Institutional Options Intelligence Platform 📈

A high-performance, real-time options market intelligence platform designed for quantitative analysis of the National Stock Exchange of India (NSE). This system aggregates live market data, computes advanced derivatives metrics using 12 specialized mathematical engines, and broadcasts actionable intelligence to a sleek, terminal-inspired frontend via WebSockets.

🌟 Key Features

• Real-Time Data Aggregation: Automated background fetching of Option Chains, FII/DII Data, India VIX, Sector Indices, and Market Breadth.
• 12 Quantitative Engines: Comprehensive analysis pipeline including Black-Scholes Greeks, Put-Call Ratio (PCR), Max Pain, Supply/Demand Zones, Sector Rotation, Institutional Flow, Technicals, and a Master Scoring Engine.
• Terminal Aesthetic UI: A clean, monochromatic React dashboard with dynamic UI panels, signal badges, and deterministic formula breakdowns.
• Low-Latency Broadcasting: Built on WebSockets and Redis caching to ensure the frontend reflects market shifts instantly.
• Containerized Architecture: Fully dockerized stack (Node.js backend, React frontend, PostgreSQL, Redis) for seamless deployment.

---

🏗 System Architecture

The platform follows a decoupled architecture, isolating data ingestion, computation, and presentation layers.

graph TD
    subgraph Data Sources
        NSE[NSE India API]
    end

    subgraph Backend - Node.js
        cron((Cron Scheduler))
        fetchers[Data Fetchers]
        cache[(Redis Cache)]
        db[(Postgres DB)]
        
        engines[12 Computation Engines]
        api[Express REST API]
        ws[WebSocket Broadcaster]
    end

    subgraph Frontend - React
        dash[Terminal Dashboard]
        state[Zustand State Store]
    end

    NSE -->|Live Data| fetchers
    cron -->|Trigger| fetchers
    fetchers -->|Raw Data| cache
    fetchers -->|History| db
    cache -->|Context| engines
    engines -->|Processed Signals| ws
    engines -->|Historical Query| api
    
    ws -->|Real-time Updates| state
    api -->|Initial Load| state
    state -->|Render| dash

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⚙️ Computation Pipeline

At the core of the backend is the engine pipeline. Every time new market data is fetched, the payload passes through 12 sequential mathematical engines. Each engine enriches the data payload, culminating in a Master Scoring result.

flowchart LR
    Start([Raw NSE Data]) --> E1(Option Chain & Greeks)
    E1 --> E2(Supply & Demand)
    E2 --> E3(Put-Call Ratio)
    E3 --> E4(Max Pain)
    E4 --> E5(Volatility & VIX)
    E5 --> E6(Market Breadth)
    E6 --> E7(Sector Rotation)
    E7 --> E8(Institutional Flow)
    E8 --> E9(Technical Indicators)
    E9 --> E10(Futures Engine)
    E10 --> E11(Master Scoring)
    E11 --> E12(Market Regime)
    E12 --> End([Final Broadcast Payload])

    style E11 fill:#f9f,stroke:#333,stroke-width:2px
    style E12 fill:#bbf,stroke:#333,stroke-width:2px

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🚀 Getting Started

Prerequisites

• Docker and Docker Compose installed on your system.

1. Clone the Repository

git clone https://github.com/Harsh-Codes-77/Option_Intelligence.git
cd Option_Intelligence

2. Start the Platform

The entire stack (Frontend, Backend API, Redis, and Postgres) can be spun up using Docker Compose.

docker compose up --build -d

3. Access the Services

• Frontend Dashboard: http://localhost:3000
• Backend REST API: http://localhost:3001
• Database: Postgres running on port 5432
• Cache: Redis running on port 6379

To view live logs:

docker compose logs -f

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📂 Project Structure

├── backend/                  # Node.js Express API & Engine logic
│   ├── src/
│   │   ├── engines/          # 12 computational algorithms
│   │   ├── fetchers/         # NSE data scraping and API clients
│   │   ├── routes/           # REST API endpoints
│   │   ├── scheduler/        # Cron jobs for automated fetching
│   │   └── websocket/        # Real-time data broadcasting
│   ├── init.sql              # Database schema initialization
│   └── Dockerfile            # Backend container definition
│
├── frontend/                 # React + Vite UI
│   ├── src/
│   │   ├── components/       # UI components (Panels, Header, Modals)
│   │   ├── hooks/            # Custom React Hooks (useWebSocket)
│   │   ├── store/            # Zustand global state management
│   │   └── App.tsx           # Main application view
│   ├── nginx.conf            # Nginx config for static serving
│   └── Dockerfile            # Frontend container definition
│
├── docker-compose.yml        # Multi-container orchestration
└── README.md                 # Project documentation

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🛠 Technology Stack

Domain	Technology
Frontend	React 18, Vite, TypeScript, Tailwind CSS, Zustand, GSAP
Backend	Node.js, Express, TypeScript, stock-nse-india
Persistence	PostgreSQL
Caching/PubSub	Redis
Containerization	Docker, Docker Compose
Maths/Finance	Custom Black-Scholes Implementation, Standard Deviation algorithms

📝 License

This project is for educational and quantitative research purposes.