For most people, it’s not a question of if AI will surpass humans in making intelligent decisions – it’s a question of when. In fact, many would argue that AI has already surpassed us in many fields, although AGI – Artificial General Intelligence – is not yet within our grasp.
However, artificial Intelligence models are sometimes explained as prediction machines. And doesn’t that sound like the perfect recipe for success when we’re talking about trading?
Machines, algorithms, and AI are by no means new to the world of trading. People have been trying to master the trading bot for decades. But have they succeeded? Have smart bots actually gotten better at trading than human traders? Would it be better to just hand over your portfolio to an AI?
This article aims to thoroughly answer the question of whether AI outperforms humans in trading, as well as address the complexity of the very question.
The State of AI in Trading Today
As mentioned, the idea of using AI to trade is not new.
People have long been hoping to develop the perfect trading bot, and many think that Artificial Intelligence will blow human intelligence out of the water in a few years – some already consider AI smarter than humans.
And while making good trading decisions certainly isn’t the best indicator of intelligence, it’s an interesting one with measurable results.
In our modern world, algorithms and AI are being used for all kinds of things. We find AI in everything from social media feeds to search engine results to entertainment analytics.
Some gambling sites have even started making use of AI to create a safer user experience. Casinos might, for instance, incorporate tools like Mindway that help ensure a positive and safe experience for each player, thanks to AI and analytics.
This is becoming more common in regions like Europe, North America, and Australia, where security standards for players are especially high. Take a deeper look at Esportsinsiders’ guide to Australian casinos if you want to understand how player safety and experience are enhanced through technology.
In trading, machine learning is used for functions like algorithmic trading (now accounting for an estimated 60-70% of trading volume), market analysis, and risk management. AI is also used for automated portfolio management. Since AI can execute trades at very high speeds, it’s become a crucial tool for many traders, both on an institutional and individual level.
What do people think about AI in trading today, then? According to a survey that CoinGecko published in April this year, around half of people believe that AI agents are better at crypto trading and investing than humans most of the time. The other half don’t think that AI has an advantage yet.
Now that we know where we are today, let’s talk about where both human intelligence and artificial intelligence fail and where they shine.
AI strengths, AI pitfalls
In his book How AI Works: From Sorcery to Science, machine learning expert Ronald T. Kneusel explains that while AI is great at interpolating, it can be really bad at extrapolating. From his book:
“When extrapolating, we might have reason to believe that the data will continue to fit the line; if that’s a valid assumption, then the line will continue to be a good fit. However, in the real world, we usually have no such assurance. So, as a slogan, we might say interpolation good, extrapolation bad.”
What this translates to practically is that if a situation fits historical patterns and the data is complete, AI can be great. But if something unexpected is going on – and with political tension and the ever-changing world, something usually is – then AI is often quite terrible at predicting what’s going to happen next.
In the previously mentioned book, Knuesel also tells a story about a conference talk he once attended about neural networks and the way they make decisions. The task of the model in the example was to classify images of Siberian Huskies and Wolves and fit them into the right category. The model performed incredibly well – but there was a catch. What happened next:
“The speaker then marked the images to show the parts that the neural network focused on when making its decisions. The model wasn’t paying attention to the dogs or the wolves. Instead, the model noticed that all the wolf training images had snow in the background, while none of the dog images contained snow. The model learned nothing about dogs and wolves but only about snow and no snow.”
That’s a typical AI mistake that could also occur when a trading algorithm is at work. It could mistake a correlation for a causation, which could potentially cause a disaster when it doesn’t translate in the real world. The website of spurious correlations proves this point well by showing totally unrelated graphs that match up despite being completely unrelated.
The main strengths of AI in trading then include the following:
- Speed. A few seconds can make all the difference in high-frequency trading, so speed is a great advantage of using an AI trading assistant or bot.
- Identifies trends quickly. Since AI can process information so quickly, it can identify trends fast and make adjustments over time.
- Efficiency and scalability. Making trades with a bit is much more efficient than doing it manually, and makes it much more possible to scale in a way you just can’t with human traders.
- Data-driven algorithms. AI’s ability to quickly process large amounts of data leads to data-driven algorithms with emotion out of the picture.
- Consistency. The ruthless patterns of artificial intelligence can be a great benefit when a strategy is dependent on consistency.
Meanwhile, the weaknesses of AI are:
- It can be too inflexible. Inflexibility can cause an AI algorithm to keep trying the same things that worked before instead of trying out something new when old methods aren’t working.
- It’s completely dependent on the quality of data. AI can’t make its own judgment, but relies on data alone. Because of this, the quality (and quantity) of that data is absolutely crucial.
- It’s bad at dealing with the unexpected. We live in unexpected times, and AI has a particularly hard time responding to unexpected events and new changes not supported by historical data.
- Success rates can be deceptive. As our example with the huskies and wolves indicates, a model can perform great while focusing on all the wrong indicators, which will eventually cause real trouble.
Human Intelligence in Trading
Unlike machines, humans are emotional, original, and intuitive. This translates to both strengths and weaknesses in the way that they trade (and make decisions overall).
The strengths of human intelligence in trading are the following:
- Creativity. Humans can imagine a new and creative strategy to tackle a situation that an AI couldn’t have come up with on its own.
- Flexibility in unpredictable situations. Humans can respond to unforeseen events in a much smoother way than a pre-programmed algorithm.
- Emotional intelligence and social understanding. Humans are better at understanding nuance, complexity, emotions, and political tension that might affect the outcome of a situation. They can perform a qualitative analysis and use their intuition.
- Deeper understanding of market trends. Humans can often see deeper relationships that an AI could miss, and are better at differentiating between correlation and causation.
There are two main weaknesses of human intelligence in trading:
- Slowness. The human brain is slow (comparatively) at both processing data and executing commands. By the time a robot has completed thousands of transactions, we’ve just had time for one. While we’ve read a headline, the AI has had time to process thousands of lines. Humans can’t compete with AI when it comes to speed.
- Emotional bias. Humans are prone to making emotional decisions and being affected by cognitive biases. This can sometimes mean we panic and sell when a stock is dropping, even though we know buying high and selling low is a losing strategy. It can also lead to careless buys due to FOMO and other situations where we just don’t stick to our own strategy.
Which Is Better for Trading?
Long story short, it’s a tie.
Human judgment is often better in unpredictable and complex environments, which also often means it’s better when it comes to long-term investment.
AI, on the other hand, has the advantages of speed, consistency, and data analysis, meaning it does great when patterns are predictable and in quantitative trading.
It Doesn’t Have to Be Either/or
The end conclusion to all of this is pretty much this – it’s not either/or, it’s both. If there’s anything that technological developments have shown us, it’s that developments don’t usually result in disappearing jobs, but rather changing ones.
AI likely won’t nullify human trading skills, but will instead be usable to complement human intelligence. Using AI can make a human trading strategy much more scalable and make decisions go through faster, but without human judgment, the AI won’t know when or how to apply a smart strategy.
Humans who know how to intelligently and consciously make use of AI are going to surpass both pure algorithmic trading strategies and pure human effort. Rather than a competition, it’s a partnership.
Those who can recognize that and implement it – especially without getting lazy and ending up leaving it all to the machine – will gain an edge over those who can not.
