Robust Inference in Single Firm / Single Event-Analyses

52 Pages Posted: 6 Feb 2019 Last revised: 21 Mar 2022

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: February 8, 2022

Abstract

Single firm/single event (SFSE) applications of event studies matter in corporate finance, e.g.,due to their role in securities fraud litigation. Since inference on abnormal returns then has to rely on the time series variance of abnormal returns, the implied problem of heteroscedasticity is obvious but hard to solve. We analyze robust inference in the SFSE setting using Monte Carlo and resampling experiments. Estimation is biased when calibration and event period occur in different volatility regimes. We develop a unique specification test for such structural breaks. Most robust inference results from using intraday data and a multiplicative component GARCH estimator.

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

JEL Classification: G01, G32, K41

Suggested Citation

Elsas, Ralf and Schoch, Daniela Stephanie, Robust Inference in Single Firm / Single Event-Analyses (February 8, 2022). 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

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