Information Networks

Ken Ahern has posted a new paper, Information Networks: Evidence from Illegal Insider Trading Tips

Abstract: This paper exploits a novel hand collected dataset to provide a comprehensive analysis of the demographics and social relationships behind illegal insider trading networks. I find that the majority of inside traders are connected through family and friendship links and a minority are connected through professional relationships. Traders cluster by age, occupation, gender, and location. Traders earn prodigious returns of about 35% over 21 days, where traders farther from the original source earn lower percentage returns, but higher dollar gains. More broadly, this paper provides some of the first evidence on information networks using direct observations of person-to-person communication.

The paper is really interesting.  There's a ton of data. Let's start with the most important for my purposes: more than 51% of all insider trading tips involve M&A announcements. Ahern had access to the LexisNexi Public Records Database (LNPRD) for his work and was able to give us a look at who inside traders - who have been caught - are:

There are 622 people in the data set. Of these, 162 people are tippers only, 249 are tippees only, 152 are both tippees and tippers, and 59 are original information sources who do not tip anyone else. Table IV presents summary statistics of the people. Across the entire sample, the average age of the people in the sample is 44.1 years old and 9.8% of the people are women. The youngest person is 19 years old and the oldest is 80. The large majority of insiders (92%) are married.

On of the most common occupation among inside traders is top executive with 107 people. Of these, 24 are board members and the rest are officers. There are 55 mid-level corporate managers and 59 lower-level employees in the sample, including 8 secretaries, 11 information technology specialists, and a few nurses, waiters, and a kindergarten teacher. There are 61 people who work in the “sell side” of Wall Street including 13 accountants, 24 attorneys, 4 investment bankers, and 3 sell side analysts. I divide the “buy side” into two groups by rank in investment firms: there are 60 portfolio and hedge fund managers and 65 lower-level buy side analysts and traders. Small business owners and real estate professionals account for 39 people in the sample and 38 people have specialized occupations, including 16 consultants, 13 doctors, and 9 engineers. There are 135 people for which I cannot identify an occupation.

As a final set of summary statistics, I compare inside traders to their neighbors. For the 448 inside traders that I can identify in the LNPRD [date set], I randomly pick a neighbor of the same gender as the insider. Neighbors are literally next-door-neighbors, as I choose the person that lives on the same street as the insider with the street number as close to the insider’s street number as possible. ... Choosing a comparison sample from the same neighborhood and of the same gender helps to control for wealth, age, and occupation, and highlights the remaining differences between insiders and non-insiders. ... 

Insiders are statistically different than their neighbors in many ways. Insiders have a higher likelihood of owning residential real estate, are more likely to be accountants and attorneys, and significantly less likely to be registered as a Democrat, compared to their neighbors. ... [I]nside traders are less likely to declare bankruptcy, but are about twice as likely to have liens and judgments filed against them, compared to their neighbors. ... [I]nsiders are considerably more likely to have a criminal record compared to their neighbors (53.7% versus 12.8%).

And then, there's this: an analysis of the ethnic surnames of the tipper/tippees.  The message?  Inside traders like to keep their tips within their ethnic group or as currency to buy their way into the dominant 'inside' group. 

 

Very interesting paper.  Download it now!

-bjmq