Nonparametric Rank Tests in Event Studies with Partially Overlapping Event Windows

Because of non-normality of stock returns nonparametric rank tests are gaining incremental popularity over 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 due to partially 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

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Year of publication:	[2021]
Authors:	Pynnonen, Seppo
Publisher:	[S.l.] : SSRN
Subject:	Nichtparametrisches Verfahren \| Nonparametric statistics \| Ereignisstudie \| Event study \| Schätztheorie \| Estimation theory \| Ankündigungseffekt \| Announcement effect \| Statistische Methodenlehre \| Statistical theory

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