AI Trading Is Now Apparently Outperforming the Market

In early February 2025, Bloomberg reported that Minotaur Capital – a hedge fund guided, not by human analysts, but artificial intelligence – had outdone the stock market in its first six months of activity. Specifically, Minotaur had clocked in with returns of 13.7%, as compared with an index of global stocks that returned only 6.7% in that time period. While it’s unclear whether or not this sort of performance will continue into the long term, it was a very encouraging sign for those aiming to harness AI to conquer the stock market – something that, until now, has eluded the efforts of developers.

We know that AI technology has plenty to offer in the field of online trading. For one thing, it can save you the hours of time you would normally have to put into researching stocks. This is through scanning thousands of pages of fundamental and technical data relating to companies and coming out with an actionable conclusion. This could even be done in a customized way – based on the input of your own criteria. There wouldn’t be any guarantees regarding the outcome of your deal, but you would at least be saved lots of time and energy.

Aside from this function, what other benefits can AI bring to your online trading platform? Are there any drawbacks to relying on AI technology in this way? Join us for some discussion.

Trade Management

The power of AI has been leveraged to take over much of the financial trading process itself, which allows traders to adopt a much more passive role. For example, your trading platform could be programmed to buy 500 shares of Meta Platforms when the firm’s 50-day moving average rises above their 200-day moving average. This would be performed automatically when that condition was met, while you are going swimming. Even when it comes to the task of closing your deal at the right time, your participation may not be required at all. Rather, you could set the dials of your trading platform to close the deal based on your own stop-loss or take-profit orders. AI technology is able to respond to real-time market conditions as they develop, which potentially allows you to sit comfortably in the back seat and watch the action from afar.

Backtesting

Let’s say you have your eye on a particular portfolio of stocks but feel unsure how it may perform under certain market conditions. AI is able to run your portfolio through thousands of different market simulations to test its staying power. If you anticipate a recession in the months to come, for instance, you could backtest the stocks in recession scenarios and watch how they respond. In the event that they respond badly, AI could suggest a different portfolio that might work better under those conditions.

The algorithm being employed by your trading platform can be refined through extensive backtesting, which can enhance its effectiveness substantially. On the other hand, there is also a danger that comes with this. It sometimes happens that, when algorithms are trained on historical data, they are over-optimized to fit those specific parameters and, thus, become unfit to excel in real market conditions. This is a problem that developers are presently doing their best to address.

Machine Learning

Machine learning (ML) is the subset of AI that specializes in spotting predictive patterns in data sets. Algorithms enabled by ML can even develop their own predictive powers through interacting with real-time information. Understandably, developers see much potential to apply ML in the field of online trading, but they have met with challenges. “The inherent ‘noise’ in financial markets makes quantitative investing one of the most challenging applications of ML”, explains JP Morgan. Speaking more broadly, computers have the same difficulty we have in determining the most relevant price trends of the moment. Remember that, while AI is good at analyzing information, it is no sort of prophecy.

Opaque Algorithms

If your trading platform is using an algorithm controlled by ML, there’s another issue that tends to pop up. In many cases, such algorithms are not understood by their own developers. That’s because they don’t merely follow a pre-established set of rules (as other algorithms do) but rather choose their own ways of meeting particular objectives. Since they are autonomous in this way, nobody knows precisely why they act as they do.

This can be a problem for traders who want to understand the underlying strategies guiding their portfolios. More specifically, it complicates the question of assigning responsibility when expensive failures happen, and it adds an extra challenge to the task of managing risk. Essentially, this kind of “black box” algorithms require the trader to step back and leave the trading to their computers, which deprives the dealmaking of essential human input.

Wrapping Up

We have seen some of the reasons why the effectiveness of AI in online trading is, at present, quite limited in certain ways. Still, it seems clear that this technology can add something significant – one way or another – to the prowess of both beginners and old-timers in the financial markets. For instance, AI’s emotionless decision-making can save many of your trades from the destructive forces of greed and fear. It’s highly challenging for anyone participating in the markets to ignore the sway of such instincts in deciding when to open and close their deals. AI has the advantage of operating exclusively based on the cold, hard data.

If you decide to make use of an AI algorithm on your trading platform, it may take you some time to identify the right one for you. That’s because, due to the long list of available options and the opacity of their functionalities, it’s difficult to know what makes each one unique.