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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp015t34sn03g
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dc.contributor.advisorShkolnikov, Mykhaylo-
dc.contributor.authorNoh, Jung Hyun-
dc.date.accessioned2016-07-28T19:29:32Z-
dc.date.available2016-07-28T19:29:32Z-
dc.date.created2016-04-12-
dc.date.issued2016-07-28-
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/dsp015t34sn03g-
dc.description.abstractA framework for the stochastic analysis of mergers and acquisitions ("M&A"s) is developed using doubly stochastic intensity models of survival analysis. The main focus of the thesis is on the parametric and the Cox models, although the Aalen and the Cox-Aalen models are utilized to highlight the time-dependent nature of macroeconomic and firm-specific covariates. Following tests used in Duffie (2011), the independence assumption underlying the parametric and the Cox models are rejected, and I provide further analysis on the shape of the hazard function based on nonparametric estimation. The results provide a new framework of understanding the role of the macroeconomic process in driving merger intensity. Empirical results are provided by M&A data spanning the 15-year period between 2000 and 2014 in the consumer and retail industry, as well as a case study on Walt Disney's acquisition of Marvel Entertainment.en_US
dc.format.extent76 pages*
dc.language.isoen_USen_US
dc.titleStochastic Prediction of Mergers and Acquisitionsen_US
dc.typePrinceton University Senior Theses-
pu.date.classyear2016en_US
pu.departmentOperations Research and Financial Engineeringen_US
pu.pdf.coverpageSeniorThesisCoverPage-
dc.rights.accessRightsWalk-in Access. This thesis can only be viewed on computer terminals at the <a href="http://mudd.princeton.edu">Mudd Manuscript Library</a>.-
Appears in Collections:Operations Research and Financial Engineering, 2000-2020

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