Artikel
Non-parametric statistic for testing cumulative abnormal stock returns
Due to the non-normality of stock returns, nonparametric rank tests are gaining accceptance relative to parametric tests in financial economics event studies. In rank tests, financial assets' multiple day cumulative abnormal returns (CARs) are replaced by cumulated ranks. This paper proposes modifications to the existing approaches to improve robustness to cross-sectional correlation of returns arising from calendar time overlapping event windows. Simulations show that the proposed rank test is well specified in testing CARs and is robust towards both complete and partial overlapping event windows.
- Sprache
-
Englisch
- Erschienen in
-
Journal: Journal of Risk and Financial Management ; ISSN: 1911-8074 ; Volume: 15 ; Year: 2022 ; Issue: 4 ; Pages: 1-13 ; Basel: MDPI
- Klassifikation
-
Wirtschaft
Information and Market Efficiency; Event Studies; Insider Trading
Econometric and Statistical Methods and Methodology: General
Statistical Simulation Methods: General
- Thema
-
finance
economics
event study
clustered event days
cross-sectional correlation
cumulated ranks
rank test
standardized abnormal returns
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Pynnönen, Seppo
- Ereignis
-
Veröffentlichung
- (wer)
-
MDPI
- (wo)
-
Basel
- (wann)
-
2022
- DOI
-
doi:10.3390/jrfm15040149
- Handle
- Letzte Aktualisierung
-
05.01.2028, 11:42 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Artikel
Beteiligte
- Pynnönen, Seppo
- MDPI
Entstanden
- 2022
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