Last spring, Dow Jones launched a new service called Lexicon, which sends real-time financial news to professional investors. This in itself is not surprising. The company behind The Wall Street Journal and Dow Jones Newswires made its name by publishing the kind of news that moves the stock market. But many of the professional investors subscribing to Lexicon aren’t human—they’re algorithms, the lines of code that govern an increasing amount of global trading activity—and they don’t read news the way humans do. They don’t need their information delivered in the form of a story or even in sentences. They just want data—the hard, actionable information that those words represent.
Lexicon packages the news in a way that its robo-clients can understand. It scans every Dow Jones story in real time, looking for textual clues that might indicate how investors should feel about a stock. It then sends that information in machine-readable form to its algorithmic subscribers, which can parse it further, using the resulting data to inform their own investing decisions. Lexicon has helped automate the process of reading the news, drawing insight from it, and using that information to buy or sell a stock. The machines aren’t there just to crunch numbers anymore; they’re now making the decisions.
That increasingly describes the entire financial system. Over the past decade, algorithmic trading has overtaken the industry. From the single desk of a startup hedge fund to the gilded halls of Goldman Sachs, computer code is now responsible for most of the activity on Wall Street. (By some estimates, computer-aided high-frequency trading now accounts for about 70 percent of total trade volume.) Increasingly, the market’s ups and downs are determined not by traders competing to see who has the best information or sharpest business mind but by algorithms feverishly scanning for faint signals of potential profit.