A giant hedge fund used artificial intelligence to analyze Fed minutes ? here's what it found
The giant hedge fund, which manages $35 billion, is as much a technology company as it is a hedge fund.
It uses advanced technologies to find investment opportunities, and just hosted its annual artificial intelligence competition.
One of those technological applications involves using natural language processing (NLP) techniques to analyze the Fed minutes, like those published Wednesday afternoon.
"Historically, interpretations of those minutes required art, so Fed watchers pontificated and critiqued," the firm said in a note. "Now natural language processing techniques can translate those minutes into relatively objective data."
Here are the key takeaways from the study (emphasis ours):
A bigger emphasis on financial markets -
At its peak in late 2008, the FOMC devoted nearly 37 percent of its meeting minutes to discussing financial markets, using words such as "securities," "credit," "dollar," "rates," and "mortgage." Since then, the share of the FOMC's attention has trended lower, though it has remained persistently above 20 percent during both the Bernanke and Yellen eras at the Fed. In contrast, the FOMC has reduced the relative fraction of its meetings dedicated to discussing growth.
Increasing attention to inflation -
During the 2007-2009 financial crisis, the FOMC devoted only 15 percent of its meeting minutes to discussing inflation. Since mid-2014, that fraction increased to more than 20 percent and, during the past few meetings, close to 30 percent. The other element of the Fed's dual mandate, employment, has persistently commanded less attention (~5 percent).
A split focus -
For the first time in the data set, four topics individually command more than 20 percent of the minutes: inflation, growth, policy, and financial markets. This might imply that these topics have become more interrelated today than in the past. It might also reflect a societal trend towards multitasking. Either way, the job of Fed watchers appears to have become more complex.
And here is a chart showing the change:
