Early detection of insider trading in option markets
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Large Scale Detection of Irregularities in Accounting Data
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
Netprobe: a fast and scalable system for fraud detection in online auction networks
Proceedings of the 16th international conference on World Wide Web
SNARE: a link analytic system for graph labeling and risk detection
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
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How do company insiders trade? Do their trading behaviors differ based on their roles (e.g., CEO vs. CFO)? 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 (SEC). We analyzed 12 million transactions by 370 thousand insiders spanning 1986 to 2012, the largest reported in academia. We explore the temporal and network-centric aspects of the trading behaviors of insiders, and make surprising and counter-intuitive discoveries. We study how the trading behaviors of insiders differ based on their roles in their companies, the transaction types, the company 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 towards these dynamics.