High-Performance Trading Backend in C++

A high-frequency trading (HFT) system built in C++ for ultra-low latency order execution targeting cryptocurrency derivatives markets via Deribit's exchange APIs. Engineered to achieve microsecond-level latency for critical path operations while maintaining robustness under extreme market volatility (10,000+ orders/sec).

📺 Watch the Project Overview: High-Performance Trading Backend Demo

📋 Project Overview

This High-Frequency Trading (HFT) System represents a sophisticated C++ implementation designed for institutional-grade cryptocurrency derivatives trading. The system is built from the ground up to address the unique challenges of modern electronic trading:

🎯 Core Mission

• Ultra-Low Latency: Achieve microsecond-level performance for critical trading operations
• High Throughput: Handle 10,000+ orders per second under extreme market conditions
• Institutional Grade: Provide the reliability and performance expected by professional trading firms
• Real-Time Processing: Deliver sub-millisecond market data and order execution

🏛️ Target Markets

• Spot Trading: Direct cryptocurrency purchases and sales
• Futures Contracts: Leveraged derivatives with sophisticated risk management
• Options Trading: Complex derivative instruments with advanced pricing models
• Cross-Exchange Arbitrage: Multi-venue trading opportunities

🔬 Technical Innovation

• Custom WebSocket Implementation: Built from scratch for maximum performance
• Lock-Free Data Structures: Eliminate contention in high-frequency scenarios
• Hardware-Accelerated Crypto: Leverage Intel AES-NI and ARMv8 crypto instructions
• Zero-Copy Message Processing: Minimize memory allocation overhead

🚀 Performance Characteristics

• Order Placement Latency: <100 microseconds end-to-end
• Market Data Processing: Real-time tick processing with <1ms latency
• Risk Calculation: Sub-millisecond position and PnL updates
• Connection Resilience: Automatic failover and reconnection handling

🚀 Features

• Ultra-Low Latency: Microsecond-level performance for critical trading operations
• Multi-Protocol Support: REST and WebSocket interfaces for order management and real-time market data
• Comprehensive Coverage: Support for spot, futures, and options instruments
• High Throughput: Designed to handle 10,000+ orders per second
• CLI-Based Interface: Command-line tools for trading operations and system management
• Real-Time Market Data: Custom WebSocket server for streaming market information
• Robust Risk Management: Built-in position and risk controls
• Performance Benchmarking: Comprehensive latency testing and optimization tools

🏗️ Architecture Overview

System Flow Diagram

┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│   Client Layer  │    │    API Layer    │    │  Core Engine    │
│                 │    │                 │    │                 │
│ • CLI/GUI       │───▶│ • REST API      │───▶│ • Order Manager │
│ • Algo Engines  │    │ • WebSocket API │    │ • Risk Manager  │
└─────────────────┘    └─────────────────┘    │ • Execution     │
                                              │ • Market Data   │
                                              └─────────────────┘
                                                       │
                                                       ▼
                                              ┌─────────────────┐
                                              │  Event Bus &    │
                                              │    Caches       │
                                              │                 │
                                              │ • In-Memory Bus │
                                              │ • Time-Series   │
                                              └─────────────────┘
                                                       │
                                                       ▼
                                              ┌─────────────────┐
                                              │   Deribit       │
                                              │  Connectivity   │
                                              │                 │
                                              │ • REST Client   │
                                              │ • WebSocket     │
                                              └─────────────────┘

Core Components

1. Client Layer

• CLI/GUI: Interactive user tools for manual trading
• Algo Engines: Automated trading strategies
• Order Submission: HTTP/JSON via REST API or WebSocket

2. API Layer

• REST API Server: Synchronous HTTP requests for order management
• WebSocket API Server: Real-time market data and order updates
• JSON-RPC Parsing: Efficient payload processing

3. Core Engine

• Order Manager: Order validation and routing
• Risk & Position Manager: Real-time PnL and limit enforcement
• Execution Engine: Deribit API integration
• Market Data Distributor: Real-time tick data processing

4. Event Bus & Caches

• In-Memory Event Bus: High-throughput, lock-free pub/sub
• Time-Series Cache: Lock-free ring buffers for recent data

5. Deribit Connectivity

• REST Client: cURL/Boost.Beast for synchronous operations
• WebSocket Client: Boost.Beast/Websocket++ for streaming

