Quantaxis is a quantitative trading framework designed for building, backtesting, and executing automated strategies across global equities, futures, and cryptocurrencies. It integrates an event-driven backtesting engine, a multi-market execution gateway for order routing, and a quantitative data pipeline for ingesting and storing multi-asset market data. The system features a Rust-accelerated financial library that utilizes Apache Arrow for high-performance technical indicator calculation and zero-copy data processing. It provides a containerized infrastructure model designed for orchestrati
tqsdk-python is a quantitative trading SDK and framework designed for developing automated strategies for futures, options, and stocks using Python. It functions as an algorithmic trading engine and financial market data API, providing the tools necessary to backtest strategies, analyze historical data, and execute live trades across multiple brokerage accounts. The project distinguishes itself through a specialized option analytics library that calculates Greeks, implied volatility, and volatility surfaces using the Black-Scholes model. It further supports complex order execution patterns, s
StockSharp is an algorithmic trading platform and quantitative framework used for developing and deploying trading robots across stock, forex, and cryptocurrency markets. It functions as a multi-asset trading gateway and a dedicated development environment for building, debugging, and scheduling automated strategies. The platform includes a visual strategy workflow editor that maps logic blocks to executable code and a simulation engine that replays historical tick data to validate trading logic. It utilizes a plugin-based broker integration system to normalize diverse exchange protocols into
Hikyuu is a quantitative trading framework designed for developing, backtesting, and executing systematic trading strategies. It functions as a high-speed system that combines a financial time-series library, a multi-factor analysis tool, and a quantitative backtesting engine to support comprehensive trading research. The framework is distinguished by its high-speed computing core, which utilizes multi-threaded execution to process large volumes of market data for technical indicator generation. It supports a modular strategy composition model where signal, risk, and fund management component
Easyquant is a quantitative trading framework and event-driven engine designed for executing automated trading strategies and managing real-time market data across multiple accounts. It includes an algorithmic strategy engine and a market data integration layer to process stock quotes and order book data from external providers.
Las características principales de shidenggui/easyquant son: Automated Trading Engines, Event-Driven Trading Engines, Algorithmic Trading Engines, Quantitative Trading Platforms, Trading Strategy Backtesters, Trading Strategy Frameworks, Market Data Providers, Event-Driven Architectures.
Las alternativas de código abierto para shidenggui/easyquant incluyen: yutiansut/quantaxis — Quantaxis is a quantitative trading framework designed for building, backtesting, and executing automated strategies… shinnytech/tqsdk-python — tqsdk-python is a quantitative trading SDK and framework designed for developing automated strategies for futures,… stocksharp/stocksharp — StockSharp is an algorithmic trading platform and quantitative framework used for developing and deploying trading… fasiondog/hikyuu — Hikyuu is a quantitative trading framework designed for developing, backtesting, and executing systematic trading… ai4finance-foundation/finrl — FinRL is a reinforcement learning framework designed for the development, training, and backtesting of automated… llmquant/quant-wiki — quant-wiki is a comprehensive knowledge base and structured reference for quantitative finance, financial engineering,…