SimTrade ecosystem is designed for modularity, clarity, and interoperability across projects.
Each component has clear functions and can be used independently or flexibly combined to meet different research and trading needs.
Fully open source, supporting community contributions for continuous improvement and optimization.
Modules are designed to call each other and share data, forming a complete closed loop from data processing to strategy execution.
The SimTrade ecosystem consists of four core modules, each focusing on different aspects of financial research and trading.
提供干净、结构化的金融数据，支持历史数据获取、处理和存储。作为整个生态系统的数据源，为SimTradeLab和SimTradeML提供可靠的数据基础。
轻量级、事件驱动的策略回测框架，利用原始数据和模型输出来运行带有动态决策的策略模拟。
用于金融预测和策略集成的机器学习引擎，从SimTradeData训练预测模型以支持交易决策。
SimTradeLab的专属桌面版，提供快速、安全、完全本地化的策略开发、回测、模拟交易与券商端部署环境。无需Python，无需配环境，下载安装即可开始写策略。
How SimTrade ecosystem modules collaborate to form a complete financial simulation and strategy development pipeline.
Strategies written in SimTradeLab can optionally call SimTradeML models to generate trading signals, and SimTradeDesk provides the professional desktop interface for strategy development, backtesting, and broker-side deployment. All four modules together form a complete ecosystem from data ingestion to model training to strategy execution and deployment.
While designed to work together, each module can run independently to meet specific needs. You can use only SimTradeData for data processing, only SimTradeLab for backtesting, only SimTradeML for predictions, or only SimTradeDesk as a standalone desktop solution for strategy development and deployment.
The workflow supports continuous iteration and optimization. Backtesting results can be fed back into model training, improved models can enhance strategy performance, and SimTradeDesk provides the interface for visualizing results and deploying optimized strategies to brokers, forming a complete virtuous cycle.
Key advantages and distinctive capabilities of the SimTrade ecosystem, providing comprehensive support for financial research and trading.
Built on high-quality financial data, supporting multi-source data integration and standardized processing to provide a reliable foundation for decision-making.
Provides comprehensive quantitative analysis tools supporting technical indicator calculation, risk assessment, and performance measurement.
Supports strategy automation execution, reducing human intervention and improving trading efficiency and consistency.
Integrates advanced machine learning algorithms to provide market prediction and pattern recognition capabilities to assist decision-making.
Open API design supporting custom function development and third-party tool integration to meet diverse needs.
Active open-source community continuously improving and extending features, sharing best practices and strategies.
Comprehensive risk management tools supporting risk assessment, backtesting, and monitoring to protect portfolio safety.
Intuitive data visualization tools to help understand market trends, strategy performance, and risk conditions.
Join the SimTrade community, explore modular, open-source financial simulation and strategy development tools to enhance your trading efficiency and decision quality.