AIQuantLab: a correctness‑first framework for ingesting and validating market data
AIQuantLab tackles the pain of messy market data by providing strict OHLCV contracts, automated CSV normalization, and integrity‑checked Parquet storage. It lets researchers load raw CSVs, run comprehensive quality reports, and persist validated datasets with metadata. Designed for quant analysts and developers building systematic strategies, it offers reproducible pipelines that out‑shine ad‑hoc scripts. Its modular architecture and test suite make it a reliable foundation for hypothesis‑driven finance work.
View on GitHub →cosi12/AIQuantLab