Artificial intelligence is a game changer for the stock market.
When Wall Street statisticians realized they could apply AI to many aspects of finance, including investment trading applications, Anthony Antenucci, vice president of global business development at Startek, had insight to share.
“They could effectively crunch millions upon millions of data points in real time and capture information that current statistical models couldn’t,” he told ITPro Today. “Machine learning is evolving at an even quicker pace and financial institutions are one of the first adaptors.”
Of course, Antenucci isn’t the only one to recognize AI’s stock potential. Online trading is expected to reach a market value of approximately $12 billion by 2028. Much of this anticipated growth will be thanks to AI.
While humans remain a big part of the trading equation, AI plays an increasingly significant role. Algorithmic trading accounts for around 60 to 73 percent of U.S. equity trading, according to Wall Street data highlighted in one report.
What Is AI Trading?
AI trading refers to the use of artificial intelligence, predictive analytics and machine learning to analyze historical market and stock data, get investment ideas, build portfolios and automatically buy and sell stocks.
AI Stock Trading
AI stock trading uses machine learning, sentiment analysis and complex algorithmic predictions to analyze millions of data points and execute trades at the optimal price. AI traders also analyze forecast markets with accuracy and efficiency to mitigate risks and provide higher returns.
How AI Stock Trading Works
AI trading companies use various tools in the AI wheelhouse — like machine learning, sentiment analysis and algorithmic predictions — to interpret the financial market, use data to calculate price changes, identify reasons behind price fluctuations, carry out sales and trades and monitor the ever-changing market.
There are several types of AI trading: quantitative trading, algorithmic trading, high-frequency trading and automated trading.
Quantitative trading, also called quant trading, uses quantitative modeling to analyze the price and volume of stocks and trades, identifying the best investment opportunities.
Algorithmic trading, also known as algo-trading, is when stock investors use a series of preset rules based on historical data to make trading decisions. (High-frequency trading is a type of algo-trading that is defined by large quantities of stocks and shares being bought and sold rapidly.)
When a trading system is built using the technical analysis of quantitative trading combined with automated algorithms built on historical data, you get AI trading, sometimes known as automated trading.
AI trading provides hedge funds, investment firms and stock investors with a slew of benefits.
Benefits of AI Stock Trading
AI trading can cut research time and improve accuracy, predict patterns and lower overhead costs.
Reducing Research Time and Improving Accuracy
AI trading automates research and data-driven decision making, which allows investors to spend less time researching and more time overseeing actual trades and advising their clients. One survey found that traders who used algorithmic trading increased productivity by 10 percent.
And because AI trading uses historical financial data to inform decisions, there is less risk for human error and more room for accuracy.
Using sentiment analysis, which is the process of gathering text and linguistics and using natural language processing to identify patterns within subjective material, an AI trading system can gather information from news outlets and social media to determine market swings.
Traditional investment firms might have hundreds of brokers, analysts and advisors working under them, but AI trading technology can replicate some of the repetitive tasks people have to do. There may be costs to implement and maintain AI, but over time firms and investors can spend less money on overhead expenses. Plus, AI algorithms can work continuously and monitor the stock market 24 hours a day.
With these benefits in mind, let's take a look at 10 companies using AI in trading.
10 AI Stock Trading Companies
Location: New York, New York
Canoe specializes in alternative investments, including venture capital, art and antiques, hedge funds and commodities. Canoe’s platform allows investors to gather all documentation related to their alternative investments in one place and deliver data to external accounting systems, data warehouses and performance systems. Canoe uses natural language processing, machine learning and meta-data analysis to verify and categorize an investor’s documentation.
Location: New York, New York
AlphaSense helps investors research the market fast with its easily searchable platform. The company collects written content and data from sources like Goldman Sachs, J.P. Morgan and Morgan Stanley and makes it easy to sift through with its search function. AlphaSense uses AI trading technology like natural language processing and machine learning to comb through thousands of documents, market reports and press releases.
3. Trading Technologies
Location: Chicago, Illinois
Through its 2017 acquisition of Neurensic, Trading Technologies has an AI platform that identifies complex trading patterns on a massive scale across multiple markets in real-time. Combining machine learning technology with high-speed, big data processing power, the company provides clients with the ability to build their own algorithm trading platforms. This allows users to automate the entry and exit of positions and reduce the market impact of large orders as well as the risk of manual errors.
4. Kavout Corporation
Location: Seattle, Washington
Kavout’s “K Score” is a product of its intelligence platform that processes massive diverse sets of data and runs a variety of predictive models to come up with stock-ranking ratings. With the help of AI, the company recommends daily top stocks using pattern recognition technology and a price forecasting engine. Its model portfolios are enhanced by AI algorithms.
Location: San Francisco, California
Numerai uses machine learning to predict stock market trends and manage a new kind of hedge fund. The firm is a unique player in the market, as it uses encrypted data sets to crowdsource stock market models predicted by AI. The models are sourced from anonymous data scientists who are awarded Numerai’s cryptocurrency, NMR, for providing better models.
Location: Fully Remote
Auquan’s platform helps investors gather market insights and create custom datasets from raw unstructured data. Users can search over 1 million sources to uncover lawsuits and sanctions before moving forward with investments. Auquan also offers solutions for asset management, wealth and risk management as well as commercial and investment banking.
Location: Miami, Florida
IntoTheBlock uses AI trading and deep learning to power its price predictions and quantitative trading for a variety of crypto markets. IntoTheBlock’s models are trained on spot, blockchain and derivatives datasets which allow users to access historical data to better inform their trade decisions. The platform also compiles market sentiment on crypto assets so investors can get a pulse on even the most in-flux parts of the market.
8. Trade Ideas
Location: Encinitas, California
Trade Ideas AI-powered self-learning, robo-trading platform “Holly” subjects dozens of investment algorithms to more than a million different trading scenarios to increase the alpha probability in future sessions. Each night the AI assistant platform will select the strategies with the highest statistical chance to deliver profitable trades for the upcoming trading day. On average, Holly enters between five and 25 trades per day based on various strategies.
9. Imperative Execution
Location: Stamford, Connecticut
Composed of experienced traders, analysts and engineers, Imperative Execution builds “efficient financial exchanges” with the help of its product IntelligentCross, which uses AI to analyze stock prices and ensure price stability after trades are complete. The platform works with a variety of brokers and receives over 200 million orders from investors per day, according to its website.
Location: San Francisco, California
Sentieo provides a host of financial solutions for investors with the help of AI. The company’s AI-powered financial search engine collects internal and external content, such as news, rating agency reports, transcripts and press releases, into a single shared workspace. Analysts can use its natural language processing to identify the latest news on key financial searches, while individual investors can use its platform to research companies and markets.