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May 2020 Data Release

Baseline Data

  • 208 firm-level characteristics (1GB)
    • These omit size and price characteristics, which can be downloaded from WRDS.
  • Returns for 210 long-short portfolios

Additional “Test Asset” Portfolios

  • Returns for N portfolios for each predictor based on the original papers
    • For each predictor, we generate 5 portfolios if our benchmark is quintiles, 10 portfolios if our benchmark is deciles, 2 if binary, etc.
  • Returns for 10 portfolios for each non-binary predictor formed by decile sorts.
    • Portfolio weights based on the original papers (typically equal-weighted), all stock breakpoints
    • Value-weighted returns, all stock breakpoints
    • Value-weighted returns, NYSE breakpoints
    • Caution: some predictors are not well-behaved enough to produce deciles

Additional Data for Making the Extended Dataset (Not Recommended)

  • But if you must, here are 104 additional firm-level characteristics that may or may not predict returns (0.7 GB)
  • Here are 1,050 additional portfolios, mostly made by altering the rebalancing frequency of other portfolios.

Data downloads

  • To download data, head to the Data tab
  • Or `pip install openassetpricing` to download via the Python package (by Peng Li)

Authors

Andrew Y. Chen
Tom Zimmermann

News

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

  • Portfolios updated to end of 2023
  • Various minor fixes and improvements
  • Head to the data page and our repo for details

 

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

  • Portfolios updated to end of 2022
  • Five additional signals
  • Various minor fixes and improvements
  • Head to the data page and our repo for details

 

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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