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Tools for filtering, retrieving, and managing time-indexed data and calendar-based schedules.
Distinguishing note: Focuses on financial market schedules and time-range filtering rather than general database querying.
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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
Retrieves specific market schedules and historical timestamps to ensure accurate timing for financial operations.