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://quant-kit.readthedocs.io/en/stable/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
Metadata
Release files for sigmaquant 0.1.5
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| sigmaquant-0.1.5.tar.gz | 16.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| sigmaquant-0.1.5-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 36.4 kB
Release files / sigmaquant-0.1.5.tar.gz
| Download URL | sigmaquant-0.1.5.tar.gz |
|---|---|
| Size | 16.4 kB |
| Tags | Source |
|
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Release files / sigmaquant-0.1.5-py3-none-any.whl
| Download URL | sigmaquant-0.1.5-py3-none-any.whl |
|---|---|
| Size | 20.0 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.11.15
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