EventStudy: Event Study Analysis

Financial event study analysis. Implements the classical event study methodology of MacKinlay (1997) <https://www.jstor.org/stable/2729691> with multiple return models: market model, market adjusted, comparison period mean adjusted, Fama and French three-factor (1993) <doi:10.1016/0304-405X(93)90023-5> and five-factor (2015) <doi:10.1016/j.jfineco.2014.10.010>, Carhart (1997) four-factor <doi:10.1111/j.1540-6261.1997.tb03808.x>, generalized autoregressive conditional heteroskedasticity (GARCH; Bollerslev, 1986) <doi:10.1016/0304-4076(86)90063-1>, rolling window, and dynamic conditional correlation GARCH (DCC-GARCH; Engle, 2002) <doi:10.1198/073500102288618487>. Provides parametric and non-parametric test statistics, including the standardized cross-sectional test of Boehmer, Musumeci and Poulsen (1991) <doi:10.1016/0304-405X(91)90032-F> and its cross-correlation adjustment by Kolari and Pynnonen (2010) <doi:10.1093/rfs/hhq072>; buy-and-hold abnormal returns (Barber and Lyon, 1997) <doi:10.1016/S0304-405X(96)00890-2>; volume and volatility event studies; cross-sectional regression; intraday event studies; panel difference-in-differences event studies with the estimators of Callaway and Sant'Anna (2021) <doi:10.1016/j.jeconom.2020.12.001>, de Chaisemartin and D'Haultfoeuille (2020) <doi:10.1257/aer.20181169>, and Borusyak, Jaravel and Spiess (2024) <doi:10.1093/restud/rdae007>; synthetic control methods (Abadie, Diamond and Hainmueller, 2010) <doi:10.1198/jasa.2009.ap08746>; wild bootstrap inference; multiple testing corrections; power analysis via simulation; data download helpers; automated reporting; and visualization tools. Results can be exported to comma-separated values (CSV), 'Excel', or 'LaTeX'.

Version:	0.66.0
Depends:	R (≥ 4.1.0)
Imports:	R6, distributional, methods, plotly, tibble, ggplot2, dplyr, purrr, tidyr, stringr, rlang, stats, tools, utils
Suggests:	testthat (≥ 3.0.0), withr, lifecycle, generics, gridExtra, knitr, rmarkdown, openxlsx, rugarch, sandwich, covr, rmgarch, quadprog, callr, did, DIDmultiplegt, didimputation, tidyquant, quantmod, zoo, httr2 (≥ 1.0.0), jsonlite, tinytex, tinytable, ragg
Published:	2026-10-21
DOI:	10.32614/CRAN.package.EventStudy
Author:	Simon Mueller [cre, aut]
Maintainer:	Simon Mueller <sm at data-zoo.de>
BugReports:	https://github.com/sipemu/eventstudy/issues
License:	AGPL-3
URL:	https://github.com/sipemu/eventstudy, https://sipemu.github.io/eventstudy/
NeedsCompilation:	no
Citation:	EventStudy citation info
Materials:	NEWS
CRAN checks:	EventStudy results

Documentation:

Reference manual:

EventStudy.html , EventStudy.pdf

Vignettes:

The Grounded AI Advisor: A Dieselgate Multi-Automaker Walkthrough (source, R code) Automated Reports (source, R code) Cross-Sectional Analysis (source, R code) Creating Custom Models (source, R code) Creating Custom Test Statistics (source, R code) Downloading Stock and Factor Data (source, R code) Diagnostics and Validation (source, R code) Factor Models, GARCH, and BHAR (source, R code) Gallery (source) Inference and Robustness (source, R code) Intraday Event Studies (source, R code) Introduction to EventStudy (source, R code) Modern DiD Estimators (source, R code) Panel Event Studies (source, R code) Result Extraction and Export (source, R code) Simulation and Power Analysis (source, R code) Statistical Conventions and Formula Audit (source, R code) Synthetic Control Methods (source, R code) Time-Varying Beta Models (source, R code) Volume and Volatility Event Studies (source, R code)

Downloads:

Package source:	EventStudy_0.66.0.tar.gz
Windows binaries:	r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries:	r-release (arm64): EventStudy_0.66.0.tgz, r-oldrel (arm64): EventStudy_0.66.0.tgz, r-release (x86_64): EventStudy_0.66.0.tgz, r-oldrel (x86_64): EventStudy_0.66.0.tgz
Old sources:	EventStudy archive

Linking:

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