In 2011 the cloud finally went from an unproven curiosity to an accepted mainstream technology solution. In 2012 we will witness the deepening penetration of the cloud into the consciousness of multiple industries. The market data industry is an interesting case in point because the major industry trends are all pointing to the rapid adoption of an on-demand cloud-based market data solution.

Let’s review each of these trends individually to understand how important the cloud will be for the market data industry in 2012:

1. Market Data Supplier Economics

The suppliers of market data are in a state of flux. On one hand, the cost of business is soaring with the new technology resources required to support sky-rocketing message rates, microsecond execution, and new regulation. On the other hand, the exchanges are experiencing sluggish revenue growth. Traditionally exchanges had four distinct sources of revenue: 1.) execution; 2.) listings; 3.) clearing; and 4.) market data. Of these, only market data is growing, while the others have either completely dried up or are not likely to be a significant source of revenue in the future. The exchanges have responded to these unfavorable economics with a wave of consolidation in an attempt to reduce costs but the health of the industry depends on growing the revenue side of the equation. The exchanges understand that their best revenue strategy is to distribute their most valuable asset, market data, direct to consumers. This strategy has already seen success with the exchanges offering direct feeds, co-location, and other services to their low-latency clients. (more…)

Perhaps nowhere more in the diverse world of hedge fund strategies is the prospect of alpha decay more unsettling than at high-frequency trading firms. In many ways high-frequency trading firms are now facing a reality that other hedge funds with more esoteric strategies may one day face – too much money chasing a finite amount of alpha.

The End of the Hardware Arms Race

The latest figures indicate that high-frequency trading now accounts for somewhere between 60-70% of trading volume in the US. This is up from around 35% just five short years ago. High-frequency trading firms, that in the past have been among the most profitable on Wall Street, are now seeing that increased competition has crowded out many of their traditional strategies. High-frequency trading firms have responded by co-locating their black boxes and by throwing ever more expensive hardware at the problem. This approach has worked for some of the larger, better-funded firms, but only postpones the inevitable.

What will happen when this hardware arms race meets the laws of physics? The answer is that many of these firms will need to develop high-frequency trading strategies where alpha is still relatively abundant and competition less fierce. (more…)

Each of the three largest US exchanges, NASDAQ, NYSE and CME Group has recently announced its cloud strategy, but exchanges and financial markets as a group have been slow to get on the cloud bandwagon. Too slow given the potential benefits to their customers and their own needs to increase revenue, market transparency and competitive advantage. That according to a recent white paper released by The Melbourne Group entitled The Winds of Change in Market Data : Winning Cloud Strategies for Exchanges and Trading Venues.

The new NYSE Technologies’ Capital Markets Community Platform is a significant and bold IaaS play that aspires to become the Amazon Web Services for financial markets by leveraging the tight community and unique technology needs within financial services that so often prevent generic offerings like AWS and Azure from competing on Wall Street. NASDAQ and CME Group on the other hand have placed their initial cloud bets one level up on the cloud stack with data-as-a-service offerings, NASDAQ Data-on-Demand and CME Data Cloud respectively. (more…)

Xignite projects were nominated for three 2011 Inside Market Data Awards, securing wins for ‘Most Innovative Market Data Project’ for the launch of NASDAQ Data-On-Demand and ‘Contract Win of the Year’ for its work with CME Group.

For the past half decade, an innovative Silicon Valley market data provider named Xignite has been skating under the radar of the mainstream Market Data industry, quietly securing over 900 clients and millions in annual revenue.  While we have achieved monumental successes year-over-year, were not a company you frequently read about in the Wall Street Journal.  To this day there are some that have problems pronouncing our name (‘x’ like xray, ‘ignite’ like a flame, x-ignite).  Times, they are changing, and were excited to have our recent achievements acknowledged by so many in the industry, even some who cant say our name correctly. (more…)

Algorithmic trading firms were put on notice last Monday when Commissioner Bart Chilton of the Commodity Futures Trading Commission (CFTC) said that high frequency trading (HFT) and algorithmic trading firms should be made legally responsible for maintaining a minimum set of testing and monitoring standards to prevent future flash crashes.

The possibility that algorithmic trading firms may need to support new regulatory requirements highlights the rapidly growing importance of the market data cloud and new cloud services like NASDAQ Data-On-Demand for back testing purposes.

