TurboBook is a promising exploration into receiving, analyzing, and exploiting order book imperfections like imbalances and price mishaps using broker WebSockets and C++. The framework focuses on ultra-low latency processing of real-time market data to identify and capitalize on fleeting market opportunities.
- Binance WebSocket Integration: Live cryptocurrency market depth data (BTCUSDT)
- Alpaca WebSocket Integration: Live stock market data with authentication
- Dual-Feed Architecture: Separate applications for crypto and equity markets
- SSL/TLS Support: Secure WebSocket connections with proper SNI configuration
- High-Performance Order Book: Efficient price-level based order book implementation
- Real-Time Updates: Processing of live market depth updates from exchanges
- Order Matching Engine: Built-in matching logic for trade simulation and analysis
- Multi-Symbol Support: Handles different trading instruments simultaneously
- Imbalance Detection: Identifies order book imbalances across price levels
- Volume-Weighted Average Price (VWAP): Calculates VWAP for both bid and ask sides
- Order Flow Analysis: Measures order flow imbalances for market sentiment
- Price Level Analysis: Deep analysis of bid-ask spreads and market depth
- Ultra-Low Latency: Average order processing time of 7.89 microseconds
- High Throughput: Capable of processing 10,000 orders in 78.9 milliseconds
- Real-Time Processing: Live market data processing with microsecond precision
- Efficient Memory Usage: Optimized data structures for minimal memory footprint
mkdir build
cd build
cmake ..
makeThis creates three executables:
turbobook- Main menu and project informationturbobook-binance- Crypto market data analysisturbobook-alpaca- Stock market data analysis
./turbobook-binance- Connects to Binance WebSocket for BTCUSDT
- Collects live market depth data for 60 seconds
- Analyzes order book imbalances and market structure
- No API credentials required
# Set environment variables
export ALPACA_API_KEY=your_api_key
export ALPACA_API_SECRET=your_api_secret
# Run the application
./turbobook-alpaca- Connects to Alpaca WebSocket for AAPL
- Requires valid Alpaca API credentials
- Analyzes stock market microstructure
- Provides real-time equity market insights
./turbobookDisplays available applications and usage instructions.
ALPACA_API_KEY: Your Alpaca API key for stock market dataALPACA_API_SECRET: Your Alpaca API secret for authentication
- Cryptocurrency: Binance BTCUSDT perpetual futures
- Equities: Alpaca AAPL stock quotes and trades
- OrderBook: High-performance order book with price-time priority matching
- OrderBookAnalyzer: Advanced analytics for market microstructure analysis
- BinanceWebSocketClient: Real-time cryptocurrency data feed integration
- AlpacaWebSocketClient: Real-time equity data feed with authentication
- MarketDataFeed: Unified interface for multiple data sources
- WebSocket clients establish secure connections to exchanges
- Real-time market data is parsed and validated
- Order book is updated with live price/volume information
- Analytics engine processes market microstructure
- Imbalances and opportunities are identified and reported
- Boost: Beast (WebSocket), Asio (Networking), Property Tree (JSON)
- OpenSSL: SSL/TLS support for secure connections
- CMake: Build system and dependency management
- C++17 compatible compiler
- macOS, Linux, or Windows
- Stable internet connection for real-time data
- Machine Learning Integration: Implement ML models for pattern recognition
- Advanced Statistical Models: Time series analysis and volatility modeling
- Cross-Market Arbitrage: Identify arbitrage opportunities across exchanges
- Market Making Algorithms: Automated liquidity provision strategies
- Additional Exchanges: Integration with Coinbase, Kraken, FTX, and other major exchanges
- Multi-Asset Support: Forex, commodities, and derivatives market data
- Global Markets: Support for international equity and bond markets
- Alternative Data: Social sentiment and news feed integration
- FPGA Acceleration: Hardware acceleration for ultra-low latency processing
- Kernel Bypass Networking: Direct hardware access for minimal latency
- Memory Pool Optimization: Zero-allocation real-time processing
- Vectorized Computations: SIMD instructions for parallel processing
- Real-Time Risk Monitoring: Position and exposure tracking
- Portfolio Optimization: Modern portfolio theory implementation
- Stress Testing: Monte Carlo simulations for risk assessment
- Compliance Integration: Regulatory reporting and audit trails
- Cloud Infrastructure: Containerized deployment with Kubernetes
- Distributed Processing: Multi-node cluster for high availability
- Real-Time Dashboards: Web-based monitoring and control interfaces
- API Gateway: RESTful API for third-party integrations
- Academic Collaborations: Partnership with financial engineering programs
- Open Source Community: Contribution to quantitative finance ecosystem
- Research Publications: Documentation of findings and methodologies
- Conference Presentations: Sharing insights with the trading community
- Order Processing: 7.89 microseconds average per order
- Throughput: 126,582 orders per second sustained processing
- Memory Efficiency: Sub-megabyte memory footprint for order book
- Network Latency: Direct WebSocket connections with minimal overhead
- Real-Time Analysis: Live imbalance detection with microsecond precision
This project represents ongoing research into market microstructure and algorithmic trading. Contributions, suggestions, and collaborations are welcome from quantitative researchers, algorithmic traders, and C++ developers interested in high-frequency trading systems.
This project is for educational and research purposes. Please ensure compliance with all applicable financial regulations and exchange terms of service when using real market data and trading systems.