Python library providing performance, risk, and distribution metrics for quantitative finance workflows
Project description
Research-Grade Performance & Risk Metrics
Statistically consistent analytics for quantitative finance
sigmaquant is a lightweight Python library providing performance, risk, and distribution metrics for quantitative finance workflows.
📦 Installation (PyPI Package)
Install the package from PyPI:
pip install sigma-quant
📘Documentation
This README is intentionally high-level.
For the complete API reference, mathematical definitions, statistical conventions, and usage examples, please refer to the official documentation:
https://sigma-quant.readthedocs.io/en/latest/index.html
ASCII Report
Generate a fast portfolio performance report using ascii_report.
If the input series represents PnL, set kind="pnl" and optionally
specify the currency.
import sigmaquant
report = sigmaquant.ascii_report(
returns=portfolio_returns,
frequency="D",
strategy_name="My Portfolio",
kind="simple",
)
print(report)
# Optional exports
df = report.to_dataframe()
data = report.to_dict()
🪪 License
MIT © 2025 — Developed with ❤️ by Lorenzo Santarsieri & Tommaso Grandi
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