TY - JOUR
T1 - Working with CRSP/COMPUSTAT in R
T2 - Reproducible Empirical Asset Pricing
AU - Simaan, Majeed
N1 - Publisher Copyright:
© 2021. All Rights Reserved.
PY - 2021
Y1 - 2021
N2 - 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).
AB - 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).
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U2 - 10.32614/rj-2021-047
DO - 10.32614/rj-2021-047
M3 - Article
AN - SCOPUS:85114354178
VL - 13
SP - 426
EP - 443
JO - R Journal
JF - R Journal
IS - 1
ER -