AI Stock Trading vs. Human Stock Trading

In this article, we will discuss the differences between AI stock trading and human stock trading. 

If computers can consistently outperform humans in stock trading, they are here to stay. With that said, AI brings different strengths and weaknesses to the table when it comes to trading stocks.

AI Stock Trading and Human Stock Trading — the Differences

Let’s take a look at the major differences between AI stock trading and human stock trading.

Your Algorithm Has the Advantage of No Emotion

When testing your stock trading algorithms, don‘t look towards times of market stability. Test your apps against the most volatile market periods in history and see if the unemotional AI can outperform humans.

Lack of emotion is an obvious advantage for AI-powered traders. Humans are notoriously bad at stock trading for the simple reason that their emotions get the better of them. Stocks plummet and they sell out of panic. Or, just as bad, a stock reaches new highs and prompts greedy investors to buy in at the top.

Dr. Christopher Krauss, chair for Statistics and Econometrics at the School of Business and Economics at Germany’s Friedrich-Alexander-Universität Erlangen-Nürnberg, points out that “Our quantitative algorithms turned out to be particularly effective at such times of high volatility when emotions dominate the markets.”

Computers are ruthless and they don‘t get sad when the markets move in a direction they didn’t predict. Instead, they learn trading rules and practices from experience and use that knowledge to better gauge future market shifts and improve future performance.

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Your App Needs a Fast Kill Switch

Whenever you build any kind of automated trading software, you must include an instantaneous kill switch. Clients need to be able to stop your program upon the first sign of any trouble.

This isn‘t the flashiest feature, but it is one of the most important. Just ask the team at Knight Capital, whose entire business was ruined in less than an hour due to a coding error in July 2012.

The New York Times explains that “as a torrent of faulty trades spewed Wednesday morning from a Knight Capital Group trading program, no one at the firm managed to stop it for more than a half-hour.” 

The glitch was identified within a few minutes, but the firm had failed to build a kill switch into their trading software.

What ensued was a 40+ minute scramble as the entire company pored through the innards of their machine, trying to identify and disable the bogus code. By the time the dust cleared, they had lost more than 400 million dollars and were near bankruptcy.

Humans can make mistakes, but not like that. This kind of crisis is only possible when a machine lurches forward, out of control, spewing money with no regard for what it is doing. Build a fast kill switch to protect against the worst-case scenario of an algorithm malfunction.

The Dangers of the Automated Trading Ecosystem

There are other safeguards to consider. When your stock trading algorithm interacts with other algorithms, what will happen? Will it know how to defend itself from irrational or deceitful algorithms elsewhere in the market?

The “flash crash” of 2010 is an example of unexpected emergent properties from AI-powered trading creating havoc in the markets. A single unusual trade from a poorly calibrated machine set off a chain reaction of bizarre computerized trades, sending the market into a tailspin for no real reason.

As the Wall Street Journal puts it, the federal regulators “pinpointed one trade by a mutual fund company as a key contributing factor to the market‘s plunge.” 

When humans are in control, these kinds of mistakes tend not to spiral out of control. Individual errors happen, but arbitrary systems-level disasters do not. Spencer Greenberg, a big name in AI trading, says: “In the hands of people who don‘t know what they‘re doing, machine learning can be disastrous.”

Interested in AI Stock Trading?

One of the ways to identify future trends is to compare the performance of AI algorithms as opposed to human traders. After all, these ideas do not exist in a vacuum. 

Read more on how artificial intelligence is used in stock trading in our article.

If you want to build a profitable AI algorithm for stock trading, you‘ll need to outperform the best humans in the market. That‘s the only way to sell your services to the biggest players. If you are planning to invest in an AI trading platform, you will need a competent team of AI developers.

Your AI developers should be proficient in using the latest software development technologies including tools and programming languages to assist in efficient AI development. These include Python, TensorFlow, Matlab, etc. 

They should have a deep understanding of machine learning algorithms including deep learning, natural language processing, semantic analysis, etc. 

DevTeam.Space can help you here. We have a community of expert AI developers with experience in creating AI software solutions. 

Write to us your initial AI stock trading development requirements via this link and one of our technical managers will get in touch with you to further discuss your software development team, project planning, etc.

Frequently Asked Questions on AI Stock Trading vs. Human Stock Trading