Enigma_24 Hack

AI-Based Stock Trading for Indian Markets

Project Overview

This project leverages AI and advanced analytical techniques to enhance stock trading strategies for Indian stocks listed on NSE and BSE. It combines sentiment analysis, price prediction, technical indicators, and chatbot recommendations to enable informed intraday and swing trading decisions.

Features

Sentiment Analysis

• News Sentiment Analysis: Analyzes real-time news to derive sentiment scores for stocks listed in NSE and BSE.
• Global and Indian Market Trends: Performs sentiment analysis on global and domestic market trends to assess market behavior.

Price Prediction

• LSTM Forecasting: Utilizes LSTM models for accurate price predictions, aiding traders in making data-driven decisions.

Trend and Risk Assessment

• RFA (Random Forest Algorithm): Evaluates market trends and assesses risk levels, enabling strategic decision-making.

Buy/Sell Recommendations

• Technical Indicators: Generates buy/sell tickers for both intraday and swing trading strategies using advanced technical indicators.

Recommendation Justification

• RAG-Based Chatbot: Implements a Retrieval-Augmented Generation chatbot to provide recommendation justifications and trading summaries, ensuring transparency and confidence in decisions.

Installation

1. Clone the Repository:

   git clone https://github.com/ShamanthHiremath/Enigma_24.git

2. Navigate to the Project Directory:

   cd 

3. Install Dependencies:

   pip install -r requirements.txt

4. Set Up API Keys:
   • Obtain API keys for necessary services (e.g., news sentiment analysis, stock data).
   • Add them to the .env file in the project directory.

Usage

1. Run the Application:

   python main.py

2. Interact with the Chatbot: Use the chatbot interface for real-time recommendations and justifications.
3. View Buy/Sell Recommendations: Access generated tickers and sentiment scores from the dashboard.

Technologies Used

• Machine Learning: Random Forest, LSTM
• Natural Language Processing: Sentiment Analysis
• Technical Indicators: RSI, MACD, Bollinger Bands, EMA, etc.
• Chatbot Framework: Retrieval-Augmented Generation (RAG)

Future Enhancements

• Integration with Trading Platforms: Automate trades based on AI-generated recommendations.
• Multi-Market Support: Expand coverage to global markets.
• Enhanced Sentiment Sources: Incorporate social media analysis.

Contributing

Contributions are welcome! Please follow these steps:

1. Fork the repository.
2. Create a feature branch (git checkout -b feature-name).
3. Commit your changes (git commit -m 'Add feature-name').
4. Push to the branch (git push origin feature-name).
5. Create a pull request.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Contact

For queries or feedback, please reach out:

• Email: your-email@example.com
• LinkedIn: Shamanth M Hiremath
• GitHub: Shamanth Hiremath

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Happy Trading! 📈