It is common to come across SAS or Stata manuals while working on academic empirical finance research. Nonetheless, given the popularity of open-source programming languages such as R, there are fewer resources in R covering popular databases such as CRSP and COMPUSTAT. The aim of this article is to bridge the gap and illustrate how to leverage R in working with both datasets. As an application, we illustrate how to form size-value portfolios with respect to (Fama and French 1993) and study the sensitivity of the results with respect to different inputs. Ultimately, the purpose of the article is to advocate reproducible finance research and contribute to the recent idea of “Open Source Cross-Sectional Asset Pricing”, proposed by Chen and Zimmermann (2020).
Supplementary materials are available in addition to this article. It can be downloaded at RJ-2021-047.zip
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For attribution, please cite this work as
Simaan, "The R Journal: Working with CRSP/COMPUSTAT in R: Reproducible Empirical Asset Pricing", The R Journal, 2021
BibTeX citation
@article{RJ-2021-047,
author = {Simaan, Majeed},
title = {The R Journal: Working with CRSP/COMPUSTAT in R: Reproducible Empirical Asset Pricing},
journal = {The R Journal},
year = {2021},
note = {https://doi.org/10.32614/RJ-2021-047},
doi = {10.32614/RJ-2021-047},
volume = {13},
issue = {1},
issn = {2073-4859},
pages = {426-443}
}