How AI is Changing the Stock Market

Advances in Artificial Intelligence (AI) are not only disrupting business models and entire industries. Stock investors and traders around the globe are rapidly adopting AI and ML technologies to improve stock trading outcomes. Institutional traders such as banks and fintech companies have been leveraging AI too.  In this article, we look into how stock markets are changing as AI technologies become more and more prevalent in the financial sector.      

It is common knowledge that the stock market is driven by two opposing emotions – fear and greed. It is theorized that these factors are causing the unpredictability and volatility of the stock market. Failure to resist pressure from fear or greed can have a detrimental effect on an investor’s trading decisions. To be successful, traders must have the discipline to manage their emotions and not succumb to fear and greed.

While it takes a lot of self-control for traders to stick to their trading plans, computers inherently lack the emotions that may affect their performance. Automated Trading Systems allow stock investors to take some of the emotions out of trading and establish specific rules for buy/sell entry, exit, andmoney management that are automatically executed by computers. Automated stock trading systems have revolutionized the stock market since the 1980s when stock exchanges transitioned from traditional auctions to computerized transactions and in the early 1990s when Electronic Communication Networks (ECN) became popular. These developments set the stage for more intelligent systems that may someday replace humans out of the stock trading equation. 

AI is defined as an area of computer science that emphasizes the creation of intelligent machines that work and react like humans (techopedia.com). Popular AI applications are designed for speech recognition, learning, problem-solving, and robotics. 

AI makes it possible for computers to discover patterns from data, adjust to new inputs, and perform human-like decision-making. Machine Learning (ML), a form of AI, allows computers to be trained from historical data, process new data as input, and generate recommendations or predictions. Both technologies bring more intelligence into automated trading systems and are making a big impact onstock trading. 

The ability to select and predict stock prices is considered the holy grail of stock market analytics for decades. With new developments in big data and advanced analytics technologies, this is no longer impossible. Let us explore how AI and ML are modernizing trading in the stock market:

Stock Recommendations

As stock exchanges generate volumes of data for each buy/sell transaction, it becomes a nightmare for traders to analyze all available stock market data. Without the aid of computer systems, it would be impossible to sift through volumes of data to evaluate stocks or securities. This is where AI technologies come into play. 

With built-in capabilities to crunch millions of data points in seconds, ML algorithms can process historical and real-time market data to pick stocks that could outperform the rest of the market. AI-powered stock pickers can analyze the equivalent of thousands of research analysts more efficiently.  

Stock Price Predictions

AI/ML systems are not only capable of analyzing stock transactions, but they can also analyze the correlation between market news and stock price movement. Using advanced text analytics, ML algorithms can draw meaning from any market news and make sense of the data to discover patterns in stock prices. 

This means ML systems can learn what factors influence the price of a particular stock based on historical trades and other market information. Once it has learned and correlated the type of information that affects stock price, it can use ML-powered forecasting models to accurately predict stock prices.

Stock Trading Bots

AI and software bots are rapidly evolving into various applications that may someday replace humans. From chatbots that are trained to handle Q&A conversations on websites to digital assistants on mobile phones that can manage schedules and fulfill commands. ML-powered bots can also be trained to learn how to trade stocks based on historical data. Trading bots can mimic successful human trader behavior and even learn to come up with their own trading strategies. 

Just as AI software can beat chess grandmasters through reinforcement learning, a form of ML, AI trading bots may be able to beat the world’s best traders over time. 

Social Bot Trading

Social Trading is a service that allows individuals to follow and copy actual trades of their favorite stock market players. This somehow makes it easy for people who just want to invest in stocks but do not have the time to study the stock market. They can subscribe to Social Trading sites that offer such services for a fee. 

Instead of following human traders, it is possible to subscribe to AI-trading bots if such a service is made available to individual traders in the future. Subscribers can choose bots that match their risk profiles and decide based on their overall performance or even based on how many followers the bots may have.

Sentiment Analysis

AI/ML systems are widely used in social sentiment analysis to measure and analyze social media posts about a particular brand or product. It uses natural language processing, text analysis, andcomputational linguistics to identify and extract subjective contextual information. Sentiment analysis adds context to conversations about a certain topic and it enables companies to evaluate the attitude of their customers toward their brand.  

Often used by social media marketers, sentiment analysis can be applied to enhance stock trading. Powerful ML algorithms can sift through millions of social media posts, search engine keywords, and news bulletins to discern market sentiment and correlate it with stock price changes in real time. 

Portfolio Management

Extending the concept of AI-powered stock recommendation, price prediction, trading bots, andsentiment analysis, AI/ML systems can make manual stock portfolio management a thing of the past.

AI-powered portfolio management can select the best mix of securities that can yield better performance than index funds. Using natural language processing to sift through public disclosures and earnings call transcripts for specific words and phrases, it can determine which securities to include in the portfolio. It can provide fund managers the ultimate edge in attracting investors with cheaper services and more effective investment options. 

AI is revolutionizing the stock market with financial data analysis tools that significantly improvetrading efficiency and effectiveness. 

The biggest breakthroughs in AI/ML are happening with more advanced techniques such as Deep Learning and Computer Vision. Deep Learning teaches computers to process information more than humans do. This means computers can be trained to understand and develop responses or take actions rather than react according to a series of programmed rules. Computer Vision, which allows computers to see and recognize visual images and distinguish variations among images. Both technologies have enabled self-driving cars and soon may enable autonomous trading.

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*Emil Capino is the President and Founder of Info Alchemy, an IT Company in the Philippines.

Note: This article was previously published in printed Issue No. 17 of The Corporate, Guide and Style for Professionals Magazine.