“Big data” — the seemingly endless and fast-growing sea of digital blog posts, tweets, texts and pictures — is on every quant firms' radar screen, but it looms larger on some than on others.
For BlackRock Inc., the world's biggest money manager, it looms very large.
It will take great investors and great systems to separate out new investment signals from the cat pictures and other useless information, but already “the additional stuff we have is having a material impact on how we invest, on how we run portfolios,” said Jeff Shen, managing director and co-head of investments for BlackRock's $80 billion Scientific Active Equity business.
Big data will “increasingly be necessary for great investment,” said Mr. Shen, who predicted a “transformational” impact on “how we think about investment.”
Kevin Anderson, Hong Kong-based senior managing director and head of investments, Asia-Pacific, with State Street Global Advisors, said his firm likewise anticipates profound opportunities. “We could potentially be entering a really enlightened age for quant investing,” anchored on the foundation of a strong partnership between quant and big data, he said.
Meanwhile, Messrs. Shen and Anderson, both executives with multitrillion-dollar firms, predicted scale could prove a benefit in making the most of big data.
Gatekeepers say they're waiting to be convinced.
Deborah Bannon, Mercer Investments' Hong Kong-based investments business leader for Greater China, said her money manager research colleagues have followed the efforts of numerous quant managers, including BlackRock, to “utilize big data in an intelligent way,” but none has provided evidence yet that those efforts are really adding value.
Others see potential for gains, but on a limited scale rather than anything transformational.
The possibility of a significant new investment signal being unearthed shouldn't be ruled out, but it's more likely that any “unique signals” found won't be “highly scalable,” relying on arbitrage opportunities that are smaller in nature or quickly arbitraged away, said Fabio Cecutto, Willis Towers Watson's New York-based global head of equity manager research. It's tough at this point to imagine any firm using big data to obtain a material or sustainable advantage, he said.
Some quant executives agree. “Most quant firms are trying to figure out how to use this data,” with little evidence yet that anyone has been able to put it to significant use, said Harindra De Silva, president of Analytic Investors LLC, Los Angeles.
“Note that none of the big risk modeling firms — BARRA or Axioma — has been successful in incorporate this type of data into their models,” said Mr. De Silva.
Smaller quant firms point to the limited likely scale of fresh arbitrage opportunities thrown up by big data as a reason why they may be better placed than a BlackRock or an SSgA to get the most out of big data.
“At large firms, the sheer size makes it hard for them to exploit small inefficiencies,” noted Mr. Harindra. “The larger the firm, the greater the size of the inefficiency you need to make a difference to your returns.”
Michael Even, CEO of Boston-based Man Numeric Investors LLC, struck a similar note, saying his firm, with roughly $20 billion in AUM, could benefit more by coming up with “one interesting thing” from its big data efforts than a competitor with $200 billion in AUM would get from a handful of interesting things. Man Numeric's more modest goals are looking to alternative data sources for ways to detect changes in fundamental inputs to the firm's models a little sooner — essentially seeking “better little pieces of the puzzle,” said Mr. Even.
And with big data compressing the time horizon of an informational advantage from a few months, to a few days, or minutes, or even a fraction of a second, the only ones who will benefit could be high-frequency traders, said William Jacques, president and CEO of Boston quant boutique Martingale Asset Management LP.