instruments +- Designed for backtesting trading strategies + +### Data Preparation +- Trade data is processed using the strategy's built-in backtesting functionality +- Optional AI/ML module for false signal detection enhances data quality +- Adaptive indicators help refine trading signals + +### Data Constraints +- Sample data provided is for demonstration purposes +- Users are encouraged to use their own trading data for personalized strategy optimization + +## Model Architecture and Training + +### Model Architecture + +The VSVTrend strategy incorporates an AI/ML module designed to detect potential false trading signals. While specific details of the machine learning model are not fully disclosed, the approach aims to enhance trade accuracy through intelligent signal filtering. + +### Training Approach + +The strategy includes a planned machine learning component for false signal detection. The training process is intended to: +- Use historical trading data for model training +- Identify and filter out potentially unreliable trade signals +- Improve overall trading strategy performance + +### Training Data + +- A sample trade log is provided in `data/sample_tradelog.csv` +- The training data likely contains historical trade information to train the signal detection model + +### Training Considerations + +- The ML module is designed to be adaptable across different timeframes +- The goal is to create a robust, community-driven approach to signal validation + +**Note:** Detailed implementation of the machine learning training script is currently not available in the repository. Future updates may provide more comprehensive training instructions. + +## Evaluation and Results + +### Evaluation Methodology + +The VSVTrend strategy is designed for robust trading signal generation and includes several built-in evaluation mechanisms: + +#### Performance Metrics +- Risk Management: Adaptive Stop Loss / Take Profit system +- Entry Conditions: Long and short trading signals based on Supertrend direction +- Risk Parameters: + - Stop Loss: Configurable, default set to 1.5% of equity + - Take Profit: Configurable, default set to 3% of equity + +#### Backtesting Capabilities +- Full backtesting functionality integrated into the TradingView strategy +- Supports multiple timeframes +- Configurable strategy parameters: + - Strategy ON/OFF toggle + - Supertrend filter toggle + - ATR period (default: 10) + - Supertrend factor (default: 3.0) + +### Evaluation Configuration + +To evaluate the strategy's performance: +1. Open the strategy in TradingView Pine Editor +2. Adjust input parameters as needed +3. Run backtesting to assess strategy performance +4. Analyze trade log and performance metrics + +### Key Evaluation Features +- Visual on/off toggle for strategy visibility +- AI/ML module for identifying potential false signals +- Adaptive trading signals based on market conditions +- Percentage-based equity risk management + +### Limitations and Considerations +- Strategy performance may vary across different market conditions +- Requires careful parameter tuning +- Recommended to conduct extensive backtesting before live trading + +## Inference / How to Use the Model + +### Model Usage in TradingView + +#### Applying the Strategy +1. Open TradingView Pine Editor +2. Copy the entire contents of `VSVTrend.pine` +3. Paste into a new strategy script +4. Apply to your desired chart + +#### Configuration Options +- `show_strategy`: Toggle strategy on/off (default: `true`) +- `use_supertrend`: Enable/disable Supertrend filter (default: `true`) +- `atrPeriod`: Average True Range period (default: `10`) +- `factor`: Supertrend factor (default: `3.0`) +- `sl`: Stop Loss percentage (default: `1.5%`) +- `tp`: Take Profit percentage (default: `3.0%`) + +#### Signal Generation +- Long Entry: When Supertrend direction is positive (green) +- Short Entry: When Supertrend direction is negative (red) +- Trade exits are managed by configurable Take Profit and Stop Loss + +#### Example Usage +```pinescript +// Enable strategy with default settings +strategy("VSVTrend Strategy", overlay=true) +``` + +#### Compatibility +- Works on all timeframes +- Applicable to various financial instruments +- Full backtesting support in TradingView + +#### Recommended Workflow +1. Apply strategy to chart +2. Adjust parameters in inputs +3. Run backtest to validate performance +4. Optimize settings for specific asset + +## Technologies Used + +### Programming Languages +- Pine Script (v5) +- Python + +### Trading and Technical Analysis Libraries +- TradingView Pine Script +- Technical Analysis (ta) Library +- Supertrend Indicator + +### Machine Learning and Data Processing +- Potential use of Python ML libraries (based on `ml/model_train.py` reference) + - Suggested: scikit-learn, pandas, numpy + +### Development and Visualization Tools +- TradingView