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req.txt
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multimodal-trading-bot/
│
├── README.md # Project documentation
├── requirements.txt # Python package dependencies
├── .env # Environment variables (API keys, secrets)
├── main.py # Entry point of the trading bot
│
├── config/ # Configuration files
│ ├── config.py # Main configuration settings
│ ├── api_config.py # API keys and endpoint configurations
│ └── logging_config.py # Logging configurations
│
├── data/ # Data handling and storage
│ ├── data_fetcher.py # Scripts to fetch market data
│ ├── data_processor.py # Scripts to process and analyze data
│ └── historical_data.csv # Sample historical data (for testing)
│
├── strategies/ # Trading strategies
│ ├── base_strategy.py # Base class for trading strategies
│ ├── futures_strategy.py # Specific strategy for futures trading
│ └── options_strategy.py # Specific strategy for options trading
│
├── models/ # AI models and integration
│ ├── chatgpt_integration.py # ChatGPT API integration
│ └── sentiment_analysis.py # Sentiment analysis model
│
├── utils/ # Utility functions
│ ├── logger.py # Custom logger setup
│ ├── notifier.py # Notification utilities (email/SMS alerts)
│ └── backtest.py # Backtesting utilities
│
├── websocket/ # WebSocket management
│ ├── websocket_client.py # WebSocket client implementation
│ ├── market_data_handler.py # Handling incoming market data
│ └── order_execution.py # Order execution logic
│
└── tests/ # Unit tests
├── test_data_fetcher.py # Tests for data fetching
├── test_strategies.py # Tests for trading strategies
└── test_websocket.py # Tests for WebSocket functionality
Certainly! Below are the detailed requirements for the multimodal trading bot project, covering all necessary aspects from high-level goals to specific functionalities and components.
### Project Requirements Document
---
**Project Title:** Multimodal Trading Bot for Futures and Options on NSE
**Objective:**
To develop a fully automated trading bot capable of trading futures and options in the National Stock Exchange (NSE) using the Dhan API for market data and order execution. The bot will incorporate real-time data processing via WebSockets and leverage AI capabilities using the ChatGPT API for enhanced decision-making.
---
### Functional Requirements
1. **User Authentication:**
- The bot should allow secure authentication using Dhan API credentials.
- Users should provide their API keys and secrets through a secure `.env` file.
2. **Market Data Fetching:**
- The bot will connect to the Dhan WebSocket API to fetch real-time market data for NSE futures and options.
- The system should handle reconnections and error management for WebSocket connections.
- It will log incoming data for further analysis.
3. **Data Processing:**
- Incoming market data will be processed to extract relevant information (price, volume, open interest, etc.).
- The system will include a data processor module that handles data transformations and prepares it for analysis.
4. **Trading Strategies:**
- The bot will support multiple trading strategies, which can be defined in separate strategy modules.
- Strategies should be customizable and allow for:
- Trend analysis
- Technical indicators (e.g., RSI, Moving Averages)
- Options pricing models (e.g., Black-Scholes)
- Each strategy will provide buy/sell signals based on defined parameters.
5. **AI Integration:**
- The bot will integrate with the ChatGPT API to analyze sentiment from news articles and social media related to NSE stocks.
- The AI module will return insights that can inform trading decisions, such as predicting market movements based on sentiment.
6. **Order Execution:**
- The bot will execute buy/sell orders using the Dhan API based on trading signals from the strategies.
- It will implement risk management features, such as stop-loss and take-profit orders.
- The system should confirm order execution and handle errors appropriately.
7. **Backtesting:**
- Implement a backtesting module to evaluate trading strategies using historical data.
- Users should be able to specify time frames and parameters for backtesting.
- The system will provide performance metrics (e.g., win/loss ratio, Sharpe ratio).
8. **Notification System:**
- The bot will send notifications via email or SMS regarding important events, such as order executions, strategy performance, or errors.
- Users should be able to configure notification preferences.
9. **Logging and Monitoring:**
- Implement a logging system to record all actions, errors, and performance metrics.
- The bot should provide monitoring capabilities, allowing users to check the status of trades and strategies.
10. **User Interface (Optional):**
- A simple web interface (using Flask or FastAPI) can be developed for users to:
- View real-time performance metrics.
- Monitor open positions and trading history.
- Adjust strategy parameters and settings.
---
### Non-Functional Requirements
1. **Performance:**
- The bot should be able to process real-time market data with minimal latency.
- Order execution must occur within milliseconds of a signal being generated.
2. **Scalability:**
- The architecture should be designed to accommodate additional trading strategies and assets in the future.
3. **Security:**
- User data and API keys must be stored securely.
- Implement best practices for secure API communication.
4. **Testing:**
- Comprehensive unit tests should be implemented for all modules to ensure reliability.
- The system must undergo integration testing to verify interactions between components.
5. **Documentation:**
- All code should be documented with clear comments and usage instructions.
- A user guide should be created to help users set up and operate the bot.
---
### Milestones and Deliverables
1. **Week 1:**
- Setup project structure and environment.
- Implement user authentication and WebSocket connection.
2. **Week 2:**
- Develop the market data fetching and processing modules.
- Implement initial trading strategies.
3. **Week 3:**
- Integrate ChatGPT API for sentiment analysis.
- Implement order execution logic.
4. **Week 4:**
- Develop backtesting module and implement logging system.
- Start testing and bug fixing.
5. **Week 5:**
- Finalize documentation and user guide.
- Conduct final testing and deploy the bot.
---
### Conclusion
This project aims to build a sophisticated trading bot that leverages both real-time market data and AI insights to make informed trading decisions in the NSE futures and options market. Following this structured approach will help ensure a comprehensive and effective development process.
---
Let me know if you'd like to proceed with implementing any specific sections or if you need help with any part of this project!
1. **Expand AI Capabilities:**
- Consider integrating additional AI models for better market prediction and sentiment analysis. Models like BERT or financial-specific models could provide deeper insights.
2. **Enhance Security Measures:**
- Implement two-factor authentication for user access.
- Use encryption for sensitive data both at rest and during transmission.
3. **Improve User Interface:**
- Develop a more robust web interface for easier interaction with the bot. Include features like drag-and-drop strategy configuration and real-time data visualization.
4. **Diversify Data Sources:**
- Integrate more diverse data sources for sentiment analysis, such as financial news feeds, social media platforms, and market reports.
5. **Optimize Performance:**
- Use asynchronous programming to handle data processing and API calls more efficiently, reducing latency.
6. **Add More Testing:**
- Implement stress testing to ensure the bot performs well under high data loads.
- Include user acceptance testing to gather feedback from real users.
7. **Expand Strategy Portfolio:**
- Explore machine learning-based strategies that can adapt and evolve with market conditions for better performance over time.
8. **Include More KPIs:**
- Track additional key performance indicators (KPIs) such as maximum drawdown, ROI, and volatility measures to better assess strategy performance.
9. **Leverage Cloud Services:**
- Consider using cloud services for data storage and processing power to enhance scalability and reliability.
10. **Community Feedback:**
- Set up a forum or community portal for users to share their experiences and provide feedback on the trading bot's performance.