Magic, brain and stocks: A lesson in playing the cards right

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A magician asks you to pick a card from a deck of playing cards, and not show it to anyone. Let’s say the card you pick is the seven of diamonds. He then asks you to write down the name of five playing cards on a piece of paper. One of the five should be the card you picked and the other four should be random cards. Once you have that down, the magician looks at the piece of paper for a while.

He then, with unwavering confidence, announces that the card you picked 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 some pressure. Under the pressure of participating in the trick, minute changes tend to occur. Enough practice and it makes for a pretty sweet card trick.

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He then goes on to tell you how banks often hire skilled magicians to help in detecting cheque fraud? Pretty cool, right?

It is, until you realise that all that was a bunch of baloney. Turns out that in most cases, the magician merely used a sleight of hand and forced the card on you. He made you pick the card he wanted you to pick — forcing cards is one of the first things a card magician learns — and the rest was mere acting and storytelling.

A big reason why we instantly fall for the story a magician tells us is due to our desire to listen to stories and find meaning in them. Being innately curious, we are always looking to make sense of the world and in the case of magic, anything that makes some sense is adopted as a potential explanation.

Now the science. Michael Gazzaniga, a professor of psychology at the University of California, Santa Barbara, has worked with patients who have undergone surgery to sever the corpus callosum, which connects the right and left hemispheres of the brain. Severing 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 every moment and creates a story to explain that information.

Gazzaniga calls this region the “interpreter”.

Unfortunately, the interpreter’s job is trying to find any explanation of what it saw rather than fact-check. So it can often come up with nonsensical explanations.

For instance, in the olden days, the area along the Nile was known to be the epicentre of a lot of eye infections. As this was a common problem for the Egyptians, they had to come up with a solution and one such solution was to drip bat blood into one’s eyes. The logic was that as bats can see during the night, they have sharp eyes and their blood had magical powers that would be transferred to humans. This is just one example of the interpreter at work.

While we don’t drip bat blood into our eyes anymore, we still build stories and find illusionary relationships between two things, without testing them. This is a widespread problem, especially in the investing world.

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

You switch on the television and you have a perpetual bear on the news channel explaining how global unrest is impacting the price of the stock. You check the latest sell-side coverage and notice a downgrade in the company’s outlook due to business uncertainty. You come across a technical analyst who is highlighting multiple charts showing a negative outlook for the company. You scroll through Twitter and come across a few contrarians 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 all the data you just gave it is being used to weave a narrative. Crazy, right?

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

  • Garbage in Garbage Out – Our interpreter can only do as well as the data we give it. So if we are consuming a lot of garbage, it’s only natural that our interpreter may throw back the same. The struggle that we as a generation are going to face is to be able to separate the right 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 has explained, playing a sport in which we are already good at is bound to give us an advantage. Our interpreter will automatically be able to filter data better if we are already an expert in the field. Also, having models in our head to explain certain aspects of reality better is bound to come in handy here.
  • Randomness – As Nassim Taleb has often touched upon in the Incerto series, investing is a mixture of skill and randomness. So when we attempt to rationalise every move in the market, our interpreter is bound to occasionally confuse randomness with skill and come to faulty conclusions. After all, “I don’t know” is not something the interpreter is designed to say.
  • Process Documentation – Knowing what data we are largely consuming, what our thoughts were after consuming that data and how our thoughts have evolved over time is almost a superpower in itself. It helps us better refine our own investing process and not fall for hindsight bias.

So, while the magician may still occasionally fool our interpreter, we can definitely try to train our interpreter to not make magic out of the stock market.

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Dhruv Maniyar is Assistant Manager (Research), IIFL AMC)

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