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Large-scale insider trading analysis: patterns and discoveries

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Abstract

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.

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Notes

  1. Enacted May 23, 2003.

  2. A point identified, with hindsight, as the start of the financial crisis.

  3. The relevant portion of Section 16(b) reads:

    For the purpose of preventing the unfair use of information which may have been obtained by [an insider] by reason of his relationship to the issuer, any profit realized by [an insider] from any purchase and sale, or any sale and purchase, of any equity security of such issuer...within any period of <6 months...shall inure to and be recoverable by the issuer, irrespective of any intention on the part of [the insider] in entering into such transaction of holding the security...purchased or of not repurchasing the security...sold for a period exceeding 6 months. Suit to recover such profit may be instituted...by the issuer, or by the owner of any security of the issuer in the name and in behalf of the issuer if the issuer shall fail or refuse to bring such suit within sixty days after request or shall fail diligently to prosecute the same thereafter[.].

  4. Under Smolowe v. Delendo Corp., 136 F.2d 231 (1943), when calculating the amount of short-swing profit realized by an insider, transactions should be match to reach the maximum possible profit. Chin (1997) claims that a transportation algorithm should be used to compute the maximum possible profit when multiple transactions occur within rolling 6-month windows. Due to the sheer number of transactions, we only consider the consecutive transactions for simplicity.

  5. We take into account the varying number of days in different months to get an accurate value for the number of months between the two transactions in a pair.

  6. The Pearson's product-moment correlation coefficient value of 0.12 indicates positive correlation between profit and number of shares traded (\(p < 0.01\)).

  7. The dollar volume of a stock is a measure of its liquidity on a given day, and it is computed by multiplying the volume of the stock (i.e., total number of shares traded) on a day with the market closing price of the stock on the same day.

  8. The scenarios leading to a ratio >1 are very unrealistic, e.g., on a given day all the trades for a company’s stock should be performed by a single insider; the dataset confirms our belief.

  9. The multiple testing problem arises when testing multiple hypotheses simultaneously. In this setting, the likelihood of observing an erroneous significant result purely by chance increases with the number of tests performed (Witte and Witte 2009).

  10. http://www.crsp.uchicago.edu/.

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Authors and Affiliations

  1. College of Computing, Georgia Institute of Technology, Atlanta, GA, USA

    Acar Tamersoy, Elias Khalil, Bo Xie, Duen Horng Chau & Shamkant B. Navathe

  2. Division of Economic and Risk Analysis, U.S. Securities and Exchange Commission, Washington, DC, USA

    Stephen L. Lenkey

  3. Tepper School of Business, Carnegie Mellon University, Pittsburgh, PA, USA

    Bryan R. Routledge

Authors
  1. Acar Tamersoy
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  2. Elias Khalil
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  3. Bo Xie
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  4. Stephen L. Lenkey
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  5. Bryan R. Routledge
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  6. Duen Horng Chau
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  7. Shamkant B. Navathe
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Correspondence to Acar Tamersoy.

Additional information

This is an extended version of the IEEE/ACM ASONAM 2013 paper “Inside Insider Trading: Patterns & Discoveries from a Large Scale Exploratory Analysis” Tamersoy et al. (2013). The Securities and Exchange Commission, as a matter of policy, disclaims responsibility for any private publication or statement by any of its employees. The views expressed herein are those of the author and do not necessarily reflect the views of the Commission or of the author’s colleagues on the staff of the Commission.

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Tamersoy, A., Khalil, E., Xie, B. et al. Large-scale insider trading analysis: patterns and discoveries. Soc. Netw. Anal. Min. 4, 201 (2014). https://doi.org/10.1007/s13278-014-0201-9

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  • DOI: https://doi.org/10.1007/s13278-014-0201-9

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