TradeMint is a full-stack MERN trading simulation platform designed to demonstrate how modern brokerage systems handle order execution, portfolio tracking, and brokerage-aware profit calculation.
It focuses on real trading logic and production-style backend architecture, not just UI β making it an internship-ready fintech engineering project.
- JWT httpOnly cookie-based authentication
- Protected frontend & backend routes
- Session restoration via
/auth/me - Secure logout handling
- Buy/Sell order placement workflow
- Holdings & positions tracking
- Order history with execution logic
- User-level portfolio management
Unlike basic dashboards, TradeMint calculates:
β Gross Profit
β Brokerage & exchange charges
β Taxes (GST, STT, etc.)
β Net Profit after charges
This mirrors how real brokerage apps compute returns.
- Real-time portfolio value tracking
- Individual stock P&L
- Investment vs current value comparison
- Exposure monitoring
- Activity tracking
- Performance-focused dashboard design
- Integrated Yahoo Finance API
- Dynamic quote fetching
- Real-time portfolio updates
---## πΈ Platform Screenshots
Entry point showcasing TradeMintβs purpose, architecture focus, and dashboard preview.

Central portfolio dashboard with investment summary, P&L, alerts, and recent activity.

Detailed holdings table with allocation charts and real-time portfolio value tracking.

Buy/sell execution workflow with order history and status tracking.

Execution-level charge breakdown showing net profit after brokerage and taxes.

Portfolio-driven alerts including exposure warnings and performance signals.

Structured documentation explaining platform modules and internal workflows.

High-level system design showing API layers, services, and data flow.

β οΈ Disclaimer TradeMint is an educational trading simulation built for learning and demonstration. It does not execute real trades or provide financial services.
TradeMint applies real-world backend practices:
- In-memory caching for live market prices (performance optimization)
- Zod validation for critical request payloads (orders, authentication)
- Secure cookie-based JWT authentication middleware
- Modular business logic for trade execution & portfolio updates
TradeMint follows a production-style backend structure:
Routes β Controllers β Services β Models β Database
- REST API communication between React and Node.js
- User-level data separation using
userId - MongoDB schemas for Orders, Holdings, Positions
- Middleware-based authentication & request handling
- React.js
- React Router
- Context API
- Bootstrap
- Node.js
- Express.js
- JWT Authentication (httpOnly cookie-based)
- Zod schema validation
- In-memory caching layer
- Middleware-based architecture
- MongoDB + Mongoose
- Git & GitHub
- Postman
- Render (Backend Deployment)
- AWS Amplify (Frontend Hosting)
TradeMint/
β
βββ backend/ # Node.js + Express REST API
βββ dashboard/ # React frontend application
git clone https://github.com/Manideepsainell/TradeMint.git
cd TradeMintcd backend
npm installCreate a .env file:
PORT=8000
MONGO_URI=your_mongodb_connection_string
JWT_SECRET=your_jwt_secret
CLIENT_URL=http://localhost:3000Run backend:
npm startBackend runs on:
π http://localhost:8000
cd ../dashboard
npm install
npm startFrontend runs on:
π http://localhost:3000
POST /api/auth/signupβ RegisterPOST /api/auth/loginβ LoginGET /api/auth/meβ Restore sessionPOST /api/auth/logoutβ Logout
GET /api/ordersGET /api/holdingsGET /api/positionsGET /api/watchlist
Planned production upgrades:
- Advanced trade reports & analytics
- WebSocket-based live price streaming
- Performance monitoring & logging
- Mobile responsiveness improvements
Manideep Sai Nellutla
MERN Stack Developer
π GitHub: https://github.com/Manideepsainell
π LinkedIn: https://linkedin.com/in/manideep-sai-97681a330
β If you found this project interesting, consider giving it a star!