October 2025 Data Release

Overview

LINK TO DATA

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.