TradeOps Portal 🚀

A comprehensive trading operations dashboard for managing trades, monitoring performance, and tracking reconciliation.

Features

1. Dashboard Overview

• Real-time trading metrics
• Trading activity visualization
• Asset class distribution
• Recent trades monitoring

2. Trade Management

• Create new trades
• Filter and search existing trades
• View trade status and details
• Manage trade lifecycle

3. Analytics

• Trading volume analysis
• Performance metrics
• Asset class distribution
• Trader performance tracking

4. Logs and Monitoring

• Operational logs
• Reconciliation tracking
• System status monitoring
• Error tracking

5. Database Management

• Database statistics
• Data initialization
• Database reset capabilities
• Sample data management

🎯 Motivation

In the fast-paced world of quantitative trading, operational efficiency is crucial. This project emerged from a desire to explore how modern software engineering practices can enhance post-trade operations. By building a simulated environment, we can:

• Understand the complexities of trade reconciliation
• Explore data-driven approaches to operational workflows
• Implement automated solutions for repetitive tasks
• Create intuitive interfaces for complex operations
• Develop robust error handling and logging systems

The project serves as a practical exploration of how technology can improve operational efficiency in trading environments, while providing a hands-on learning experience in full-stack development.

🛠️ Tech Stack

• Backend

  • FastAPI - Modern, fast web framework
  • SQLAlchemy - SQL toolkit and ORM
  • APScheduler - Job scheduling
  • Pydantic - Data validation
  • SQLite/PostgreSQL - Database

• Data Processing

  • Pandas - Data manipulation
  • NumPy - Numerical computing
  • Plotly - Interactive visualizations

• Frontend

  • Streamlit - Interactive dashboard
  • Plotly Express - Data visualization
  • Requests - API communication

🚀 Getting Started

Prerequisites

• Python 3.8+
• pip (Python package manager)
• Git

Installation

1. Clone the repository:

git clone https://github.com/ranjanakarsh/TradeOps.git
cd TradeOps

2. Create and activate a virtual environment:

python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

3. Install dependencies:

pip install -r requirements.txt

4. Set up the database:

# Create database
createdb tradeops

# Initialize database
python -m app.db.init_db

5. Start the application:

# Start FastAPI backend
uvicorn app.main:app --reload

# In a new terminal, start Streamlit frontend
streamlit run app/frontend.py

6. Access the application:

• Backend API: http://localhost:8000
• Frontend Dashboard: http://localhost:8501

📈 Future Enhancements

• Authentication & Authorization

  • Role-based access control
  • Secure API endpoints
  • User management

• Data Management

  • Bulk CSV trade upload
  • Data export functionality
  • Advanced filtering options

• Notifications

  • Email alerts for discrepancies
  • Real-time dashboard updates
  • Custom notification rules

• Advanced Analytics

  • Machine learning for anomaly detection
  • Predictive analytics
  • Custom report builder

📝 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.

📧 Contact

Ranjan Akarsh - Instagram