AI has become a buzzword that signals innovation and change. Startups are raising jaw-dropping amounts of money for AI-based ideas that are barely off the ground, and companies everywhere are racing to add AI to make their processes smoother. In financial markets especially, where finding that elusive “alpha” (or edge) is everything, AI is generating serious excitement. The future is uncertain, but one thing seems clear: AI-powered algorithms could shape the way markets work, both today and in years to come.
Algorithmic trading boils down to a set of rules that a computer follows to make trades. The general principle being, the better the rules, the higher the returns. With AI in the mix, the possibilities get even more interesting. Usually, building an effective trading algorithm requires some serious theory, like deciding which factors matter and how to judge them. But with AI, the process of building and testing these algorithms is faster and more flexible. AI doesn’t just help brainstorm ideas; it can actually write code to bring those ideas to life. This makes it easy to try out even the wildest theories like “moon phase” investing, and quickly find out if they have any real potential by performing backtests – testing returns that would have been generated by the model based on previous market data.
Figuring out the best way to create an algorithm to maximize returns is no easy feat, though AI can help here too. With no one being able to fully model the stock market, the rules governing it are elusive. While it’s tempting to think AI could uncover the hidden rules of the financial markets, it’s not that simple. The financial world is complicated and often unpredictable. Even if there are patterns to be found, AI’s process for discovering them is typically a “black box”—we know the data going in and the results coming out, but the “how” in between is tough to unpack. Running an AI model sophisticated enough to trade well is no small feat either; the computing power needed to do this is immense. So, while AI trading sounds enticing, it isn’t just a matter of writing some code and watching the money roll in—it takes serious resources, both financial and computational as deciding the most optimal approach to implementing AI is not easy and requires heavy mental lifting.
Another huge advantage of using AI in finance is that it takes the emotion out of trading. Human investors have all sorts of biases that can mess with good decision-making. For instance, there’s overconfidence bias: investors sometimes think they’ve struck gold with a can’t-miss strategy, only to watch it go up in smoke. AI, on the other hand, sticks to the rules without a hint of ego. There’s also anchoring, where people base their predictions on old information, like a previous price, instead of considering current factors. AI takes in fresh data and doesn’t get “anchored” to the past. Then there’s herd behavior, where people follow the crowd instead of thinking for themselves. This is how bubbles form, with prices surging not because of any real value but because everyone is just copying each other. AI doesn’t care about the crowd; it trades based on numbers, not hype. Lastly, there’s the disposition effect, where people hold on to losing stocks while selling the winners. AI doesn’t get attached to any investment, cutting losses and riding winners based purely on performance.
In short, AI brings a lot to the table in finance, from optimizing trading algorithms to helping traders avoid common mental traps. But it’s not a magic fix. Building a good AI trading system is expensive, requires deep financial know-how, and demands serious computing power. While AI can help sharpen trading strategies and make more objective decisions, creating an AI that consistently beats the market isn’t as easy as it sounds. Right now, AI is a tool to improve the way professionals trade—helping them stay focused on data instead of emotions and to sidestep some of the usual pitfalls. There’s huge potential but getting there means understanding both the tech and the markets inside and out.
– Arturs Linde