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Data (October 2025 Release)

Overview

LINK TO DATA

The data is also accessible programmatically via ‘pip install openassetpricing‘ or ‘devtools::install_github(“tomz23/OpenSourceAP.DownloadR”)‘

Note that most of the current data run through December 2024. Predictors based on option-implied volatility currently only run through December 2022 (and are taken from the 2023 release) due to revisions to the underlying data. See the Github issue.

Documentation

  • The current data release is version 2.0.0 (created with the latest code release)
  • This release is the first to use the Python translation for all signals data. We painstakingly validated the translation such that all signals data are either nearly identical to the Stata outputs or are improvements. See Github issue 174.
  • ChNAnalyst, PriceDelayTstat, and Recomm_ShortInterest have major revisions due to bug fixes. Other revisions are small. See release notes for details.
  • Detailed info on the underlying papers and our implementations: Signal Browser or Signal Documentation csv file
    • Includes acronyms, original paper (OP) references, and hand-collected results from the OPs
    • New in 2025: Google Scholar Citation data (from Ivo Welch)
    • Data release notes to help to get an overview of what is available

Featured Portfolio Return Datasets

  • Monthly portfolio returns
    • Monthly long-short returns of 212 predictors following OPs (wide csv)
    • 212 csvs, each has returns for a portfolio sort using a different predictor following OPs (Gdrive folder)
      • Use this link to get, say, 5 long portfolios based on B/M (BM.csv) or the long- and short portfolios based on dividend seasonality (DivSeason.csv)
    • All 212 predictor portfolio sort csvs in a single file (still following OPs)
  • Daily portfolio returns
    • Daily portfolio returns (Gdrive folder)

Featured Stock-level Signal Datasets

  • 209 predictive firm-level characteristics in wide format, signed so future mean returns increase in characteristics (1.6 GB zipped csv)
    • Omits Price, Size, and STreversal, which can be downloaded from CRSP
      • To automate the download of all 212 predictive firm-level characteristics, use the openassetpricing Python package, or the OpenSourceAP.DownloadR R Package, or this self-contained R script.

Previous data releases

See here for previous versions of our datasets (but you likely want to use the most recent one for your work)

  • October 2024 Data Release (v1.4.1)
  • August 2024 Data Release (v1.4.0).
  • August 2023 Data Release (v1.3.0)
  • March 2022 Data Release (v1.2.0)
  • April 2021 Data Release (v1.1.0)
  • March 2021 Data Release (v1.0.0)
  • July 2020 Data Release (v0.1.2)
  • May 2020 Data Release (v0.1.1)

To Download Data

  • Head to the Data tab
  • Use the openassetpricing Python package (by Peng Li)
  • Use the OpenSourceAP.DownloadR R package

Authors

Andrew Y. Chen
Tom Zimmermann

News

2025-10-22: Data update (October 2025)

  • Major code update: Signals translated to Python
  • Various other minor fixes and improvements
  • Head to the data page and our repo for details

2024-10-14: Data update (October 2024)

  • Fixes lookahead bug in AnnouncementReturn
  • All other data same as August 2024 release

2024-08-22: Data update (August 2024)

  • Portfolios updated to end of 2023
  • Various minor fixes and improvements

2023-08-16: Data update (August 2023)

  • Portfolios updated to end of 2022
  • Five additional signals
  • Various minor fixes and improvements

2022-03-30: Data update (March 2022)

  • Portfolios updated to end of 2021
  • Two additional signals
  • 2×3 Fama-French factor style portfolios
The views expressed herein are those of the authors and do not necessarily reflect the position of the Board of Governors of the Federal Reserve or the Federal ReserveSystem.
This project has received support from the Deutsche Forschungsgemeinschaft (DFG) under Germany’s Excellence Strategy EXC2126/139083886.
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