I analyze the relationship between insider trading outcomes and insiders' information environment within a network. While most existing studies rely on one dimension of commonality (e.g., personal ties, professional ties, geographic proximity) to construct the social network, I document the formation of the institutional investor groups (cliques) that exogenously connect firm-level insiders within the social network. Using difference-in-differences designs examining changes in clique size, I provide empirical evidence on the information dissemination channels within a network in which its members are quasi-randomly selected. Insider transactions in larger cliques exhibit lower abnormal trading profits, higher level of trading frequency, and larger amount of trade size, suggesting information dissemination is increasing in clique size. Then, I provide empirical evidence that the association between the value of information and the information dissemination rate is monotonic, consistent with prior theoretical studies. / Doctor of Philosophy / People communicate and are influenced by other people when they reside in a social network. I analyze how corporate insiders' trading outcomes are influenced by their information environment within a network. Most current research rely on one specific type of connection (e.g., personal relationships, professional relationships, geographic proximity) to build the social network, I provide evidence that firm-level insiders are involuntarily connected by the institutional investor social network (cliques). Using archival study approach, I document that insider transactions in larger cliques exhibit lower abnormal trading profits, higher level of trading frequency, and larger amount of trade size, suggesting information dissemination is increasing in clique size. Then, I provide empirical evidence that the association between the value of information and the information dissemination rate is linear, consistent with prior theoretical studies.
Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/114587 |
Date | 19 April 2023 |
Creators | Zhang, Zhenyu |
Contributors | Business, Accounting and Information Systems, Davidson, Robert H., Lisic, Ling Lei, Tan, Liang, Lowry, Michelle Rene |
Publisher | Virginia Tech |
Source Sets | Virginia Tech Theses and Dissertation |
Language | English |
Detected Language | English |
Type | Dissertation |
Format | ETD, application/pdf |
Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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