crseEventStudy: A Robust and Powerful Test of Abnormal Stock Returns in Long-Horizon Event Studies

Based on Dutta et al. (2018) <doi:10.1016/j.jempfin.2018.02.004>, 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) <doi:10.1016/B978-0-444-53265-7.50015-9>. 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) <10.1198/jbes.2010.07136> 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.

Version: 1.0
Depends: R (≥ 3.5)
Imports: methods, stats, sandwich
Suggests: testthat
Published: 2018-11-15
Author: Siegfried Köstlmeier [aut, cre], Seppo Pynnonen [aut]
Maintainer: Siegfried Köstlmeier <siegfried.koestlmeier at gmail.com>
License: BSD_3_clause + file LICENSE
NeedsCompilation: no
In views: Finance
CRAN checks: crseEventStudy results

Downloads:

Reference manual: crseEventStudy.pdf
Package source: crseEventStudy_1.0.tar.gz
Windows binaries: r-devel: crseEventStudy_1.0.zip, r-release: crseEventStudy_1.0.zip, r-oldrel: not available
OS X binaries: r-release: crseEventStudy_1.0.tgz, r-oldrel: not available

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