Looking through
the lens of big data
for alpha
As the largest asset manager in the world, BlackRock has been one of the pioneers over the past decade in exploring the potential of big data, and in particular, alternative data sources, for generating alpha.
Their success has spurred an increasing number of managers to turn away from the traditional methods of determining success, and embrace the growing hunger for data. “We’re still in the early innings of the game, but there’s more and more firms that understand the importance of analysing data, collecting data, and looking for ways to monetise it,” says Brad Betts, managing director and data scientist at BlackRock.
“I’m fond of a quote from Jim Barksdale, who was the old CEO of Netscape. He used to say, ‘If we have data to look at, let’s look at data. If all we have are opinions, let’s just use mine.’”
Every day, BlackRock’s active equity portfolio management team feeds approximately three terabytes of data into a series of sophisticated machine learning algorithms. These computer models mine the information for useful signals, and then return suggestions for how to optimise the current portfolio by trading and rebalancing.
This data is obtained through a variety of means. This can range from drone footage of oilfields to company executive transcripts in foreign languages that can be decrypted into stock predictors using natural language processing.
“We do a lot of data analysis at large scale to get us some insight in terms of how companies are really doing, using machine learning to read between the lines into whether the language is consistent between executives. But given we operate at scale, we also need to think very carefully about the market impact we have, when we demand liquidity in the stock. All these things feed into a very sophisticated optimisation process,” says Weinberger, managing director and portfolio manager at BlackRock.
“If we have data to look at, let’s look at data. If all we have are opinions, let’s just use mine.”
Jim BarksdaleBlackRock say that there are several reasons to why their methods are successful. One is that they are able to operate their models at scale, which gives them scope for investing so much money in purchasing data. “We carry out careful capacity planning of course,” Betts says. “But scalability of process confers a tremendous advantage.”
Another is that their philosophy is to go above and beyond how other managers are willing to use data to get a full picture of companies or consumer bases in different markets. “Across Asia we have developed capabilities to do natural language processing in all sorts of languages and that’s where the hard work comes in, and how you can really differentiate,” Weinberger says. “Europe is also still very fragmented.”
Their considerable experience over the past decade also confers an advantage in being able to evaluate whether new data sources which emerge are likely to be useful or not.
TEAM EFFORTS
BlackRock’s Systematic Active Equity team, which applies machine learning and AI to generate alpha, is currently made up of 80 people, making it one of the largest and more diverse teams within the asset manager.
Weinberger says: “We have people with traditional economics, finance and accounting backgrounds and we have people like Brad, who are experts in the field of data science. You really need both and you need a great culture. A culture of collaboration to be able to push things forward in the sense that we can continue to innovate, get better and as such, produce good results.”
But to be able to deliver superior results using the large amount of data it works with, BlackRock doesn’t operate alone and not through just one team – it continuously interacts with other specialists in the company as well as partners.
“We work closely with our internal partners inside BlackRock. We leverage tremendous power from our data teams, our trading teams and others,” Betts says.
“We can devote tremendous resource at BlackRock because of our skills. This is a huge strength and advantage that Simon and I surround ourselves with a diversified group of highly talented specialised colleagues and so, at BlackRock, we just can bring a scale to the problem that confers a tremendous competitive advantage
to us.”
[1] Source: BlackRock, as at April 2018.
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