For the past several years, insider trading has been one of the hottest topics in world of corporate and securities law. The controversy that has followed Second Circuit’s December 2014 dismissal of the insider trading convictions of Todd Newman and Anthony Chiasson ensures that insider trading will continue to be a hot topic for some time to come. But beyond the legal issues surrounding the question of what makes or should make trading on inside information illegal are the even more basic questions about insider trading itself, such as: who is sharing information, what type of information is shared, what is the source of the information and how are the people sharing information related to each other?
These questions are examined in an interesting February 5, 2015 article entitled “Information Networks: Evidence from Illegal Insider Trading Tips” (here) by University of Southern California business school professor Kenneth Ahern. Using a compilation of all insider trading cases filed by the SEC and the DoJ between 2009 and 2013, Professor Ahern examined 183 insider trading networks. Because the case documents are highly detailed, Ahern was able to analyze biographical information and the relationships within the trading networks, as well as the information that was shared and the amount and timing of the trades. The information in the database covered 1,139 insider tips involving 465 events, shared among 622 insiders who made an aggregate of $928 million in illegal profits.
Based on his review of the data, Ahern was able to discern a number of characteristics about the information that was shared and how it was shared.
First, he observed that the insiders share information about certain types of corporate events that have a large effect on share prices. Merger-related events accounted for 51% of the insider tips, followed by earnings-related events (26%). Another major category of events involved clinical trial and regulatory announcements (8.0%) or operational news such as CEO turnover (2.8%)
Next, Ahern determined that trading in advance of these events yielded large returns. On average, trading on inside information earns returns of 34.9% over 21.3 trading days. Clinical trial and drug regulatory announcements generate the largest returns, on average, with gains of 101.2% for positive events and -38.6% for negative events, with an average holding period of just 9.2 days. M&A related tips generated average returns of 43.1% in 30.5 days.
The firms involved in the sample tend to be relatively large firms; the average firm involved had market equity of $10 billion and the median firm’s market equity was $1 billion. Ahern speculates that dollar trading volume of larger firms may be attractive for illegal traders because they are less likely to affect the stock price through the trades. The firms involved in the trades tend to be overweighted toward the high-tech industries.
The insider trading networks involve a wide variety of people. The average insider trader is 43 years old and about 10% of the insiders in the data set are women. In order to understand some of the characteristics of the insiders, Ahern looked that the value of the insiders’ homes as a proxy for wealth. He found that the average insider’s home was worth an estimated $1.1 million in September 2014, and the median value was $656,300, which by comparison to national average and median home values led Ahern to conclude that “the inside traders in the sample tend to be among the nation’s wealthiest people.”
Ahern found that the total amount invested per tippee ranges from a minimum of $4,400 up to a maximum of $375 million. The average total amount invested is $4.3 million and the median amount invested is $226,000. Many of the SEC complaints document how some insider traders sell all of the existing assets in their portfolio and borrow money to concentrate their holdings in the target firm. The median inside traders invests an amount worth 39% of his median home values. On the other hand, the trades tend to be highly profitable. The median investor realized gains of $133,000, and the average investor realizes gains of $2.3 million. Per tip, the median investor gains $72,000.
The most common occupation among inside traders is top executive, with 107 people identified in the database. Of these, 24 are board members and the rest are officers.
Ahern then compared the insiders in the dataset to their neighbors, using public databases to identify the insiders’ next door neighbors. Ahern determined that the insiders are different from their neighbors in many ways. Among other things, he determined that the insiders “have a higher likelihood of owning residential real estate, are more likely to be accountants and attorneys, and [are] significantly less likely to be registered as a Democrat, compared to their neighbors.” He also determined that the “insiders are considerably more likely to have a criminal record compared to their neighbors,” which he interpreted to mean that the insider trading activity was “consistent with other patterns of behavior,” adding that “it seems more likely that the insiders have less respect for the rule of law and are more brazen in their illegal activities than their neighbors.”
With respect to the relationships between the tippers and the tippees, Ahern examined the 461 pairs of tippers and tippees in the sample and determined that 22.6% of the relationships were familial, 34.7% are business-related, 35.1% are friendships, and 21.3% do not have any clear relationships. The pairs in this later category tended to be relationships formed through expert networking firms, where insiders are paid consultants to clients in the expert networking firm. Of business associates, about half of the relationships are between a boss and a subordinate or client. Across the whole sample, 74% of pairs of insiders met before college and 19% met during college. Excluding family members, about 43% met during college.
Insiders are connected in other ways as well. Insiders tend to live close to each other. The median distance between a tipper and tippee is 26 miles. Women are more likely to be tipped by other women. Insiders are more likely to share tips with people who share a common surname ancestry. Ahern also found that as information diffuses away from the original source, top executives and mid-level executives are less likely to send or receive tips, and after three degrees of separation, buy-side managers and analysts account for the majority of the information sharing. The first links in a tip chain are more likely to be friends and family, but as the information diffuses further from the source, business links become more prevalent. People further from the source invest larger amounts, make smaller percentage returns, and earn larger dollar gains.
Using information available from public databases, Ahern constructed a broader network of insiders’ family members and associates, in order to test what he called “counterfactual tippees” as a way of investigating why some people received tips and others do not. He found that insiders tend to share information with people that are closer in age and of the same gender, and are less likely to tip family members compared to non-family members. Using the counterfactual database, Ahern also examined the existence of selection bias in the database (which makes sense, since the database is by definition limited to insiders who were caught). Based on his analysis, Ahern concluded that the sample tends to omit infrequent, opportunistic traders who make smaller investments and share information with family or friends, while the sample comprises traders that are more likely to actually impact the share price: wealth CEOs and fund managers who are likely to be in larger networks and invest larger sums.
Ahern’s paper is interesting but it involves aggregate data and generalizations. Those who prefer more narrative flow and more specific detail will want to read the October 2014 New Yorker article entitled “The Empire of Edge” (here), which details the facts surrounding one of the S.A.C. Capital Advisors insider trading prosecutions.
A March 3, 2015 FT Alphaville blog post about Ahern’s paper can be found here.
Special thanks to a loyal reader for sending me a link to Professor Ahern’s paper.