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Massachusetts Institute of Technology

Weaponized disclosure : the feedback effect of disclosure externalities

Abstract

dc:description.abstract

Information about one firm has the potential to affect the stock price of another firm. I investigate whether managers recognize this potential and strategically alter their disclosure decisions when doing so is beneficial. Using data on media coverage and merger negotiations, I find that bidders in all-cash mergers originate substantially more negatively (positively)-charged press release articles when the bidders' disclosure content is expected to positively (negatively) co-vary with the targets' value during merger negotiations. This strategy generates a short-lived walk-down in the targets' stock prices during the period when the targets' takeover price is determined, which substantially increases the relative wealth gains realized by bidders. My results demonstrate that the timing and content of disclosures may be biased by firms seeking to manipulate the stock prices of other firms.

Degree

thesis:*
Department dc:contributor.department
Sloan School of Management.
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2017

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Kim, Jinhwan
Advisor dc:contributor.advisor
  • Rodrigo S. Verdi and Eric C. So.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/112021
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/112021

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Kim, Jinhwan. Weaponized disclosure : the feedback effect of disclosure externalities. Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/112021