It’s no secret that technological prowess can shape a company’s future.
It turns out, however, that tech prowess also creates hidden linkages that can shape the futures of companies that seem entirely different on the surface.
A new study led by Charles M.C. Lee, the Moghadam Family Professor and professor of accounting at Stanford Graduate School of Business, finds that shrewd investors can use this technological proximity to predict how a tech-based stock will perform in the months ahead.
“Technological capability drives growth, but these capabilities don’t occur in isolation,” Lee says. “There are overlapping technologies, subject to common shocks, and there are knowledge spillovers. Our central hypothesis is that investors don’t quite understand these sneakier connections between companies.”
Lee isn’t talking about obvious similarities, such as those between smartphone companies and wireless carriers, or between rival social media platforms.
Rather, he is talking about a similarity in underlying expertise as it’s reflected in the kinds of patents that companies receive.
A biotech company that makes pharmaceuticals is in an entirely different business from a company that makes equipment for analyzing gene sequences. But if both companies have a big share of their patents in molecular biology, Lee says, they may well be “tech peers” and be more intertwined than investors initially appreciate.
If that actually is the case, Lee theorized, the stock market may be slow to recognize that important news for one company is also important for many of these hidden tech peers. That would constitute an information lag and create an opportunity for astute investors.
“Our hypothesis was that when good stuff happens to your technology peers, then it is likely to happen to your company too,” Lee says. “If bad stuff happens to your tech peers, then that may be down the road for you as well.”
Lee and his colleagues — Stephen Teng Sung at the City University of Hong Kong, Rongfei Wang at Peking University, and Ran Zhang at the China Investment Corp. in Beijing — confirmed their intuition by analyzing decades of historical data on technological closeness and stock returns.
Step one was to identify tech peers based on how much their patents were concentrated in some 700 different categories of technology.
Step two was to test the investment strategy by running thousands of computer simulations. In essence, the researchers tested what would have happened if they had systematically bought or sold shares of companies based on whether portfolios of their tech peers were outperforming or underperforming the market.
Sure enough, the researchers found, the strategy worked. Going “long” on companies with good tech peers and “short” on companies with weak ones generated monthly returns that were 1.17% higher than those for other investments with comparable risk factors.
The researchers say this tech-peer momentum is distinct from the momentum of a particular industry or category of investing, such as growth stocks or large-cap stocks.
The study found that the tech-peer strategy does best at predicting stock movements over the next six months, though the predictive power fades in looking further ahead. The researchers also found that the investing strategy works better for companies that attract relatively little scrutiny from analysts and professional investors. That’s because information lags become much shorter when more people are paying close attention.
The main insight, Lee says, is that tech-heavy companies can be both more similar and more different than they appear on the surface.
“Firms that compete in different markets and industries, firms that you wouldn’t think of in the same breath, are actually quite close in terms of their technological expertise,” Lee says. “Their fortunes are going to move together.”