Can computers pick stocks better than humans? Investment companies think so

Investment firms increasingly rely on algorithms to make investment decisionsDANIKA SO

Walk into an investment firm today and you’ll likely find it crowded with analysts poring over paperwork and investment managers weighing stocks to add to their portfolios. Chances are their days are numbered. Soon, computers with artificial intelligence (AI) will do much of the stock picking, while fund managers will just make sure the machines are running the right algorithms.

Many fund companies are already turning to AI in hopes that it can deliver better returns than human stock pickers. The systems identify patterns in pricing data, yield curves, how markets execute trades and more, then make predictions based on those patterns. Bridgewater Associates, the world’s largest hedge fund, said last year it would replace many of its managers with machines. Research firm Optimas estimates that by 2025, the use of AI will lead to a 10% reduction in the financial services workforce, including 40% of those layoffs in fund management operations.

Andrew Dassori, founder and chief investment officer at Wavelength Capital Management in New York, has been using AI in his Wavelength Interest Rate Neutral fund since 2013. He applies it primarily to the fixed income side, but is experimenting with stock picking algorithms on the bond side as well. the equity portion of the fund. “The computer can analyze more data than any individual,” he says. “It can look at areas where there is rapidly expanding new data, such as market sentiment and measures of buying and selling pressure.”

AI also surpasses humans in its predictive powers. It can determine whether one stock or bond is likely to perform better than another based on factors ranging from past performance to weather to who uses a company’s products, where and when. Dassori created a model looking for stocks that have a specific combination of carry styles (dividend or yield on a stock), momentum and value. After the 2016 US election, the algorithm suggested he buy a five-year Treasury bond instead of a 10- or 30-year one. It was fair, he said.

While Dassori’s fund uses “supervised” technology – meaning it monitors and sometimes adjusts what the computer selects – it is also testing an unsupervised version in which it enters its parameters and lets the machine make the selection. . If that takes off, he knows his role as fund manager may change. “Individual security analysis is best done by a machine,” he concedes, though he adds, “People have to test and validate the process.”

At London-based Man AHL, an industry leader in investing in AI adoption, algorithms look at market trends over two months to help determine the best decision. The AI ​​could decide, for example, to buy into a dip while others could sell, or vice versa. “I could say, I’ve seen this pattern before, so I’d like to sell on the small downturn and buy the dips as the market starts to rise again,” says Larry Kissko, a client portfolio manager. “He’s using what he’s learned from the data to do things slightly differently than human intuition [might suggest]While the system currently primarily analyzes market-related data, Man AHL can incorporate language from analyst reports, demographic trends, and other analysis.

Whether AI will perform better than humans remains to be seen. Kissko and Dassori think the technology improves their yields, but won’t say by how much. And machine addiction comes with risks. Since the algorithms mostly rely on historical data, something that has never happened before could trip them up. “What if you train these things and all of a sudden the pattern breaks?” asks Davyde Wachell, founder of Responsive, a Vancouver-based company that created an AI-powered wealth management program.

The fact that people are programming AI to analyze specific information is also a factor. What if they tell it to focus on the wrong datasets? And what if everyone’s AI is looking at the same things? “The market would become perfectly efficient,” said Sébastien Betermier, professor of finance at McGill University. “There would be nothing more to predict.”

Regardless of how AI ends up affecting markets, the role of the traditional fund manager is set to change dramatically. Many of those who keep their jobs will be tasked with creating investment models and making sure the algorithms work properly. “They will oversee and validate what the machine is doing,” says Dassori.