This is a Guest Post by AK of Fallible:

 

Gambler’s Fallacy Explained

On the other side of the coin (pun intended) we have the gambler’s fallacy (also known as the Monte Carlo fallacy).

This is the opposite of recency bias. It occurs when you start believing that because a certain result happened more frequently in the past, there’s a higher probability a different result will occur in the future.

Take the coin flip example again. Someone who flipped heads five times in a row may think the next flip has to be tails because of the 50% probability associated with the game.

This is once again illogical.

Over a large enough sample of trials (which can be performed through a Monte Carlo simulation), the number of heads and tails will be evenly split. But over any individual, shorter stretch, there is no requirement they must show up equally. You can have 100 head flips in a row and yet the probability of the next flip will still be 50% heads, 50% tails. The gambler’s fallacy is thinking the probability of a tails flip has increased based on the previous streak.

Our “buy the dip” example once again shows the dangers of this bias in markets.

The post-QE era was littered with the corpses of fund managers who tried to short the indices. Why’d they do it? It’s because they thought that after working so many times, “buy the dip” had to fail eventually.

“Business cycles only last 5-7 years. It’s due time for the market to correct for real and blow out all these “buy the dip” idiots.”

Again, this is not how it works. As John Maynard Keynes once said:

“The market can stay irrational longer than you can stay solvent.”

As always, stay Fallible out there investors!

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***All content, opinions, and commentary by Fallible is intended for general information and educational purposes only, NOT INVESTMENT ADVICE.