# 🤖 AutoTrader ### Build Your Own Algorithmic Trading System — From Zero to Production [](LICENSE) [](https://python.org) [](https://react.dev) [](https://nats.io) [](https://docker.com) **An open-source, event-driven algorithmic trading platform designed to be your go-to framework for building, testing, and deploying automated trading strategies.** [Quick Start](#-quick-start) · [Architecture](#-architecture) · [Documentation](#-documentation) · [Contributing](#-contributing) · [Roadmap](#-roadmap) --- ## 🎯 What is AutoTrader? AutoTrader is an **institutional-grade personal trading system** built from the ground up with a focus on: - **Event-driven architecture** — Every trading action (tick, signal, order, fill) flows as an immutable event through NATS - **Low-latency execution** — Designed for the lowest practical latency achievable through retail broker APIs - **Complete observability** — Real-time dashboard with PnL, positions, Greeks, latency analytics, and exposure monitoring - **Strategy experimentation** — Plug in your own strategies with a clean, decoupled interface - **Risk-first design** — Built-in risk engine with drawdown protection, exposure limits, and kill switch - **Historical data accumulation** — Every tick, signal, order, and fill is persisted for backtesting and ML Whether you're a quantitative developer, an algo trading enthusiast, or someone who wants to learn how professional trading systems work — AutoTrader gives you a production-ready foundation to build on. --- ## ✨ Features | Feature | Description | |---------|-------------| | 📊 **Market Data Service** | Real-time tick ingestion via broker WebSocket, normalization, and event publishing | | 🧠 **Strategy Engine** | Pluggable strategy framework with built-in EMA crossover example | | ⚡ **Execution Engine** | Order placement, modification, cancellation, and fill tracking | | 🛡️ **Risk Engine** | Real-time margin checks, exposure limits, drawdown protection, and kill switch | | 📈 **React Dashboard** | Live PnL charts, position management, strategy controls, latency monitoring | | 🔌 **Broker Adapter** | Modular broker integration (currently INDstocks, easily extensible) | | 💾 **Dual Storage** | Redis for hot state + ClickHouse for historical analytics | | 📡 **NATS Messaging** | JetStream-powered event bus with replay capability | | 📉 **Grafana + Prometheus** | Infrastructure and trading metrics monitoring | | 🧾 **Paper Trading** | Full simulation mode for strategy development without risking capital | --- ## 🏗️ Architecture ``` ┌─────────────────────────────────────────────────────────────┐ │ React Dashboard (Vite) │ ├─────────────────────────────────────────────────────────────┤ │ Dashboard API (FastAPI) │ ├─────────────────────────────────────────────────────────────┤ │ Redis (Live State) │ ├─────────────────────────────────────────────────────────────┤ │ NATS (Event Bus) │ ├──────────────┬──────────────┬───────────────┬───────────────┤ │ Market Data │ Strategy │ Risk Engine │ Execution │ │ Service │ Engine │ │ Engine │ ├──────────────┴──────────────┴───────────────┴───────────────┤ │ Broker Adapter │ ├─────────────────────────────────────────────────────────────┤ │ Exchange (NSE / MCX) │ └─────────────────────────────────────────────────────────────┘ │ │ ClickHouse Prometheus (Historical) + Grafana ``` ### Tech Stack | Component | Technology | |-----------|------------| | Strategy Layer | Python 3.12+ | | Event Bus | NATS JetStream | | Live State | Redis 7 | | Historical Storage | ClickHouse | | Dashboard Backend | FastAPI | | Dashboard Frontend | React 18 + Vite | | Monitoring | Prometheus + Grafana | | Containerization | Docker Compose | --- ## 🚀 Quick Start ### Prerequisites - [Docker & Docker Compose](https://docs.docker.com/get-docker/) - [Python 3.12+](https://python.org) - [Node.js 20+](https://nodejs.org) ### 1. Clone & Configure ```bash git clone https://github.com/ertanuj96/AutoTrader.git cd AutoTrader # Copy and configure your environment cp .env.example .env # Edit .env with your broker API credentials ``` ### 2. Start Infrastructure ```bash # Start NATS, Redis, ClickHouse, Prometheus, and Grafana docker-compose up -d ``` ### 3. Start the Trading Core ```bash cd trading-core pip install -e . python -m pts.main ``` ### 4. Start the Dashboard API ```bash cd dashboard-api pip install -e . uvicorn app.main:app --port 8001 ``` ### 5. Start the Dashboard UI ```bash cd dashboard-ui npm install npm run dev ``` Open [http://localhost:5173](http://localhost:5173) to see your trading dashboard. --- ## 📂 Project Structure ``` AutoTrader/ ├── trading-core/ # Core trading engine (Python) │ └── pts/ │ ├── main.py # Async orchestrator — starts all services │ ├── market_data.py # WebSocket tick ingestion & normalization │ ├── strategy_engine.py # Pluggable strategy framework │ ├── risk_engine.py # Risk checks, exposure limits, kill switch │ ├── execution_engine.py# Order lifecycle management │ ├── broker_adapter.py # Broker API abstraction layer │ ├── state_manager.py # Redis state management │ ├── persistence.py # ClickHouse historical storage │ ├── events.py # Canonical event definitions │ ├── config.py # Configuration management │ └── metrics.py # Prometheus metrics │ ├── dashboard-api/ # REST + WebSocket API (FastAPI) │ └── app/ │ ├── main.py # FastAPI app with WebSocket support │ ├── deps.py # Dependency injection │ └── routes/ │ ├── orders.py # Order endpoints │ ├── positions.py # Position endpoints │ ├── strategies.py # Strategy control endpoints │ └── system.py # System health & metrics │ ├── dashboard-ui/ # Real-time trading dashboard (React + Vite) │ └── src/ │ ├── App.jsx # Main dashboard layout │ └── components/ │ ├── Header.jsx # Connection status & branding │ ├── StatsRow.jsx # Key trading metrics │ ├── PnlChart.jsx # Real-time PnL visualization │ ├── StrategyManager.jsx# Strategy start/stop/pause │ ├── PositionsPanel.jsx # Active positions table │ ├── OrderBook.jsx # Order history │ ├── LatencyMonitor.jsx # Execution latency analytics │ └── ExposureGauge.jsx # Portfolio exposure visualization │ ├── platform-docs/ # Architecture & design documents │ ├── PTS-001-Architecture-and-Vision-v0.1.md │ ├── PTS-002-Event-Model-and-Message-Contracts-v0.1.md │ └── PTS-003-Data-Model-and-Storage-Architecture-v0.1.md │ ├── monitoring/ # Observability configuration │ ├── prometheus.yml │ └── grafana/ │ ├── provisioning/ │ └── dashboards/ │ ├── docker-compose.yml # Infrastructure services ├── .env.example # Environment variable template └── .gitignore ``` --- ## 📚 Documentation Detailed design documents are in the [`platform-docs/`](platform-docs/) directory: | Document | Description | |----------|-------------| | [PTS-001](platform-docs/PTS-001-Architecture-and-Vision-v0.1.md) | Architecture & Vision — System overview, design principles, technology choices | | [PTS-002](platform-docs/PTS-002-Event-Model-and-Message-Contracts-v0.1.md) | Event Model — NATS subjects, event envelopes, all message contracts | | [PTS-003](platform-docs/PTS-003-Data-Model-and-Storage-Architecture-v0.1.md) | Data Model — ClickHouse schemas, Redis key design, retention policies | --- ## 🤝 Contributing We welcome contributions from the community! Whether it's fixing bugs, adding strategies, improving documentation, or building new features — every contribution matters. See [CONTRIBUTING.md](CONTRIBUTING.md) for guidelines. ### How to Contribute 1. **Fork** the repository 2. **Create** a feature branch (`git checkout -b feature/amazing-strategy`) 3. **Commit** your changes (`git commit -m 'Add amazing strategy'`) 4. **Push** to the branch (`git push origin feature/amazing-strategy`) 5. **Open** a Pull Request ### Ideas for Contributions - 🧠 New trading strategies (mean reversion, momentum, pairs trading, etc.) - 🔌 Broker adapters for other platforms (Zerodha, Alpaca, Interactive Brokers) - 📊 Additional dashboard components (volatility surface, order flow) - 🧪 Backtesting framework - 📖 Tutorials and documentation - 🐛 Bug fixes and performance improvements --- ## 🗺️ Roadmap ### Phase 1 — Foundation ✅ - [x] Market data ingestion - [x] Single strategy execution - [x] Execution engine - [x] Real-time dashboard - [x] Historical storage (ClickHouse) ### Phase 2 — Multi-Strategy & Risk - [ ] Multi-strategy portfolio management - [ ] Advanced risk engine with position-level controls - [ ] Portfolio-level Greeks aggregation ### Phase 3 — Analytics - [ ] Greeks engine (real-time IV computation) - [ ] Volatility surface visualization - [ ] Slippage and execution quality analysis ### Phase 4 — Backtesting - [ ] Historical event replay from ClickHouse - [ ] Walk-forward testing framework - [ ] Strategy comparison and ranking ### Phase 5 — Intelligence - [ ] Adaptive execution algorithms - [ ] Liquidity-aware order routing - [ ] ML-assisted trade signal ranking --- ## ⚠️ Disclaimer **AutoTrader is for educational and research purposes.** Trading in financial markets involves substantial risk. Past performance is not indicative of future results. Always paper trade first and understand the risks before deploying with real capital. --- ## 📝 License This project is licensed under the MIT License — see the [LICENSE](LICENSE) file for details. ---

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