ASRQuant: Python framework for auditable quantitative finance research
ASRQuant gives quantitative analysts a single Python library to backtest strategies, run Monte‑Carlo simulations, price derivatives, and perform econometric and machine‑learning analyses with built‑in audit trails. It bundles data ingestion, portfolio optimisation, risk metrics and visualisation, letting researchers move from academic papers to production‑ready code in a few lines. The package targets quants, researchers and developers who need reproducible, transparent finance workflows, and it stands out by integrating auditability and broker‑execution safeguards not commonly found in other libraries.
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