Big Data Doesn’t Automatically Mean Big Investment Returns

The quant craze in investing doesn’t come without its own set of challenges, says a recent Bloomberg article.

As hedge funds delve headlong into the data world to hoist up returns and stay competitive, some may lack the prowess necessary to harvest relevant and accurate numbers, says Matei Zatreanu, who led the charge at $19 billion hedge fund King Street Capital Management. “There are those who realize their industry is changing and their fund isn’t going to exist if they don’t adapt,” he says, adding, “but not many of them know what they are doing, except a few.”

The problem comes with the integrity of some information collected. It’s not as simple as tracking credit card charges or foot traffic into restaurants. There can be errors—Zatreanu cited one example in which transaction data for restaurant chain Cracker Barrel included those for the Nutcracker Ballet. The data can also be legally suspect, as some vendors may not have the required consents from customers to sell it.

James Holloway, founder of quant fund Piquant Technologies in London, argues, “Humans have created a huge amount of low-grade data recently, but have failed to realize the rule that quantity does not equal quality.”

The role of scientists has become very important in the big data effort, the article asserts. Zatreanu believes that hedge funds should “give data scientists more gravitas” and foster a closer and better relationship between the firms’ management and scientists. Managers and “quants,” he says, “struggle to understand each other.”