Financial Market Data Web Services – Xignite Blog

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.”

NASDAQ discusses it’s market data cloud initiative with Max Bowie
of Inside Market Data at the 2010 SIFMA Financial Services Technology Expo

Obtaining and collecting tick data can be onerous and time-consuming as firms are required to establish feeds and maintain large amounts of data on-hand. On-demand market data distribution gives applications a way to cherry pick the specific subset of data that the application needs with pinpoint accuracy. Instead of combing through very large data sets of historical tick data, developers will be able to program their applications to select very specific data sets and obtain them on-demand and process them instantly. Data-on-Demand will also allow clients to download large tick data subsets on a scheduled basis.

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.”

Pete Harris of the A-Team Group interviews CME Group, BG Cantor and Xignite.
The A-Team Group gave the cloud prime coverage in their recent Q2 issue,
and Pete is launching a new “Market Data Cloud” channel, so stay tuned to that.

CME Group plans to offer on-demand access to end-of-day OTC settlement, volume and open interest data to support markets available through CME ClearPort®, a set of flexible clearing services open to OTC market participants to substantially mitigate counterparty risk and provide neutral settlement prices across asset classes. CME ClearPort currently clears more than 500,000 contracts daily, including Credit Default Swaps (CDS), energy, metals, agricultural commodities and foreign currencies. The service brings together more than 10,000 global users across the world including banks, hedge funds, trading entities, Inter Dealer Brokers (IDBs), Future Commission Merchants (FCMs), and clearing firms.

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.

Mass Customization and Market Data

According to Wikipedia, mass customization is about providing “services to meet individual customer’s needs with near mass production efficiency” by offering a “tremendous increase in variety and customization without a corresponding increase in costs.” Or rather, have it your way at a cost you can afford. In the last installment in this series entitled Thinking Out Cloud – The Market Data Sweet Spot, I pointed out that the best way to identify market data that can benefit from cloud computing is to look for data that is hard-to-use, hard-to-manage, and hard-to-access. Mass customization on the cloud strikes at the core of the “hard-to-use” problem by replacing inflexible data feeds and files in static formats with financial Web services that allow applications to select and consume highly customized market data sets on the fly.

Mass Customization, Meta Data and Web Services

In software, mass customization is achieved by converting hard-coded application functions into meta-data, so that the functional behavior of the software can be controlled through data on an ad-hoc basis. For example, the only real difference between this Xignite Wordpress blog and a million other Wordpress blogs comes down to a few theme files and the store of data that comprises the brilliant blog posts within. The posts in turn get shuffled around the Internet using RSS (really simple syndication). The RSS standard lies at the heart of the Web 2.0 revolution, powering the distribution of widely varied content such as blogs, news, friends, tweets, music, video, etc., all because a few abstract meta-data elements like “title”, “description”, and “link” can be generalized to contain an enormous and disparate variety of data. Swapping out this data can literally change one blog to any other blog (or one friend to any other friend!).

In cloud computing, meta-data abstraction is realized through Web services (like RSS). Web services take the concept of configurability through meta-data abstraction to its natural limit, because every operation of a Web service is inherently abstracted to meta-data in the XML inputs and outputs of the API. For example, the Xignite delayed stock quote Web service allows applications to retrieve a single quote for a single symbol, multiple quotes for multiple symbols, intraday tick-by-tick prices, market volume and news, simply by varying the Web service operation and the input parameters, i.e., the meta data. Providing access to such a wide variety of information in an ad-hoc fashion from a statically formatted feed or file is simply not possible without lots of hardware, software and custom development–most likely to create a Web service.

Wrap it Up, I’ll Take It!

More plainly, market data Web services are built for mass customization, because they cleanly wrap the underlying market data and data management infrastructure in meta-data enabling highly customized output based on variable input. Therefore, applications that require highly varied, ad-hoc market data subsets will be better served by Web services over the static formats of data feeds and files. Or, as we like to say at Xignite: “There’s an op[eration] for that!”

If you look at our new corporate bond master service, XigniteBondMaster, you’ll quickly see that you can use it to get information for over 125,000 U.S. corporate bonds, including issuer information, maturity dates, coupon rates and so on.  But you’re not likely to see one of the best features of the service until you roll up your sleeves and start digging around in the data:  the ability to look up official CUSIP identifiers with remarkable ease.

CUSIP identifiers are highly valued throughout the industry as the de facto standard for uniquely identifying over 9.1 million financial instruments.  And now you can easily look up CUSIPs for thousands of corporate bonds using XigniteBondMaster.  Interested in a particular issue, but not sure what its CUSIP is?  Try looking it up by the bond issuer!  Or just look it up by bond name.

All CUSIP data comes from CUSIP Global Services, an organization managed by Standard & Poor’s on behalf of the American Bankers Association specifically to oversee the official set of CUSIP identifiers.

