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No Risk No Reward: The Psychology Behind Insider Trading

Let’s try an exercise; I’m going to give you some scenarios and you put them in order, from least to greatest risk to general health and safety:

  1. Going to the Doctor
  2. Living near a Nuclear Power Plant
  3. Driving a Car
  4. Playing with Fireworks
  5. Flying in an Airplane
  6. Shaking something free from a Vending Machine
  7. Swimming in the Ocean during Shark Attack Season

Finished deciding your order?

Based on the number of casualties per year, and ordered least to greatest, here’s the answer:

  1. Living near a Nuclear Power Plant
  2. Swimming in the Ocean during shark attack season
  3. Shaking something from a vending machine
  4. Flying in an Airplane
  5. Setting off Fireworks
  6. Driving a car
  7. Going to the Doctor

How did you do?

Even if you based your decisions on prior knowledge, chances are that your answer might have been in the reverse order.

But why is that?

It’s called perceived risk and it’s what we as humans use in the decision making process. According to a 1990 study, the way we perceive risk is based on 8 separate factors. Based on intuitive heuristics, perceived loss, the situational characteristics, associations with the risk source, credibility in risk-handling agencies, social amplification (media coverage), judgement of others, and familiarity with the risk, our brains determine how risky something is.

If you noticed, numbers and statistics aren’t on that list because to our perception the fact that the only disaster related to nuclear power in the U.S. occurred in 1961 and resulted in 3 death doesn’t matter. We understand that radiation is bad, we understand that there have been reactor core melt downs before, but what we don’t understand is the mindboggling rarity with which melt downs occur.

a study done on trades actioned prior to a specific merger or acquisition determined that roughly 25% of the trades were likely (odds that they arose out of chance are stated to be about 1 in 3 trillion) done based on material non-public information. However, when we compare those trades with the cases that the SEC prosecuted, there’s only a 4.7% overlap.

Taking those previously listed factors into account, and the estimated SEC prosecution rate, we start to get a picture of why people think it’s not a big risk and why they think they’ll get away with it.

Looking at elaborate schemes, like the one run by Ivan Boesky, they all start out with one trade where they didn’t get caught, which in turn altered their intuition. The thought process of “if I can get away with this one, I can get away with it once more” motivates them to do it again. And again. And again, spiraling into a scheme where they are eventually caught purely because they statistically had to.

If we take a look at their perceived risk factors, we see intuition telling them they’ve never been caught before, they’ve done it often so they’re familiar with the risk, and there are others involved thus lowering social judgement. Each of these factors perpetuates the idea of little perceived loss, ultimately exacerbating the notion that they won’t get caught. It’s truly a snowball effect, how we convince ourselves that engaging in risky behavior is ok.

To make matters worse, it doesn’t help that our brains suck at understanding probability.

To most people, flipping a coin means that there’s a 50% chance it’ll land on heads each time, and they’re right but only in each individual case. What we don’t understand is that if we flip the coin multiple times, the odds that it’ll land on heads each time decreases.

Without getting too deep into the math, if we take a coin flip and we want to land on heads twice in a row, mathematically it would take an average of 6 tosses before that would happen. This is because the more you repeat something the more your chances of seeing a specific outcome.

That being said, if we take the probably of the SEC charging you with one case of Insider Trading to be the aforementioned 4.7%, the likelihood that you’ll get caught after 10 trades is about 38%. But after a few more trades say 100 in total, that likelihood jumps to a little over 99%.

When everything is put into this context, you can start to understand the mechanisms behind behaviors such as a trader making risky trades in a portfolio to buying lottery tickets.

Now you might be thinking, “Okay, this is great to know and all but what, if anything, can we do about it?”

Well, if we understand these behaviors and if that study was correct in its conclusion that a quarter of the trades done before an M&A were done on inside information, we can analyze their trading patterns to see if they’re going to do it again.

By looking at and individual’s historical trades, their normal trading pattern, and correlating those with press releases from companies they traded in that significantly affected their stock price, we can start to notice a pattern. If this individual receives an email about groceries from someone right before every trade, then next time they get an email like that we have an opportunity to change their perceived risk through intervention.

With these new techniques, companies will soon be able to capture illicit activity with a higher rate of success than the SEC by analyzing the data at a granular individual-based level.

Of course, it is still possible that the SEC will still be able to identify illicit activity before the company can.

But we probably don’t have to worry about that.

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