SentroTrade

An intelligent, full-stack paper trading platform that executes trades based on real-time and historical market sentiment analysis. The system aggregates sentiment signals (using NLP on news and social media) to algorithmically buy and sell assets, offering users a comprehensive dashboard to monitor portfolio health, track AI decision logic, run backtests, and manually intervene when necessary.

• Sentiment Engine: Analyzes real-time news and market sentiment to generate actionable trading signals.
• Algorithmic Trading Engine: Automatically executes paper trades (buy/sell/hold) based on aggregated sentiment scores.
• Backtest Engine: Test sentiment-driven strategies against historical datasets before running them live.
• AI Justification Logs: Transparent tracking of why the algorithm made a specific trade, showing the underlying sentiment triggers.

• Live Tickers & Watchlists: Real-time asset tracking and custom watchlist management.
• Portfolio Analytics: Interactive charts to track paper-portfolio performance over time.
• Manual Trade Overrides: Instantly intervene in the AI's logic to manually execute trades through the UI.

• Frontend: Next.js (React), Tailwind CSS, TypeScript
• Backend: Python, FastAPI, SQLite (Trading Database)
• Infrastructure: Docker, Docker Compose, AWS (Elastic Beanstalk, ECS, EC2)

sentiment-paper-trader/
├── backend/               # Python/FastAPI backend (Sentiment & Trading Engines)
│   ├── sentiment_engine.py # Analyzes text/sentiment to generate signals
│   ├── trading_engine.py   # Executes algorithmic paper trades
│   ├── dataset_manager.py  # Manages backtesting historical data
│   └── main.py             # FastAPI entry point
├── frontend/              # Next.js React frontend dashboard
│   ├── src/components/     # UI components (Charts, Watchlists, Logs)
│   └── app/                # Next.js App Router pages
├── infrastructure/        # AWS Deployment guides & scripts
└── docker-compose.yml     # Local multi-container orchestration

• Docker and Docker Compose installed.
• Alternatively, Node.js (v18+) and Python (3.10+) if running outside of Docker.

The easiest way to get the entire stack (Frontend + Backend) running locally is using Docker Compose.

1. Clone the repository:

   git clone https://github.com/your-username/sentiment-paper-trader.git
   cd sentiment-paper-trader

2. Start the containers:

   docker-compose up -d --build

3. Access the application:

   • Frontend Dashboard: http://localhost:3000
   • Backend API / Swagger Docs: http://localhost:8000/docs

Backend:

cd backend
python -m venv venv
# Windows: venv\Scripts\activate | Mac/Linux: source venv/bin/activate
pip install -r requirements.txt
uvicorn main:app --reload --port 8000

Frontend:

cd frontend
npm install
npm run dev
# The UI will be available at http://localhost:3000

The project is designed to be highly scalable and can be deployed to various cloud providers.

For detailed instructions on deploying this application to Amazon Web Services (AWS) using Elastic Beanstalk, ECS (Fargate), or manual EC2 instances, please see the Infrastructure Deployment Guide.

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