A revitalization in the hedge-fund industry may be more dependent on machines than humans.
After years of outflows, new reports show many of the larger funds and their current and prospective investors, are keenly focused on words like "quant" and "data science."
As one indication, take a look at this chart that was highlighted in a recent client report by Jefferies that was obtained by CNBC. This is based on Google Trends, showing the relative interest in the words "hedge fund" versus "data science."
"2016 seems to have marked a tipping point for the hedge fund industry's mainstream embrace of data science," Jefferies wrote in the report from June.
Data science essentially means using large amounts of data for making investment decisions. It's largely a catch-all term employed by many industries — not just hedge funds — to indicate mathematical and computerized methods for collecting and analyzing information.
For hedge funds, this expands beyond traditional spreadsheet models. Hedge funds are employing machine learning, where computers can detect patterns and alter investment decisions accordingly, largely through algorithms. Some funds are using a human approach but sifting through alternative data — or sources not considered traditional in finance like annual reports — to manage their portfolios.
For hedge funds, data science may be a big part of the comeback story. At least that's what investors are hoping.