📁 Codebase Structure

Frequency_Check_Algo/
├── src/
│   ├── Api.cpp/hpp              # Main interface layer
│   ├── Trader.cpp/hpp           # Trading logic engine
│   ├── main.cpp                 # Application entry point
│   ├── Boost_WebSocket/         # Boost.Asio WebSocket client
│   ├── Custom_WebSocket/        # Custom socket implementation
│   ├── WebSocketpp/             # websocketpp library client
│   ├── interfaces/              # Abstract interfaces
│   ├── market_data/             # Market data handling
│   ├── oms/                     # Order management system
│   ├── risk_management/         # Risk controls
│   └── strategies/              # Trading strategies
├── test/
│   └── test_latency/           # Performance testing
├── CMakeLists.txt              # Build configuration
└── README.md                   # This file

Key Components

✅ Api.hpp & Api.cpp — Main Interface Layer

• Responsibilities: JSON RPC serialization/deserialization
• Features: Client authentication, clean abstraction layer
• Methods: Order placement, cancellation, modification

✅ BSocket.hpp & BSocket.cpp — Boost WebSocket Client

• Technology: Boost.Asio/Beast implementation
• Features: Production-grade error handling, async I/O
• Use Case: Fallback and test environments

✅ Socketpp.hpp & Socketpp.cpp — websocketpp Library Client

• Technology: websocketpp::config::asio_tls_client
• Features: TLS encryption, thread-safe async handling
• Performance: Sub-millisecond latency optimization

✅ Trader.hpp & Trader.cpp — Trading Engine

• Order Management: Place, cancel, modify orders
• Market Data: Order book, positions, open orders
• Integration: API and socket layer coordination

🔧 Performance & Optimization

Latency Optimization

• WebSocket Protocol: RFC 6455 with persistent TCP connections
• Zero-Copy Message Retrieval: Direct in-memory buffer processing
• Condition Variable Wakeup: Immediate thread activation
• Result: Sub-millisecond round-trip latency

Threading & Concurrency

• Mutex-Guarded Queues: Race condition prevention
• Dedicated Worker Threads: I/O decoupling from business logic
• Producer-Consumer Pattern: High-throughput message processing

TLS Performance

• Asynchronous Handshake: Non-blocking TLS setup
• Session Reuse: Connection and TCP session optimization
• Hardware Acceleration: Intel AES-NI and ARMv8 crypto support
• Result: <10% latency overhead with optimized ciphers

Scaling Considerations

• Vertical Scaling: Efficient CPU core utilization
• Horizontal Scaling: Stateless request model for microservices
• Connection Pooling: Extensible for high-load scenarios

🧪 Testing & Benchmarking

Performance Testing Suite

Located in test/test_latency/ directory:

• Latency Measurement: Round-trip timing for all operations
• Throughput Testing: Orders per second capacity
• Protocol Comparison: WebSocket++ vs Boost vs Custom implementations
• Async vs Sync: Performance benchmarking of different approaches

Test Results

• WebSocket++: Outperforms Boost Beast implementation
• Async Calls: Better performance than synchronous counterparts
• Latency: Sub-millisecond performance under optimal conditions

🚀 Getting Started

Prerequisites

• C++17 compatible compiler
• CMake 3.10+
• Boost libraries
• OpenSSL development libraries

Building the Project

mkdir build && cd build
cmake ..
make -j$(nproc)

Running Tests

cd test/test_latency
make
./test_latency

🔮 Future Improvements

1. Modular Plugin System

• Purpose: Easy adaptation to multiple data sources
• Implementation: Interface-based architecture with runtime loading
• Benefits: Protocol flexibility (Binance, Kraken, custom APIs)

2. Caching & Batching

• Message Batching: Periodic chunk transmission
• LRU Cache: Response caching with eviction policies
• Benefits: Reduced downstream load and bandwidth

3. AI-Powered Data Filters

• ML Anomaly Detection: Filter abnormal market data
• NLP Intent Recognition: Smart command-based interactions
• Benefits: Intelligent, context-aware backend

📊 Monitoring & Observability

Logging & Metrics

• Structured Logs: JSON format for easy parsing
• Prometheus Integration: Latency, error rate, fill rate metrics
• Audit Trails: Complete order and execution history

Health Monitoring

• Grafana Dashboards: Real-time system performance
• Alertmanager Rules: Automated issue detection
• Key Metrics: Latency spikes, risk breaches, connection drops

🤝 Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

📄 License

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

👨‍💻 Author

Priyanshu Yadav
Final Year BTech ECE
📧 priyanshs.ece@gmail.com

🙏 Acknowledgments

• Deribit: Exchange API integration
• Boost Libraries: High-performance C++ components
• WebSocket++: WebSocket protocol implementation
• Open Source Community: Tools and libraries that made this possible

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For questions about architecture, optimizations, or low-latency C++ design, feel free to reach out!