# OpenSourceAP/CrossSection

Code to accompany our paper Chen and Zimmermann (2020), "Open source cross-sectional asset pricing"

Repository: https://github.com/OpenSourceAP/CrossSection
Canonical: https://ross.abutalabs.com/products/crosssection
Homepage: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3604626
Language: Python
License: GPL-2.0
License Family: copyleft
Topics: asset-pricing, finance, quantitative-finance, reproducible-research, stocks
Last push: 2025-10-22T17:06:47+00:00

## Health v2 (maintenance only)
Score: 49/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 48, release rhythm 21, longevity 100
- inputs: {"age_days": 2308, "days_push": 315, "days_rel": 315, "gap_med": 378, "n_releases_24m": 2}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1034, forks 283 (observed 2026-08-28T04:03:18.557553+00:00)

## What it is
Code and data accompanying Chen and Zimmermann's paper on open source cross-sectional asset pricing. It reproduces dozens of stock-level predictor signals in Python and portfolio constructions in R, with downloadable outputs at openassetpricing.com.

## Use cases
- reproduce cross-sectional asset pricing signals from academic papers
- download stock characteristic data for factor research
- understand how a predictor like BrandInvest is constructed
- build stock portfolios from firm characteristics
- replicate quantitative finance research results

## When to choose
- you need transparent, reproducible implementations of stock return predictors
- you want open-source alternatives to commercial factor libraries
- you're doing academic research on cross-sectional equity returns

## When to avoid
- you need real-time trading infrastructure or backtesting engines
- you lack WRDS access and only need the code rather than the data
- you want a maintained library API rather than research scripts

## Facets
- artifact type: dataset
- maturity: active
- function: data-science, etl, data-generation
- domain: fintech, data-science, analytics
- platform: python, cli
- tags: asset-pricing, quantitative-finance, reproducible-research, stock-signals, wrds, factor-portfolios, r

## Member repositories
- OpenSourceAP/CrossSection (main) score 49

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:18.557553+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 2026-08-30T07:06:30.959276+00:00, confidence not recorded.
  - readme: https://github.com/OpenSourceAP/CrossSection (fetched 2026-08-28T04:03:18.557553+00:00, sha e5cef7f9bf3a)
- Data as of 2026-08-30T08:39:29.467469+00:00.