Strategy Editor +- Pine Script Compiler +- Backtesting Platforms + +### Key Technical Components +- Strategy Framework +- Adaptive Indicators +- Machine Learning Signal Detection +- Equity Percent Trading + +## Project Structure + +The project is structured to support a comprehensive TradingView strategy with machine learning capabilities: + +### Main Components +- `VSVTrend.pine`: The core Pine Script strategy implementation + - Contains the main trading logic + - Implements Supertrend filter + - Provides configurable strategy parameters + - Supports long and short trading conditions + - Includes adaptive stop loss and take profit mechanisms + +### Configuration and Customization +- Strategy can be toggled on/off +- Configurable parameters include: + - Strategy activation + - Supertrend filter usage + - ATR period + - Stop loss and take profit percentages + +### Planned Enhancements +- Machine learning integration for false signal detection +- Potential future expansion of trading strategy + +## Contributing + +We welcome contributions to the VSVTrend Strategy! Whether you're fixing bugs, adding features, or improving documentation, your help is appreciated. + +### How to Contribute + +1. **Fork the Repository** + - Fork the repository to your GitHub account + - Clone your forked repository locally + +2. **Create a Branch** + - Create a new branch for your contribution + - Use a clear and descriptive branch name + ```bash + git checkout -b feature/your-feature-name + ``` + +3. **Make Changes** + - Implement your changes in the Pine Script or Python files + - Ensure code follows existing conventions + - Add comments to explain complex logic + +4. **Testing** + - Test your changes thoroughly in TradingView's strategy tester + - Verify the strategy's performance across different timeframes and assets + - Add or update tests if applicable + +5. **Submit a Pull Request** + - Push your changes to your fork + - Open a pull request with a clear description of your modifications + - Reference any related issues + +### Reporting Issues + +- Use GitHub Issues to report bugs or suggest improvements +- Include detailed information: + - Description of the issue + - Steps to reproduce + - Expected vs. actual behavior + - TradingView chart screenshots (if relevant) + +### Development Setup + +1. Ensure you have: + - TradingView Pine Script editor + - Python 3.x (for ML components) + - Required Python libraries (see `requirements.txt`) + +2. Local testing: + - Use TradingView's strategy tester for Pine Script changes + - Run Python ML scripts with appropriate dataset + +### Code of Conduct + +- Be respectful and constructive +- Focus on improving the trading strategy's accuracy and performance +- Maintain a collaborative and inclusive environment + +### Note on AI/ML Contributions + +Given the strategy's AI/ML false signal detection module, contributions to machine learning components are especially welcome. Improvements in signal detection and model training are highly valued. + +## License + +This project is licensed under the [MIT License](LICENSE). + +### MIT License Overview +The MIT License is a permissive free software license that allows users to: +- Use the software commercially +- Modify the software +- Distribute the software +- Privately use the software + +The only condition is that the original license and copyright notice must be included in any substantial portion of the software. + +For the full license details, please see the [LICENSE](LICENSE) file in the repository. + +## Additional Notes + +### Customization and Configuration + +Users can fine-tune the VSVTrend strategy through several built-in configuration options: + +- **Strategy Toggle**: Use `show_strategy` to enable or disable the entire strategy +- **Supertrend Filter**: `use_supertrend` allows toggling the Supertrend filter on/off +- **ATR Parameters**: + - `atrPeriod`: Configurable Average True Range period (default: 10) + - `factor`: Supertrend calculation factor (default: 3.0) +- **Risk Management**: + - Stop Loss: Configurable percentage (default: 1.5%) + - Take Profit: Configurable percentage (default: 3.0%) + +### Performance Considerations + +- Tested on multiple timeframes +- Designed for flexible trading across different market conditions +- Includes basic AI/ML false signal detection capabilities + +### Potential Improvements + +- Enhance machine learning signal validation +- Implement more advanced risk management techniques +- Add support for additional technical indicators +- Create more comprehensive backtesting scenarios + +### Disclaimer + +This trading strategy is provided for educational and research purposes only. Always: +- Thoroughly backtest before live trading +- Use proper risk management +- Start with paper trading +- Understand that past performance does not guarantee future results \ No newline at end of file