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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01kp78gk401
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dc.contributor.advisorFan, Jianqing
dc.contributor.authorCarney, Trevor
dc.date.accessioned2020-09-30T14:18:17Z-
dc.date.available2020-09-30T14:18:17Z-
dc.date.created2020-05-02
dc.date.issued2020-09-30-
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/dsp01kp78gk401-
dc.description.abstractHedge fund activism activity has risen dramatically since the late 1990s, attracting both large amounts of capital and controversy. Critics often portray activist investors negatively under the assumption they raid companies for short-term profits, leaving the target company without substantial long-term benefits. This study uses hedge fund activist events from 1994 – 2016 to determine characteristics of companies targeted, the short- and long-term impact on share price, and the long-term impact on operating performance as measured by the return on assets. Since most previous work focuses on hedge fund activism in the 1990s and early 2000s, I split the data set into three time periods to analyze the scope and effectiveness of activism over time. Finally, I look at the impact of the target company characteristics on the returns to the target company and shareholders to determine for which types of companies activists can more successfully create value. I find that activism provides a large short-term boost to share price and does not destroy nor create additional value in the long run. Also, while the characteristics of the companies targeted has remained relatively steady over time, the ability of activists to achieve operating improvements has diminished greatly.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.titleA Modern Look at Hedge Fund Activism Performance and the Impact of Target Company Characteristics
dc.typePrinceton University Senior Theses
pu.date.classyear2020
pu.departmentOperations Research and Financial Engineering
pu.pdf.coverpageSeniorThesisCoverPage
pu.contributor.authorid920092075
pu.certificateCenter for Statistics and Machine Learning
Appears in Collections:Operations Research and Financial Engineering, 2000-2020

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