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🤖 AI Trading Assistant

An intelligent trading assistant powered by LangChain and GPT-4 that helps you make informed decisions in the Indian stock market, with a focus on F&O trading.

Python Version LangChain License

✨ Features

🎯 Core Capabilities

  • Market Analysis: Real-time analysis of Indian stock market conditions
  • Strategy Generation: Custom F&O strategies based on your investment profile
  • Risk Management: Built-in risk parameters and position sizing
  • Trade Execution: Automated trade execution with proper logging
  • Memory Management: Contextual awareness of past decisions and market conditions

💡 Smart Features

  • Adaptive Learning: Uses past conversations and decisions to improve recommendations
  • Multi-timeframe Analysis: Short-term, medium-term, and long-term strategy generation
  • Risk-Aware: Considers your liquidity needs and risk tolerance
  • Technical Analysis: Advanced indicators and chart pattern recognition
  • News Integration: Real-time market news analysis and impact assessment

🎨 User Interface

  • Interactive Chat: Natural conversation interface for market analysis
  • Visual Analytics: Real-time charts and technical indicators
  • Trading Dashboard: Track your strategies and execution history
  • Configuration Management: Easy customization of trading parameters

🚀 Getting Started

Prerequisites

  • Python 3.9 or higher
  • OpenAI API key
  • NSE credentials (for live market data)

Installation

  1. Clone the repository:
git clone <repository-url>
cd trading-assistant
  1. Install dependencies:
pip install -r requirements.txt
  1. Set up environment variables:
cp .env.example .env
# Edit .env with your API keys and credentials
  1. Configure your investment profile:
cp config_schema.yaml my_config.yaml
# Edit my_config.yaml with your investment preferences

Running the Application

Start the Streamlit interface:

streamlit run app.py

💼 Usage

1. Investment Configuration

Configure your investment profile in config_schema.yaml:

investment_profile:
  total_amount: 1000000  # Total investment amount in INR
  risk_profile: "moderate"  # Options: conservative, moderate, aggressive
  
time_horizons:
  short_term:
    percentage: 30
    liquidity_date: "2024-12-31"
  # ... more configuration options

2. Market Analysis

Ask the assistant about market conditions:

"What's your analysis of NIFTY for the next week considering current volatility?"

3. Strategy Generation

Request trading strategies:

"Generate a hedged F&O strategy for BANKNIFTY with maximum risk of 2%"

4. Trade Execution

Execute strategies with proper risk management:

"Execute the suggested bull call spread on NIFTY with defined parameters"

🏗️ Architecture

Components

  • TradingAgent: Core orchestrator for market analysis and trading
  • MemoryManager: Handles conversation history and trading checkpoints
  • Market Research Tools: Real-time data collection and analysis
  • Strategy Generator: Creates customized trading strategies
  • Trade Executor: Handles order execution and logging

Data Flow

  1. User Input → Natural Language Processing
  2. Market Analysis → Data Collection & Processing
  3. Strategy Generation → Risk Assessment
  4. Trade Execution → Position Management
  5. Memory Storage → Learning & Improvement

📊 Features in Detail

Market Research

  • Technical Analysis (RSI, MACD, Moving Averages)
  • Options Chain Analysis
  • Market News Integration
  • Sentiment Analysis

Strategy Generation

  • F&O Strategies (Spreads, Straddles, Iron Condors)
  • Position Sizing
  • Risk-Reward Calculation
  • Market Regime Adaptation

Risk Management

  • Position Size Limits
  • Stop-Loss Management
  • Portfolio Correlation Analysis
  • Volatility Assessment

🔄 Future Integrations

Planned Features

  • Groww API Integration for automated trading
  • Advanced Portfolio Analytics
  • Machine Learning for Pattern Recognition
  • Real-time Alerts System
  • Performance Attribution Analysis

📝 License

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

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

📧 Support

For support, please open an issue in the GitHub repository or contact the maintainers.

⚠️ Disclaimer

This software is for educational purposes only. Always do your own research and consider consulting with a financial advisor before making investment decisions.

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