Robust Inference in Single Firm / Single Event Analyses

60 Pages Posted: 6 Feb 2019 Last revised: 21 Feb 2023

See all articles by Ralf Elsas

Ralf Elsas

Ludwig Maximilian University of Munich (LMU) - Faculty of Business Administration (Munich School of Management)

Daniela Stephanie Schoch

EMLYON Business School; Ludwig Maximilian University of Munich (LMU)

Date Written: November 25, 2022

Abstract

Single firm / single event (SFSE) studies are relevant in corporate finance. Since inference on
abnormal returns in this context necessarily relies on the time series variance of these abnormal
returns, the implied problem of heteroscedasticity is obvious, although hard to solve. We analyze
robust inference in an SFSE setting using Monte Carlo and resampling experiments. Estimation is
biased when the calibration and event period occur in different volatility regimes. We develop a
unique specification test for these structural breaks. The most robust inference is obtained by using
intraday data and a multiplicative component GARCH estimator.

Keywords: Event studies, Inference, Monte Carlo simulation, Volatility, Structural breaks

JEL Classification: C12, C15, G14, K41

Suggested Citation

Elsas, Ralf and Schoch, Daniela Stephanie, Robust Inference in Single Firm / Single Event Analyses (November 25, 2022). Journal of Corporate Finance, Forthcoming, Available at SSRN: https://ssrn.com/abstract=3321221 or http://dx.doi.org/10.2139/ssrn.3321221

Ralf Elsas (Contact Author)

Ludwig Maximilian University of Munich (LMU) - Faculty of Business Administration (Munich School of Management) ( email )

Kaulbachstr. 45
Munich, DE 80539
Germany

Daniela Stephanie Schoch

EMLYON Business School ( email )

23 Avenue Guy de Collongue
Ecully, 69132
France

Ludwig Maximilian University of Munich (LMU) ( email )

Geschwister-Scholl-Platz 1
Munich, DE Bavaria 80539
Germany

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
212
Abstract Views
1,715
Rank
271,331
PlumX Metrics