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crseEventStudy
View on CRAN: Click
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Download and install crseEventStudy package within the R console
Install from CRAN:
install.packages("crseEventStudy")
Install from Github:
library("remotes")
install_github("cran/crseEventStudy") Install by package version:
library("remotes")
install_version("crseEventStudy", "1.2.2") Attach the package and use:
library("crseEventStudy")
Maintained by
Siegfried Köstlmeier
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[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-11-15
Latest Update: 2022-02-23
Description:
Based on Dutta et al. (2018) , this package provides their standardized test for abnormal returns in long-horizon event studies. The methods used improve the major weaknesses of size, power, and robustness of long-run statistical tests described in Kothari/Warner (2007) . Abnormal returns are weighted by their statistical precision (i.e., standard deviation), resulting in abnormal standardized returns. This procedure efficiently captures the heteroskedasticity problem. Clustering techniques following Cameron et al. (2011) are adopted for computing cross-sectional correlation robust standard errors. The statistical tests in this package therefore accounts for potential biases arising from returns' cross-sectional correlation, autocorrelation, and volatility clustering without power loss.
How to cite:
Siegfried Köstlmeier (2018). crseEventStudy: A Robust and Powerful Test of Abnormal Stock Returns in Long-Horizon Event Studies. R package version 1.2.2, https://cran.r-project.org/web/packages/crseEventStudy. Accessed 04 Jun. 2026.
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imports, suggests or enhances
Complete documentation for crseEventStudy
Functions, R codes and Examples using
the crseEventStudy R package
Some associated functions: asr . crseEvent . demo_returns . demo_share_repurchases . sar .
Some associated R codes: asr.R . check_data.R . crseEvent.R . sar.R . Full crseEventStudy package functions and examples
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