‘Big Data’ Alters Investment Research Landscape04.07.2015
The convergence of ‘big data’, technology, regulations and new market entrants are changing the research landscape and the relationship between the buy- and sell-side communities.
“Both the business and technology aspects of securities research are changing because the players and regulations are changing,” Alexei Miller, managing director of DataArt, a technology consulting firm, told Markets Media. “New technology is forcing its way into the business, which has not changed very much in the last 20 years, and now it’s changing pretty rapidly.”
The buy side has relied traditionally on the sell side for most of its research. For the last several years, though the buy side has been seeking out alternatives, either through independent providers or by deploying human power and technology to conduct their own internal research.
A major question is to what degree a machine or a computer can support and in some cases replace humans in the research process. “There’s been a lot of talk about big data and how all of this information is out there, both structured numerical data and unstructured,” Miller said. “This includes mining the web for insights, social media, filing, analyzing text, deriving intelligence from complex data structures such as supply chain relationships, etc.”
While for the traditional ‘bulge-bracket’ firm, building the technology infrastructure required to process this massive amounts of data is affordable, few buy side firms have the know-how to build it out.
“My expectation is that they will increasingly rely on third-party cloud infrastructure to process all of that,” said Miller. “I also expect to see quite a bit of consortium activity whereby both buy side firms and sale side firms will be pooling their resources to process all of this big and small data. Because they’re doing this same operation, it makes little sense to do it individually at each and every firm.”
Third-party providers and technology and research have had to take different approaches.
“A lot of people make this point that the amount of data is so large that they’re having trouble processing all of the data,” Miller said. “From what I observed in projects we do for our clients and the technical problems we’re facing, the actual processing of data is less of a problem. Technology, particularly that coming from open source has become so powerful, that it can process an almost infinite amount of data very efficiently.”
The bigger problem is not so much processing data, but figuring out what questions to ask. “A machine can find answers to almost any question, but people are struggling asking the right questions,” said Miller. “And building technology to answer all questions is a completely different problem.”
Alternative research providers are deploying crowdsourcing concepts to support investment research. Estimize, for example, provides crowdsourced earnings forecasts for certain stocks and other securities.
“There are community sites for investment managers and hedge fund managers who share their investment ideas and debate them in this protected sort of walled garden,” Miller said. “Those communities are fairly large, and I expect consumer players like Google and others to train their targets on this space soon enough.”
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