Magic, Brain and Actions: A Lesson in Playing the Cards Right

A magician asks you to choose a card from a deck of playing cards and not show it to anyone. Let’s say the card you choose is the seven of diamonds. He then asks you to write the names of five playing cards on a sheet of paper. One of the five must be your chosen card and the other four must be random cards. Once you have that, the magician stares at the piece of paper for a while.

He then announces, with unwavering confidence, that the card you chose was “seven of diamonds”. Wait, how did he do that?

The magician goes on to explain how our handwriting often tends to differ when we are under pressure. Under the pressure to participate in the round, minute changes tend to occur. Enough practice and it makes for a nice card trick.

He goes on to tell you how banks often hire skilled magicians to help them detect check fraud? Pretty cool, right?

It is, until you realize it was all just a bunch of nonsense. It turns out that in most cases the magician just used a sleight of hand and forced the card from you. He made you choose the card he wanted you to choose – forcing cards is one of the first things a card magician learns – and the rest was acting and storytelling.

A big reason we instantly fall in love with the story a magician tells us is due to our desire to listen to stories and find meaning in them. Being naturally curious, we always seek to make sense of the world and in the case of magic, anything that makes sense is embraced as a potential explanation.

Now science. Michael Gazzaniga, a professor of psychology at the University of California, Santa Barbara, has worked with patients who have had surgery to sever the corpus callosum, which connects the right and left hemispheres of the brain. Cutting it does not allow the two halves of the brain to communicate with each other. Through his experiments with these patients, Gazzaniga concluded that the left hemisphere of our brain includes a special region that interprets the information we receive moment by moment and creates a story to explain this information.

Gazzaniga calls this region “the interpreter”.

Unfortunately, the job of the interpreter is to try to come up with an explanation for what he saw rather than verifying the facts. Thus, he can often come up with absurd explanations.

For example, in ancient times, the area along the Nile was known to be the epicenter of many eye infections. Since this was a common problem for the Egyptians, they had to find a solution and one of those solutions was to pour bat blood into their eyes. The logic was that because bats can see at night, they have sharp eyes and their blood has magical powers that would transfer to humans. This is just one example of the interpreter at work.

Although we no longer drip bat blood in our eyes, we still construct stories and find illusory relationships between two things, without testing them. This is a widespread problem, especially in the investing world.

For example, imagine that the price of a popular stock has suddenly dropped. You are now asking the same question you ask after seeing a cool magic trick: “how or why did this happen?” Instead of a magician’s lies, you are spammed with a myriad of explanations from various sources justifying this price drop.

You turn on the TV and you have a perpetual bear on the news channel explaining how global unrest is impacting stock price. You check the latest sell-side coverage and notice a downward revision to the company’s outlook due to trade uncertainty. You encounter a technical analyst who highlights several charts showing a negative outlook for the company. You scroll through Twitter and come across a few opposites among the largely negative outlook.

Flooded with all this data from multiple sources, your own interpreter is now at work. Remember that the interpreter’s job is to weave a possible story to explain an outcome, and so whatever data you just gave them is used to weave a narrative. Crazy, right?

Just knowing all of this, we couldn’t help but think of four crucial learnings to improve our investment process:

  • Garbage in Garbage Out – Our interpreter can only do as well as the data we give it. So if we consume a lot of garbage, it’s only natural that our interpreter returns the same. The struggle we as a generation will face is being able to separate the good signals from an ocean of noise.
  • Circle of Competence – As we consume more data, it becomes crucial to be able to distinguish between experts and pseudo-experts. As Warren Buffett explained, playing a sport we’re already good at is bound to give us an edge. Our interpreter will automatically be able to better filter the data if we are already an expert in the field. In addition, having models in our head to better explain certain aspects of reality is bound to be useful here.
  • Random – As Nassim Taleb has often talked about in the Incerto series, investing is a mixture of skill and randomness. So when we try to rationalize every move in the market, our interpreter sometimes confuses chance with skill and comes to the wrong conclusions. After all, “I don’t know” is not something the interpreter is supposed to say.
  • Documenting the Process – Knowing what data we largely consume, what our thoughts were after consuming that data, and how our thoughts evolved over time is almost a superpower in itself. This helps us to better refine our own investment process and not fall into the backseat bias.

So, although the magician can still sometimes fool our interpreter, we can certainly try to train our interpreter not to do magic with the stock market.

Dhruv Maniyar is Deputy Director (Research), IIFL AMC)

About Nicole Harmon

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