Skip to main content

Python library providing performance, risk, and distribution metrics for quantitative finance workflows

Project description

Python NumPy Pandas Quant Finance Research Grade

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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

sigmaquant-0.1.3.tar.gz (16.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

sigmaquant-0.1.3-py3-none-any.whl (20.0 kB view details)

Uploaded Python 3

File details

Details for the file sigmaquant-0.1.3.tar.gz.

File metadata

  • Download URL: sigmaquant-0.1.3.tar.gz
  • Upload date:
  • Size: 16.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.15

File hashes

Hashes for sigmaquant-0.1.3.tar.gz
Algorithm Hash digest
SHA256 4bb9acc6cce27335a0f407c1b817d42f983457816fe9bcb271fd4e752e7c0b14
MD5 fc41f432565ca4315716c50bd7bbeeac
BLAKE2b-256 eda5e82245c4c89356694ce6487bfe6a63f4f3799bdc6ce8e5932ae7d6c8535b

See more details on using hashes here.

File details

Details for the file sigmaquant-0.1.3-py3-none-any.whl.

File metadata

  • Download URL: sigmaquant-0.1.3-py3-none-any.whl
  • Upload date:
  • Size: 20.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.15

File hashes

Hashes for sigmaquant-0.1.3-py3-none-any.whl
Algorithm Hash digest
SHA256 822337a33723d63b08aca913bc8f378b450bece6b9512a635ebbe4d9c3f0d9c4
MD5 a12c76fba388ee39ca50df2b88658abe
BLAKE2b-256 2cd1c344f70fb3f7145e7490776c027c4f0a92b9a19593f66961946232a1d946

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page