Introduction
C++ remains a dominant language in high-frequency trading (HFT) and algorithmic trading due to its performance efficiency. Below is a curated list of top C++ projects for trading systems, optimized for low-latency applications and quantitative finance.
1. InfluxDB
A high-performance time-series database for managing trading metrics and market data.
Key Features:
- Real-time data transformation
- Automated task execution
- OSS version available
👉 Explore InfluxDB for time-series analytics
2. Krypto-trading-bot
A self-hosted crypto trading bot specializing in automated market making.
Use Case: High-frequency arbitrage strategies.
3. Riskfolio-Lib
Portfolio optimization library for strategic asset allocation.
Language: Python/C++ hybrid.
4. EA31337
Multi-strategy Forex trading robot for MetaTrader platforms.
Supports: MT4/MT5.
5. QtBitcoinTrader
Secure client for multi-exchange crypto trading.
Highlight: Cross-platform compatibility.
6. AAT
Event-driven algorithmic trading framework.
Languages: Python (backend), C++ (core).
7. Trade-frame
Library for testing equities/futures strategies with real-time data feeds (IQFeed, Interactive Brokers).
Notifications: Telegram integration.
8. Flox
Modular C++ framework for building customizable trading systems.
Mention: Featured on HN for scalability.
9. Viperfish
Algorithmic trading library focused on low-latency execution.
10. Sbepp
C++ implementation of FIX Simple Binary Encoding for high-speed order messaging.
11. Stock-exchange
Local stock exchange simulator for strategy backtesting.
12. BinanceExtensionCPP
Extension for Binance’s API with enhanced trading functionalities.
13. FSM
State machine for order processing in latency-sensitive environments.
14. Order-warehouse
Persistent storage engine for large-scale order-book data (archived).
FAQs
Q1: Why use C++ for trading systems?
C++ offers unmatched speed and memory control, critical for HFT and real-time data processing.
Q2: Can these projects handle crypto trading?
Yes, projects like Krypto-trading-bot and QtBitcoinTrader are crypto-specific.
Q3: Is Python integration possible?
Libraries like AAT and Riskfolio-Lib support Python wrappers for quantitative analysis.
👉 Discover more about high-performance trading tools
Note: Projects are ranked by GitHub activity and community relevance.