Opening Cross: Is ‘Fundamental’ Change Afoot for ‘Traditional’ Content?

Fundamental research, once second fiddle to low latency, is getting a second wind.


For the past decade, cutting-edge technical innovation in the market data industry has primarily been around the pursuit of low latency—in some cases, to the detriment of other fundamental datasets that might arguably have delivered better long-term returns. But as it has become more expensive to compete in the latency race, firms have begun looking for other sources of insight. As a result, the models by which datasets such as old-school fundamental research are produced and distributed are getting a facelift.

For example, years ago, Multex (now part of Thomson Reuters) revolutionized the delivery of broker research by providing access through a single portal. Then vendors such as Alacra pioneered the concept of online marketplaces for non-real-time premium content, while UK-based software consultancy Worldflow took this a step further with research apps and mobile access to research, responding to the emergence of wireless tablet devices that made research consumption feasible via mobile devices.

Now, London-based crowd-sourced investment platform StockViews is taking research a step further with a series of new initiatives: First, the vendor—which is introducing fees for accessing its platform—is improving real-time tracking of the research and recommendations on StockViews, adding a social media-style immediate feedback element to the research and analyst rating capabilities of the platform. In addition, StockViews is not limiting clients’ research choices to established firms or individual analysts, but is introducing features that allow users to search for analysts by their area of specialty or based on specific expertise, and the ability for users to pitch specific research projects and find the best-placed analysts with the most relevant experience to produce the research, essentially creating not just an online marketplace for research, but an interactive venue for custom content creation.

Once these “traditional” datasets are in new formats, one can use them in different ways, such as how New York-based AnalytixInsight is leveraging its database of research generated from fundamental company data and other metrics to create actionable indicators that firms can directly incorporate into trading strategies, in response to increased use of its CapitalCube platform by buy-side firms.

Similarly, crowd-sourced earnings estimates provider Estimize is beginning the process of working with BCA Research, the Canadian research subsidiary of Euromoney Institutional Investor, which recently took a 10 percent stake in Estimize. Though longer-term details aren’t yet available, the vendors are initially looking to incorporate Estimize’s data into BCA’s Edge research platform, combining BCA’s “top-down, macroeconomic research” with Estimize’s “bottom-up, crowd-sourced earnings estimates” to give a better indicator of stock price movements.

The upshot of all this is that, in my opinion, greater importance will be placed going forward on well-known types of data, but created and delivered in new ways, leaving vendors such as those described above well placed to deliver unique sources of alpha. Meanwhile, to extract value, search tools—such as those from search providers like 9W Search and AlphaSense—will become critical to finding the right piece of data. Once users have the right data, they can turn to analytics providers to correlate it with other datasets, or store it for future use—perhaps using Cloudera, which has allied with Corvil to store Big Data on network statistics, which could itself become an important dataset to be combined with other metrics. And to bring these capabilities and content sets together, look perhaps not to traditional vendor aggregators, but to on-demand platform providers such as Xignite and others, who can create professional-level portals using Web Services and widgets.

All this is technologically possible. Now all we need are commercial models that make it economically feasible so that the providers can make money while the consumers save money.

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