Large-scale insider trading analysis: patterns and discoveries

How do company insiders trade? Do their trading behaviors differ based on their roles (e.g., chief executive officer vs. chief financial officer)? Do those behaviors change over time (e.g., impacted by the 2008 market crash)? Can we identify insiders who have similar trading behaviors? And what does...

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Bibliographic Details
Published in:Social network analysis and mining 2014-12, Vol.4 (1), p.201, Article 201
Main Authors: Tamersoy, Acar, Khalil, Elias, Xie, Bo, Lenkey, Stephen L., Routledge, Bryan R., Chau, Duen Horng, Navathe, Shamkant B.
Format: Article
Language:English
Subjects:
Applications of Graph Theory and Complex Networks
Behavior change
Codes
Computer Science
Data mining
Data Mining and Knowledge Discovery
Datasets
Economics
Game Theory
Humanities
Insider trading
Law
Methodology of the Social Sciences
Original Article
Ownership changes
Policy making
Regulation of financial institutions
Securities markets
Social and Behav. Sciences
Social networks
Statistics for Social Sciences
Time series
Transactions
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Summary:How do company insiders trade? Do their trading behaviors differ based on their roles (e.g., chief executive officer vs. chief financial officer)? Do those behaviors change over time (e.g., impacted by the 2008 market crash)? Can we identify insiders who have similar trading behaviors? And what does that tell us? This work presents the first academic, large-scale exploratory study of insider filings and related data, based on the complete Form 4 fillings from the U.S. Securities and Exchange Commission. We analyze 12 million transactions by 370 thousand insiders spanning 1986–2012, the largest reported in academia. We explore the temporal and network-based aspects of the trading behaviors of insiders, and make surprising and counterintuitive discoveries. We study how the trading behaviors of insiders differ based on their roles in their companies, the types of their transactions, their companies’ sectors, and their relationships with other insiders. Our work raises exciting research questions and opens up many opportunities for future studies. Most importantly, we believe our work could form the basis of novel tools for financial regulators and policymakers to detect illegal insider trading, help them understand the dynamics of the trades, and enable them to adapt their detection strategies toward these dynamics.
ISSN:1869-5450
1869-5469
DOI:10.1007/s13278-014-0201-9