# quantopian/research_public

Quantitative research and educational materials

Repository: https://github.com/quantopian/research_public
Canonical: https://ross.abutalabs.com/products/research_public
Homepage: https://www.quantopian.com/lectures
Language: Jupyter Notebook
License Family: other
Last push: 2020-11-03T03:33:00+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 4206, "days_push": 2129, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2864, forks 1723 (observed 2026-08-28T04:07:26.533250+00:00)

## What it is
A collection of quantitative finance research projects and lecture notebooks from the Quantopian Lecture Series, written primarily as Jupyter Notebooks. It covers educational material on topics like statistics, portfolio theory, and algorithmic trading strategies.

## Use cases
- learn quantitative finance with python notebooks
- study algorithmic trading lecture series
- educational material on portfolio theory and statistics
- example jupyter notebooks for financial research
- learn factor analysis and risk modeling
- intro to quantitative trading strategies

## When to choose
- you want free, notebook-based tutorials on quant finance concepts
- you are learning python for financial data analysis and backtesting concepts
- you want lecture-style explanations of statistics applied to markets

## When to avoid
- you need maintained, up-to-date code or library dependencies
- you want a production trading platform - Quantopian shut down in 2020
- you need a supported software tool rather than educational material

## Facets
- artifact type: learning-resource
- maturity: abandoned
- function: data-science, machine-learning, math
- domain: fintech, education, data-science, tutorials
- platform: python, cross-platform
- tags: quantitative-finance, jupyter-notebooks, lecture-series, algorithmic-trading, quantopian

## Member repositories
- quantopian/research_public (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:26.533250+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T07:36:15.121907+00:00, confidence not recorded.
  - readme: https://github.com/quantopian/research_public (fetched 2026-08-28T04:07:26.533250+00:00, sha fe1b0ff5df04)
- Data as of 2026-08-30T08:39:29.467469+00:00.