Context is required to fully explain the functionality of AI in the stock market. The stock market exists for three reasons. The main reason is investing. It centralizes investing allowing the public to have the ability to invest in the company. The next reason is price discovery. The stock market helps determine a good market price for goods and services provided by a business. The third one is capital formation which is used to describe the capital of a particular country. Before AI took control of the stock markets, about 80% of all NYSE stocks were traded on the floor of the NYSE. Now, that number is 11%. This is because of two reasons. The first one is because AI is being created to trade automatically, meaning that you don’t have to physically be present or knowledgeable of what the AI is doing. The second reason is there are services that allow you to trade online.

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Two of the uses for AI in the stock market is research and high-speed trading. For the research portion, the AI used in trading stocks does not determine what stocks it will trade any differently than how a person would do it. The simple research is as follows: know what the company does, who their partners are, their plans, their quarterly earnings, annual reports, and news events. An AI can configure all of this information for hundreds of businesses in the time that it takes a person to do one. AI is an incredible time saver. For high speed trading, AI gives firms the ability to buy and sell millions of shares in a fraction of a second. These efficient moves in the process of buying and selling stocks is based on data and patterns. These uses lead to a growing demand for AI because it doesn’t make human errors. Firms are paying more than $1,000,000 for machine learning specialists. The official title for the occupation that makes algorithms of this caliber are labeled quantitative analyst. This occupation doesn’t consist of being a professional in investing or business, rather creating algorithms used in AI that determine if you should buy and sell certain shares. Quantitative Analysts determine this by scanning through stock charts and recognizing patterns. More than 50% of trading volume in a given day is due to high-frequency trading.

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Citadel group is one of the businesses that are creating efficient frequency trading algorithms. They are the largest trading firm in the country. They execute 14% of all the stocks traded in the NYSE and manage more that $25 billion in assets. More employees are quants and work in customer service than people who actually trade stock. The decision to buy and sell stock are 100% the AI. AI starts up at the start of the trading day and begins to crunch the numbers to buy and sell shares within seconds.

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A common pattern that high-frequency trading algorithms capitalize on is called the zones pattern. This pattern is when the stock is bouncing up and down between two resistance lines. (Resistance lines are strike prices that the stock halts at or struggles to surpass.) When the stock is considered by the AI to be in a zones pattern, it begins monitoring. If the stock breaks the resistance line, thus, breaking out of the zone, the AI predicts whether purchases of that stock should be made or not. Another pattern is the inverse head and shoulders pattern. This is when the stock evens out after a significant increase or decrease. This pattern indicates that the stock has the potential to change direction drastically, thus, the AI buys stock if necessary and sells minutes, sometime seconds, later.

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