skoestlmeier/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.

Getting started

Package details

MaintainerSiegfried Köstlmeier <[email protected]>
LicenseBSD_3_clause + file LICENSE
Version1.2
URL https://github.com/skoestlmeier/crseEventStudy
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("skoestlmeier/crseEventStudy")
skoestlmeier/crseEventStudy documentation built on Aug. 21, 2019, 3:26 p.m.