Artificial Intelligence (AI) plays a critical role in trading financial assets. And its role is set to grow as technology advances and better, more capable hardware and software is built. AI helps financial institutions, trading firms and individual traders that can afford to use machine learning in their trading tremendously.
- AI is involved in creating advanced trading robots/algorithms that can execute trades automatically. Algorithms are programmed to follow a predetermined set of rules diligently. The main advantage trading algorithms have over humans are the ability to conduct news sentiment analysis, analyze large technical data such as indicators, and price action. Algorithms measure trade volumes, and execute trades without breaking predetermined risk management rules. Trades done by robots are highly precise. In addition, robots don’t get tired, sick or go on vacations.
- High Frequency Trading (HFT) is largely based on trading algorithms. When institutional and individual traders decide to use HFT, they prioritize the latest hardware and software, in addition to high speed internet connections. Financial Markets are incredibly efficient, however, price discrepancies still take place. HFT typically aims to take the advantage of these discrepancies by executing trades in milliseconds. This approach is also known as arbitrage trading, where trading algorithms buy assets in one market where it is priced lower and simultaneously sell it in another market where it is priced higher, and free risk trades are generated.
As already mentioned, trading algorithms can process a large amount of information fast. AI can be trained using machine learning to identify market trends and patterns. In addition, AI is involved in risk assessment and management, furthermore. AI helps investors optimize portfolios, and helps analyze market sentiment.
It’s easy to see that application of AI could have significant advantages over trading done solely by humans. Many institutions use hybrid models where both humans and machines work together to create better trading systems and increase profitability while limiting risks.
Financial markets are complex ecosystems with a diverse range of participants. They all have different goals, agendas and capabilities:
- Retail investors buy and sell assets using their own money.
- Institutional traders manage large pools of capitals
- Individuals and companies use financial markets to hedge against various risks, such as interest rate changes, currency rate fluctuations, political and economic events.
- Banks and financial institutions are using financial markets for several reasons, such as: providing services and products to their clients, and managing their balance sheet.
- Governments and central banks participate in the markets to implement their monetary policies and keep domestic inflation in check.
- Many global corporations that have production lines in different countries use financial markets to exchange currencies and give their employees paychecks in their local currency.
- Companies and governments that participate in international trade use foreign exchange market to exchange currencies.
As you can see, financial markets have many participants, and not all of them are aiming to make money in the markets using speculation. Money is often viewed as a technology
. And it has three main functions: to serve as a medium of exchange, to serve as a unit of account, and to be used as a store of value. In addition, money is highly portable. Modern forms of money such as digital currencies and electric payments have improved the portability of money.
AI is used in the financial markets for speculative purposes, with the only goal to make profits. However, the current form of AI is still at the very beginning phase of its full potential. Nowadays, AI is more involved in pattern recognition, and giving traders hints where to sell and buy. As AI is getting more advanced, it could become far more capable and make huge profits. As already mentioned, money has many uses, and the advantages this technology provides for us may be in danger.
One scenario is that AI becomes so advanced, with the only goal of making more profits, that the markets break. We’ll get highly volatile financial assets and the system will break. Robots do not care about ethics, or economies. Their only goal is to make more money. Many believe that trading algorithms have played an important negative role in the 2008 financial crisis
, which was triggered by various factors such as the housing bubble, subprime mortgage lending, and securitization of risky loans.
When markets become highly volatile, they only attract speculators and long term investors lose motivation to invest. Which can become a huge problem for publicly traded companies looking for investments.
In addition, if AI helps markets become more volatile (speculative money is made in highly volatile markets), the current functions of money markets will be lost, which are the store of value, medium of exchange, and unit of account.
Development of advanced AI is a threat not only for current financial markets, but for retail and institutional traders that cannot compete against AI. Creating and managing advanced AI that can make huge profits through the use of Expert Advisors
is not going to be cheap, and many individuals and companies will simply not be able to invest.
AI and automation has displaced many jobs, and made product creation more affordable and faster. However, advanced AI in the financial markets possesses a danger to the function of these systems. Transparency and accountability
are crucial in AI-powered stock trading. When we follow these principles carefully, financial institutions, traders, and regulators can build trust and increase confidence in using AI for stock trading. It's essential to make sure that these ethical rules are part of every step in creating and using AI systems for stock trading. This way, we ensure they are used responsibly and ethically in the complex world of financial markets.