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This is a Guest Post by AK of Fallible

AK has been an analyst at long/short equity investment firms, global macro funds, and corporate economics departments. He co-founded Macro Ops and is the host of Fallible.

In this video we’re going to talk about the dangers of algorithmic trading in the stock market. Cathy O’Neil who is a former Wall Street quant made a great video recently that describes what algo’s are. And as it turns out, they’re just opinions embedded in math…

This means they aren’t objective. Whatever opinions the creator has will be expressed in the algorithm itself. The issue here is that people tend to believe that algos in the market are perfect, because it’s pure objective data. But if algo’s express the opinion of the creator, there’s a lot of room for error. In fact, algo’s can heighten that error when it’s trying to optimize.

Cathy makes a very distinct that the creator defines the success of the algo. And that definition is how the creator’s opinions slip in. The creator also curates the data. That has a big effect as well. These things together start having compounding effects as the algorithm gets optimized.

The issue I see with this is how similar all the algos will be. Most algo creators come from schools like MIT and Stanford. So they all think the same. And they all work at similar funds. Which means they look at markets the same way and are likely optimizing for the same thing. That ends up making all the algos do the same thing at the same time. Which can be dangerous!

We already see this in very sell off in the current market. If you watch carefully, you can see that once prices break a certain level in the market, it immediately shoots downward. And that’s because all the algo’s are kicking in with their selling at the same price.

And 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.