Machines taking over hedge funds despite lack of evidence they outperform 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."

"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.

Based on a biannual Credit Suisse survey, it appears that a comeback is in store. The firm said 81 percent of investors it surveyed said they would likely make allocations to hedge funds during the second half of 2017, an increase of 8 percent from the mid-year survey last year. Of those investors surveyed, almost 60 percent said they plan to increase allocations to quantitatively focused strategies over the next three to five years.

Quantitatively focused funds have doubled their assets since 2009 to nearly $1 trillion – or about one-third of the industry's total assets – according to Jefferies.

As non-quant assets have ticked down, those funds using more of a scientific approach have skyrocketed, a trend that is likely to continue.

To be sure, just because a hedge fund has a quantitative strategy does not guarantee returns. A recent Barclays report showed that while investors perceive quant strategies outperform those that are less technology-driven, there's no research that would indicate that is actually the case.

In the first half of the year, so-called systematic diversified strategies, or those that have investment processes managed almost entirely by computers and have very little human influence over portfolio management, underperformed other strategies, according to new data by Hedge Fund Research Inc.

The HFRI Macro: Systematic Diversified Index declined 2.8 percent during the first half of 2017, while the broader industry gained 3.7 percent.

While the headcount, assets and interest appear to be growing, it doesn't appear that the returns are following suit.