# quant-science/sunday-quant-scientist

A Free Newsletter for Quantitative and Algorithmic Trading, Portfolio Analysis, and Investing

Repository: https://github.com/quant-science/sunday-quant-scientist
Canonical: https://ross.abutalabs.com/products/sunday-quant-scientist
Homepage: https://learn.quantscience.io/quant-scientist-newsletter-register-9614
Language: HTML
License Family: other
Last push: 2025-09-20T20:23:13+00:00

## Health v2 (maintenance only)
Score: 48/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 43, release rhythm 35, longevity 81
- inputs: {"age_days": 1142, "days_push": 347, "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 1817, forks 365 (observed 2026-08-28T04:05:40.115410+00:00)

## What it is
A free weekly newsletter repository covering quantitative and algorithmic trading, portfolio analysis, and investing. It serves as the signup and content hub for the Sunday Quant Scientist newsletter.

## Use cases
- learn quantitative trading strategies
- algorithmic trading newsletter
- portfolio analysis education
- stay updated on quant investing
- free quant finance resources

## When to choose
- you want a free weekly digest of quant trading and investing topics
- you are learning algorithmic trading and portfolio analysis

## When to avoid
- you need runnable trading software or backtesting code
- you want a licensed library or tool rather than educational content

## Facets
- artifact type: learning-resource
- maturity: active
- function: documentation, analytics
- domain: fintech, tutorials, education
- platform: -
- tags: newsletter, quantitative-trading, algorithmic-trading, portfolio-analysis, investing, web-server

## Member repositories
- quant-science/sunday-quant-scientist (main) score 48

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:40.115410+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 2026-08-30T03:20:14.101181+00:00, confidence not recorded.
  - readme: https://github.com/quant-science/sunday-quant-scientist (fetched 2026-08-28T04:05:40.115410+00:00, sha 29b4d740aa86)
  - homepage: https://learn.quantscience.io/quant-scientist-newsletter-register-9614 (fetched 2026-08-29T10:59:15.789871+00:00, sha b2f68c023452)
- Data as of 2026-08-30T08:39:29.467469+00:00.