In a bid to resuscitate the heroes of 1980’s sitcoms, Mr. Chilton declared, “I want to be like MacGyver. Remember, he was always trying to prevent crime before it happened.” So if you’re a criminally culpable algorithmic trading firm, you’d best beware—especially if Mr. Chilton gets his hands on a paper clip and a stick of chewing gum. Household items aside, Mr. Chilton also plans to rely on tools such as a “kind of Good Housekeeping Seal of Approval.” He’d like algorithmic trading systems to be tested by either exchanges or regulators before going live. And after going live, he’d like algorithmic trading systems to be monitored on an on-going basis. (more…)

This week NASDAQ was the first major exchange to launch an on-demand service offering Level 1 historical stock tick data.  As the first truly on-demand service for historical stock tick data, NASDAQ Data-On-Demand is leading a revolution that’s democratizing access to market data and reducing costs by orders of magnitude.

NASDAQ Data-On-Demand has made it easy and affordable to get access to historical stock tick data for everyone from individuals to large institutions.  Individuals can analyze historical stock tick data in Excel, while large institutions can develop large-scale applications like algorithmic trading applications, using NASDAQ Data-On-Demand’s historical stock tick data for back-testing their algorithms. (more…)

The was plenty of market data cloud buzz at the 2010 SIFMA Technology Conference and Exhibition with NASDAQ and Xignite right in the center. Using the XigniteOnDemand Market Data Cloud Platform, NASDAQ plans to launch Data-on-Demand in the second half of 2010 to provide easy and flexible access to large amounts of detailed historical NASDAQ Level 1 trade and quote data for all U.S.-listed securities. Tick data is increasingly in demand for back testing of algorithmic trading strategies as the securities industry pushes the limits of high frequency trading.

Randall Hopkins, NASDAQ OMX’s Senior Vice President of Global Data Products, is quoted in the press release as saying: “Today our customers spend a large amount on technology infrastructure, not the market data itself. With Data-on-Demand, we want to drastically cut data management costs by running the technology infrastructure on the cloud for our clients and delivering to them the data they need, when they need it, and how they need it.” (more…)

We’re proud to announce that CME Group, the world’s leading and most diverse derivatives marketplace, is jumping on the cloud computing bandwagon and has agreed to use the XigniteOnDemand market data cloud platform to deliver OTC data from the cloud.

Brian McElligott, Managing Director of Information Products at CME Group is quoted in the press release as saying “With the ongoing development of our multiple OTC product and service offerings, and the need to deliver this data to customers with continued market transparency, the Xignite platform will be a quick and cost-effective way to get OTC pricing and reference data to our global market participants.” (more…)

Henry Ford once said: “Any customer can have a car painted any color that he wants, so long as it is black.” Then, in 1923 Alfred Sloan came along and cleaned his clock by offering a tremendous variety in colors and models. But, Sloan didn’t do it one customer at a time. GM redesigned its manufacturing line with the flexibility to produce a multitude of models and colors without compromising the inherent economies-of-scale of Ford’s assembly line innovation—a practice that today has evolved into the concepts of flexible manufacturing and mass customization.

What does any of this have to do with cloud computing? And for that matter, what does it have to do with financial market data? This is the third post in a series called “Thinking Out Cloud” with the aim of helping financial services and market data IT professionals charged with developing cloud computing strategies separate the cloud buzz from the cloud reality. This post explores the important idea of mass customization in the cloud and its relevance to market data management. (more…)

Market data providers and IT professionals have tough jobs. Every day financial markets spew out huge fountains of data that must be captured, routed, scrubbed, reconciled, stored and redistributed with dizzying speed and accuracy. The diversity of data is staggering, from low-latency pricing data for algorithmic trading to intermittent corporate actions such as stock splits, and from globally dispersed real-time currency exchange rates to aggregated end-of-day VWAP and NAV calculations. Optimizing and tuning the market data systems that keep this crucial information flowing smoothly and cost effectively is no easy task. What, if anything, can cloud computing offer to ease the challenge?

This is the second post in a series called “Thinking Out Cloud” with the aim of helping financial services and market data IT professionals charged with developing cloud computing strategies separate the cloud buzz from the cloud reality. This post explores the types of market data that naturally lend themselves to cloud computing (and those that do not) in order to identify the market data sweet spot for cloud computing.

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