The Causal Heuristic
- Posted by Leigh Drogen
- on June 27th, 2012
Every day we read headlines from financial media publications which attempt to explain why the market was up or down. You may think that these headlines are just to garner pageviews, and often they are dramatized to do that, but the explanation goes much deeper than that. Our brains love to connect cause to effect.
If you have not yet read “Thinking Fast and Slow” by Daniel Kahneman, I implore you to do so. I talk a lot about behavioral psychology, behavioral finance, and behavioral economics, and Kahneman is the foremost scientist in this field. While I do not have any academic background in this field, my professional career has focused in and around learning and exploiting his research to a great extent.
The causal heuristic is an effect of the way our brains are hard wired which attempts to tie cause and effect. This takes place in what Kahneman calls “system 1″, the fast thinking behind the scenes system which you often do not have much active control of. We naturally attempt to pair cause and effect as a result of thousands of years of evolution. If there are tracks on the ground, the antelope must have been here. If the ground is wet, it must have rained.
Building patterns of cause and effect allows us to project into the future, an important skill.
But the natural inclination of our brain to make these connections often leads us astray, especially when we attempt to make sense of larger systems.
Like the stock market.
When a stock drops, your brain’s first inclination is to attach a cause to that event. Our brains do not like ambiguity, they do not like to be stumped, we will jump to conclusions when we don’t have any where near a reasonable amount of information to make them.
And this can be extremely detrimental to your trading. Why? Because if you consistently form causal conclusions which are wrong, or simply have no basis, you will develop patterns in your mind which diverge from reality, putting you at a disadvantage the next time you go to make a decision.
Attempting to attach a cause to a certain market movement is a fools game, a fools game that your brain will always try and play for you. This is why understanding the mood of the market is important, but blocking out the actual news is even more important. How the market reacts to the data is the the only thing you should be concerned with, because the only thing that pays is price.
Attempting to explain the “why” is a useless and harmful endeavor. The “what” is important, it should guide you to making your own conclusions on how it will effect the value of a security in the future, but attempting to explain the “why” of previous price movement is useless.
If you attempt to explain the “why”, you will end up writing headlines in your mind the same way the financial media does. If the Iranians talk tough about closing the straights of Hormuz and oil spikes during the first half of the trading session, the headlines will read “market fears Iranian will pinch oil supply.” And if it then trades down at the end of the day the headlines will read “market doesn’t believe Iran will pinch oil supply.” I’ve seen these headlines on the same exact day. The Iranians did not cause the price of oil to go up or down, but our minds love to connect a cause to an effect, and we love stories. Supply and demand for oil on that day caused the price movement, what went into that supply and demand is irrelevant to us, all we should care about are the patters that the price exhibited, because they give us a road map to potential future movements based on patterns we’ve seen in the past.
The causal heuristic can be very detrimental to your trading, and decision making in general. It’s something we all must struggle against, but with the correct training you can overcome it.
Stop focusing on the “why”, that’s for writers who need pageviews.
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Leigh Drogen is the founder and chief investment officer of Surfview Capital, LLC, a New York based investment management firm employing an intermediate term long/short momentum strategy. More »
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