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Journal of Corporate Finance Vol. 80 2023

Robust inference in single firm/single event analyses

Ralf Elsas1,2; Daniela Stephanie Schoch3

1 Munich Business School · 2 Ludwig-Maximilians-Universität München · 3 École de management de Lyon

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.

DOI
10.1016/j.jcorpfin.2023.102391
Volume
80
Pages
102391
Language
en
Sources
bibtex:phds-export.bib openalex crossref

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