AI Trading Software vs Human Traders: Who Will Win?

Experts say that even the best AI trading software will never replace humans’ intellect. At the same time, AI software for trading has evolved over the last six decades. What’s more, it now offers even more comprehensive solutions with the implementation of machine learning technologies letting automated platforms decide on the next step considering specific market parameters and configurations as well as perform different types of trading strategies on autopilot.

Will humans be able to oppose artificial intelligence stock trading software? Or will the market be at machines’ disposal with humans only watching platforms making money for them? Let’s discuss the future perspectives of AI-based smart trading.

How AI Trading Software Works

Some beginners mistakenly think that “AI software for grading is the same as trading robots, which are programmed and configured by humans to perform specific actions within a given timeframe. AI-based trading considers a more complex system that relies on machine learning. It means that software will take into account previous trades and results as well as users’ preferences to change on the go while improving the approach without manual setup.

In other words, it is not a human who keeps control over software, the technology that tells the machine what to do while generating and processing specific data. On the one hand, it looks like a great option for those who still need to maintain their daily tasks while the system makes money for them avoiding human factors. On the other hand, some specific drawbacks may also take place.

AI Trading Software vs Humans

The key challenge when applying artificial intelligence stock trading software in the financial market is complexity. Trading is not just a set of factors, dependencies, and rational parameters. It is also about psychology, geopolitical events, market overviews, different types of economic variables, and other points that require in-depth analysis, as they affect the market greatly resulting in its up or downtrends.

Engineering does help to finetune machines letting them predict sequences and possible outcomes. However, markets tend to move unpredictably and historical data can have no sense in the context of the present time, especially keeping in mind rapidly evolving markets and industries. Besides, machines are still unable to retrieve other supportive information that is vital.

Let’s see, what AI software for trading with machine learning technologies applied can do right now:

1. Sentiments Prediction – some of the best AI software for trading comes with built-in sentiment indicators as the result of ML experts who conducted a set of experiments teaching the machine to foresee stock trading results via the blend of 1-learning systems, specific knowledge graphs, and sentiment analysis. The machine identifies the most meaningful word from the news headline, which helps to separate core info from noise. The process is rather time-consuming while the technology is mainly used by banks, hedge funds, etc.
2. Trading Signals – a simpler and faster algorithm to provide trading signals as well as direct call-to-action notification. The good news here is that it is still up to a trader whether to follow those signals or not depending on the investment horizon, trading strategies, risk tolerance, and other factors. The main benefit here is that software can process a bigger number of different metrics from various sources if compared to human analysts.
3. Fraud Prevention – after some time, trading will inevitably turn into routine. Beginners will feel like moving back and forth performing the same actions day by day resulting in reduced concentration. With AI technologies, this is no longer an issue. Software never sleeps or gets tired. It strictly follows specific machine learning algorithms that can prevent traders from losses or missed events. Besides, ML technologies ensure a faster validation process and ID protection to prevent users from potential frauds.

High-Frequency Trading – HFT introduces a set of complex algorithms. The idea is to use powerful software capable of executing numerous trades simultaneously. Humans are simply unable to deliver the same level of execution, as such calculations are beyond their skills. On the other hand, the approach has some obvious downside for the regular trader, as it requires high-speed and expensive hardware along with closely located servers, which only huge corporations can afford.

Summing up, AI trading software is a good alternative that helps to avoid human factors and execute numerous trades simultaneously. On the other hand, machine learning follows only a set of rational factors, not being able to react and make decisions like a human. As a result, a balance between human intervention and AI technologies is required to ensure safe and successful trading.

This material does not contain and should not be construed as containing investment advice, investment recommendations, an offer of or solicitation for any transactions in financial instruments. Before making any investment decisions, you should seek advice from independent financial advisors to ensure you understand the risks.