As someone who grew up a blue-collar kid in New Jersey, I have very special memories of Bruce Springsteen. But most people don't remember that his first two albums were considered commercial failures. Many critics used that sales data to predict he wouldn't succeed. But in 1974, while The Boss was struggling, music critic Jon Landau wrote something very prescient after watching him perform: "I saw rock and roll future and its name is Bruce Springsteen. And on a night when I needed to feel young, he made me feel like I was hearing music for the very first time." What did Mr. Landau see that others had missed?
Predictions are important in the hedge fund business, too, and we often come up with them by accumulating a wealth of data. In the early 1980s, investors who found data others did not were the winners. However, in the past 10 years we've seen such an explosion of data that the edge for humans finding this hidden data is no longer enough. Computers are probabilistically forecasting what the data will be before it is announced.
The active management industry is filled with media headlines on the arms race of data and artificial intelligence. Hundreds of millions of dollars are pouring into the search for the holy grail of predictions through data. If we're not careful, the end of this race will look a lot like the gold rush, with a few winners and many more losers. Indeed, many large, successful quantitative funds have been doing this for decades and already have scraped much of the available alpha chicken off the bone. Meanwhile, we're seeing plenty of competition outside the hedge fund industry coming from algorithm builders who are providing data. This increased competition to immediately connect asset prices to real-time data will continue to lead to shorter and sharper investment cycles, as evidenced in the chart below.