Quantitative equity firms this year are seeing their strongest inflows since the global financial crisis, and some managers predict their growing use of “big data” — or non-traditional data sources — could leave them better positioned than before to put hefty client allocations to work.
Exploiting a growing trove of newly available data — from Chinese investor blog posts on mainland stocks to Google searches for big-ticket items — has helped BlackRock Inc.'s quantitative equity strategies achieve “good results” over the past five years, with investments that are different from “a lot of other competitors,” said Jeff Shen, San Francisco-based managing director and co-head of investments for the firm's $80 billion scientific active equity business.
While declining to provide specific numbers for outperformance, Mr. Shen noted that more than 80% of the firm's SAE portfolios were outperforming their benchmarks on a three- and five-year basis.
With the continued availability of big data, and its promise of offering up different ways to harvest signals for investment, a real case can be made “for a revival of quant,” said Kevin Anderson, a Hong Kong-based senior managing director and head of investments, Asia-Pacific, with State Street Global Advisors.
The pursuit of “differentiated” portfolios is a case of “once bitten, twice shy,” Mr. Shen said.
Institutional investors' previous, passionate embrace of quant firms — between 2004 and 2007 — ended badly when a number of those firms' computer-driven models left clients with leveraged exposures to the same market segments.
When global equity markets unraveled starting in late 2007, the hangover for quant firms — in terms of client flows — persisted long after the damage to performance, which was mostly confined to 2008 and 2009. Flows for quant firms only turned broadly positive in 2014.