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Tools for modeling and executing complex, multi-level interactions within a controlled environment.
Distinguishing note: Focuses on hierarchical decision simulation rather than general-purpose game or physics engines.
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This project is a comprehensive platform for quantitative investment research, machine learning, and algorithmic trading. It provides an end-to-end environment for developing, testing, and executing financial strategies, supporting the entire lifecycle from data ingestion and feature engineering to model training and backtesting. The system is distinguished by its configuration-driven workflow orchestration, which allows researchers to automate complex pipelines and manage experiments through declarative files. It features a high-performance data infrastructure that utilizes custom binary for
Coordinates daily portfolio management and intraday order execution through a hierarchical simulation model.