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OpenFactsheet

Free talks and project announcements

News and events

Join a free online session to see how OpenFactsheet looks past the headline return, or follow what is new in the open-source library.

Invitations

Both sessions are free and online. Registration is handled by each organizer on its own site.

All Day AI speaker card: Andrés Bagnasco, Investment Management Program Director and Professor at UCU Business School. Talk: OpenFactsheet: Compare Investments, Not Marketing Claims. October 22, 2026, 9:30 to 10:00 a.m. ET, Build track, Stage 1. Free virtual event.

Free virtual conference, hosted by All Day AI

OpenFactsheet: Compare Investments, Not Marketing Claims

All Day AI 2026

  • 9:30–10:00 a.m. ET, Build track, Stage 1
  • Online, free registration

A talk in the Build track of All Day AI, a free, live, online conference running all day on October 22. How to compare investments on the same measurements, applied the same way, instead of on the figures each sales pitch chooses to show.

Speaker: Prof. Andrés A. Bagnasco, Investment Management Program Director, UCU Business School

Register free at alldayai.com
Packt free live webinar card: OpenFactsheet: Analyze Investment Risk-Adjusted Performance with Python. Instructor Andrés Bagnasco. November 7, 2026, 10:00 a.m., online. Register free.

Free live webinar, hands-on, hosted by Packt

OpenFactsheet: Analyze Investment Risk-Adjusted Performance with Python

Packt free live webinar

  • 10:00 a.m. ET (US Eastern), online
  • Online, free registration

A hands-on session with the open-source Python library: risk-adjusted measures such as Sharpe, Sortino, Calmar and Omega, drawdowns, recovery and tail risk, and reproducible reports that compare funds, ETFs and strategies on the same terms. Basic Python is recommended. The joining link is sent two days before the session.

Speaker: Prof. Andrés A. Bagnasco, instructor

Register free on Luma

Project news

  • OpenFactsheet 0.1.0a1 public alpha released on PyPI and GitHub

    The open-source Python library is now installable from PyPI as a pre-release. It applies methodology 0.1.0 to 102 measurements, documents its conventions in 36 decision records, and links every result to the page of the reference manual that defines it. Public alpha: interfaces, metrics and documentation may still evolve.

    Install and quick startSource code on GitHub

Press coverage

Articles about OpenFactsheet, the press release and the media kit are in the newsroom.