Tests for Abnormal Returns in the Presence of Event-Induced Cross-Sectional Correlation
Niklas Ahlgren and
Jan Antell
Journal of Financial Econometrics, 2017, vol. 15, issue 2, 286-301
Abstract:
We introduce a spatial autoregressive model for cross-sectional correlation of abnormal returns. In the model the abnormal returns of firms in the same industry are correlated, whereas the abnormal returns of firms in different industries are uncorrelated. Tests for abnormal returns which are robust to event-induced cross-sectional correlation are proposed. We apply our tests to U.S. stock returns from Bear Stearns’ collapse and Lehman Brothers’ bankruptcy in 2008. We document evidence of event-induced cross-sectional correlation. Simulations show that tests which estimate the cross-sectional correlation from the event period have size close to the nominal level.
Keywords: abnormal return; cross-sectional correlation; event study; spatial autoregressive model (search for similar items in EconPapers)
JEL-codes: C21 C22 G14 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://hdl.handle.net/10.1093/jjfinec/nbw012 (application/pdf)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:oup:jfinec:v:15:y:2017:i:2:p:286-301.
Ordering information: This journal article can be ordered from
https://academic.oup.com/journals
Access Statistics for this article
Journal of Financial Econometrics is currently edited by Allan Timmermann and Fabio Trojani
More articles in Journal of Financial Econometrics from Oxford University Press Oxford University Press, Great Clarendon Street, Oxford OX2 6DP, UK. Contact information at EDIRC.
Bibliographic data for series maintained by Oxford University Press ().