The amount of data available to us today leaves us constantly making choices—what data to use, how to use it, how much weight to assign it, and what delivery method is appropriate for the business case in question: is it more important, for example, to perform deep but time-consuming analytics, or to receive the raw data as fast as possible?
Until now, low-latency data for algorithmic trading, and sophisticated analytics on niche datasets for functions that aren’t yet automated have remained largely separate, albeit with some crossover in areas such as complex event processing and tick data analysis, which perform analytics on low-latency data streams. However, I suspect this crossover will grow in 2012 as firms specializing in each area seek out a new edge.
There are plenty of examples to support each side of the equation, and a few that demonstrate this emerging middle ground.
As an example of the scale of investment in low latency, undersea cable provider Huawei Marine Networks last week announced it had signed a deal to construct part of a new trans-Atlantic cable for Hibernia Atlantic, which is investing in a new cable infrastructure to reduce latency between the US and Europe, dubbed Project Express, which won’t even be ready until the middle of next year. Meanwhile, NYSE Technologies, the data and trading technology arm of NYSE Euronext, opened a new “liquidity center” in Toronto, to provide high-performance access to data and trading platforms from NYSE’s markets and other exchanges via its SFTI network.
Another function of these datacenters is to support the massive processing requirements of vendors and firms managing the ever-increasing amounts of market data being generated and consumed by the industry, and to provide connectivity between market participants, such as CME Group’s new datacenter in Aurora, Ill., which is building a “community” of service providers; or datacenter provider Interxion, which last week announced it will host Nordic data vendor Infront’s systems in its London and Stockholm facilities, to provide improved speed and connectivity; or Savvis, which just announced a deal to host BATS Global Markets’ backup datacenter in its CH4 Chicago facility.
Meanwhile, outside the latency race, the scope of analytics is growing. Last week, data and trading technology vendor Fidessa unveiled Fidessa Intelligence, a suite of analysis tools integrated with its sell-side OMS, while Swedish visualization and analytics vendor Panopticon released connectors for other analytics platforms, including Thomson Reuters’ Velocity Analytics, OneMarketData’s OneTick, Oracle CEP, and Sybase’s Event Stream Processor, reflecting the need to perform analytics across multiple platforms and sources.
But analysis requires underlying data, and vendors are increasingly seeing value in creating niche datasets—such as Data Explorers’ news feed of securities lending and short sale data; EPFR Global expanding the capabilities of its fund flows data; or GMI’s expanded analytics based on environmental, social and governance (ESG) data. And those who don’t already own niche data are snapping it up: Canadian exchange TMX Group acquired the assets of shareholder data provider IR2020, while Deutsche Börse’s Market News International business bought the China Consumer Sentiment Survey from Hyperlink Market Consulting (Shanghai), bolstering its suite of economic indicators.
Meanwhile, in an example that bridges the gap between low latency and analysis, technical analysis software vendor Updata has integrated low-latency data from Activ Financial, and we can expect to see many more such deals in future as these two camps meet in the middle, to create the best of both worlds. As Simon Ringrose, managing director of sales at EPFR Global, says, “It’s about smart use of the data, rather than just providing the data itself.”
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