In the last couple of years, surveys have shown a significant increase in AI applications in social, political, and business spheres of our lives. Artificial Intelligence can perform almost 70% of all business operations. It is present on every social media, our phones use it to interact with us, even mentioned surveys about the AI were done by using the AI algorithms.
Statistics say that many people believe more in AI than in their governments, banks, or institutions, so it is clear why leading companies from different industries choose to rely on new technology.
So when it comes to our investments, should we put our trust in AI?
Stock trading is changing and evolving every day. These changes inevitably include the introduction of machine learning and algorithms that will make market estimates and advice on the most effective investment.
To understand the significant role of cognitive systems on the stock market, we must first determine all the functions that can be improved by AI.
The essential difference between human and computer work is that machines have the ability to process an incredible amount of data in a short time. That is why machine learning will absorb a great deal of historical data and create patterns about smart investing, or a pattern about behaviors and decisions that have always lead to losses.
Some hedge funds are using AI algorithms that can access up to 300 million New York Stock Exchange data only in the first hour of daily trading. Such numbers are unimaginable for the human mind.
Predictive analytics is one of the most advanced fields of Artificial Intelligence. By processing information from the past, news, social media, or public comments, AI can predict the direction in which stocks will move. Moreover, it can also analyze the behavior of other stock market participants and their moves.
Stock trading requires speed. Every broker’s competency depends on their ability to react quickly. Imagine an AI that can buy in a split second. Indeed, if only Artificial Intelligence could be reliable in decision-making, it would certainly be an excellent job executor.
Machine learning is getting better every day. However, it can often go wrong. The decision making is based solely on the input of available data. Even if one system can be fed with a mass of information, relying solely on its quality is not flexible enough for the demanding operations required by the stock market.
Moreover, AI will be productive under normal circumstances. However, in the case of any unnatural appearance, like the 2008 recession, an AI system could be exposed to confusion and dysfunction, and an entire investment could be lost.
In light of such adverse events, another question would arise, especially if an AI-based financial intermediary invested in your name. Who will bear the consequences of the loss? Is it a company that entered a stock market, or AI is completely responsible for the crash?
In our present environment, perhaps the smartest thing to do is to use AI to get the proper analysis and prepare numbers and odds for the stock market while entrusting the very act of trading to our own knowledge and experience.