Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/258872 
Year of Publication: 
2022
Citation: 
[Journal:] Journal of Risk and Financial Management [ISSN:] 1911-8074 [Volume:] 15 [Issue:] 4 [Article No.:] 149 [Publisher:] MDPI [Place:] Basel [Year:] 2022 [Pages:] 1-13
Publisher: 
MDPI, Basel
Abstract: 
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.
Subjects: 
finance
economics
event study
clustered event days
cross-sectional correlation
cumulated ranks
rank test
standardized abnormal returns
JEL: 
G14
C10
C15
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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