Humans Vs AI: Who Is Better At Money Making In Financial Markets

Humans Vs AI: Who Is Better At Money Making In Financial Markets

Artificial intelligence now closely competes with humans in various fields, which were previously unattainable such as arcade games, protein folding, chess, self-driven cars, and more. Technological progress has made its mark on the financial service industry. Technology startups are now challenging financial institutions such as banking. AI is the backbone behind cybersecurity, chatbots, and many such features.

Pavel/Pexels | AI has been making progress in many industries

Traders use simple algorithms. AI algorithms are less famous in financial or investment decision-making. However, as machine learning is all about analyzing huge sets of data and finding trends, financial markets generate huge data so they are a good match. Some specialist investment companies have declared that they use AI technology to help them make decisions in their investment decisions. In this article, we will analyze whether AI is better than humans at generating money.

AI’s Financial Forecasts

We analyzed various studies presented by researchers between the years 2000 and 2018 about how machine learning algorithms affected the various kinds of stock market forecast experiments. The motive was to determine whether these techniques are applicable in the real world or not.

The immediate observation was that most experiments run multiple versions of investment models together. The highest-performing model was the primary product in most experiments, which meant they would get the best results. On the other hand, this approach is not possible in a real-world investment where a given strategy can be executed once and if it results in a loss you cannot undo the results.

Karolina/Pexels | People often argue that AI algorithms may be better at making money

Running multiple variants and presenting the best as the representative would show a misleading picture of the investment sector and can be regarded as illegal. One version of an algorithm should be tested, which best represents the real-world investment setup. Models that we reviewed had a 95% accuracy rate but in market forecasting, if the algorithm is wrong 5% of the time, this could be a big problem. The 5% can cause a loss of profit as well as capital.

Most AI algorithms we tested had no transparency on how they work. This characteristic doesn’t appeal to investors in the real world and can be a problem from a regulation perspective. Moreover, the experiments did not account for trading costs although it’s decreasing but should be accounted for to have a clear idea of profit and loss.

Pixabay/Pexels | All of this leads to the analysis that AIs discussed in the experiments were not feasible in the real world.

Are Humans Better?

We also compared AI’s achievement with human investment professionals. If AI could perform equally well as humans or better in the field, then that could have resulted in a large number of jobs being lost. We discovered that AI-powered funds whose performance data was present in market data sources were not doing that great in the market. This may be because of the critical thinking skills of the human brain, which allows us to take efficient mental shortcuts. Thus, we concluded that humans are ahead of AI.

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