You do need to have an agreement in place with CUSIP Global Services in order to receive CUSIP data, since this is highly valued data that must be licensed first.  But once you have an agreement in place, CUSIPs will automatically start appearing in your XigniteBondMaster outputs.

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.

First, it’s important to recognize that it is not the market data that is being outsourced to the cloud, but the on-premise market data management infrastructure. Therefore, the market data sweet spot for cloud computing is the intersection of data management systems that offer little competitive advantage, but are costly and difficult to maintain in-house. Both relative competitive advantage and relative level of difficulty will vary from firm to firm by business focus and IT capability respectively; however, there are aspects of the market data itself that can contribute significantly to the cost and complexity of maintaining an in-house data management system.

Hard to Use Market Data

If the market data comes in original feed formats that are not well suited to the particular use of the data in the final application, then considerable effort must be expended to make the market data application-ready. For example, a real-time streaming exchange feed is great for creating a stock ticker, but not so great when the goal is to analyze historical tick data or simply get an ad-hoc real-time quote for a single symbol, then there can be lots of programming involved to parse the feed, store the data, continuously refresh the database and create a data access layer that applications can easily utilize. Cloud computing is built on Web services that allow for multiple interfaces to the market data, so it is especially good at tailoring the data format to the specific needs of the application on the fly. For example, a Web service request can be for a single price, multiple prices, or simply for symbol validation against master data.

Hard to Maintain Market Data

If the market data in question is stored and refreshed often due to daily activity, such as historical time series and tick-by-tick data, then it can entail a complex update process that must be maintained and monitored. Quality testing must be put in place to ensure data quality and alerts to ensure that update processes run successfully to completion. As market data accumulates, Read more

Cloud computing has graduated from technical curiosity to technology trend. According to a recent Gartner survey, cloud computing and virtualization sit squarely at the top of the list of 2010 CIO priorities. However, most financial services IT professionals are still taking a cautious approach to cloud computing. This is quite understandable given the high performance, security and compliance requirements of financial applications. Unlike Twitter, you can’t just post the fail whale when a financial application has an issue, because real money is at stake not just tweets. So, what financial applications are good candidates for cloud computing and why? To cloud or not to cloud? That is the question.

This is the first post in an series entitled Thinking Out Cloud with the aim of helping financial services IT and market data professionals charged with developing cloud computing strategies separate the cloud buzz from the cloud reality.

Focus on Competitive Advantage

Realistically, somewhere between 75% and 95% of the software used by most businesses today is a commodity. That is, it offers no competitive advantage because the competition has access to the exact same capabilities from a plethora of software vendors, SaaS vendors, open-source projects and home-grown systems. This means that if your financial services IT department does everything in-house, pretty much 75%-95% of your IT department’s hard work and budgetary expense offers a competitive advantage of exactly zero. Only the 5%-25% spent on systems that help your business stand out from the competition make a real difference to top line revenue. Yet, I’ve never seen a financial services IT department that had extra time on its hands. Therefore, the first consideration in any analysis of cloud computing should be to weigh the competitive importance of the various systems under IT management, and to look for opportunities to free up resources by pushing systems that do not offer competitive advantage to the cloud.

Leverage Cloud Computing to Lower Costs

The primary financial benefit of cloud computing is lower total cost of ownership created through the economies-of-scale of shared computing resources. It makes no difference if it is infrastructure from Amzaon AWS, CRM from Salesforce.com, or market data from Xignite, the underlying common thread is that these vendors can do it significantly cheaper by the dozen than customers can do it in-house one at a time. This cost savings is then passed onto the customer in the form of an ongoing usage-based subscription. Conveniently, this prospect of lower overall costs fits nicely with the idea of outsourcing commodity systems. Therefore, the next consideration in an analysis of the benefits of cloud computing for a particular system should be the relative costs savings. It is critical at this point to Read more

Now that the cat’s finally out of the bag on BGCantor’s new on-demand web services, I can finally take the readers of the Xignite blog back stage for a “behind the scenes” look at the making of the biggest initiative in the on-demand financial web services world since the start of Xignite.

BGCantor On-Demand offers fixed income and derivatives data via on-demand web services using Xignite’s core platform.

What happened behind the scenes?  How did this new on-demand business get launched?  And what did it take to launch it?  Well, first and foremost, it took a great team at BGCantor Market Data.  The BGCantor team was absolutely delightful to work with.  Everyone was highly knowledgeable, very responsive, dedicated to accomplishing the mission and very excited about the whole project.  We couldn’t have asked for a better group to work with.

Together, the BGCantor/Xignite team started by designing web services to be truly application-ready, combining Xignite’s web service experience with BGCantor’s in-depth market data knowledge.  Then we coded the web services on top of the XigniteOnDemand market data distribution platform for rapid development on a robust, high-performance, highly scalable architecture.  At the same time, we also built the BGCantor On-Demand website and tightly integrated it with the web services themselves.  To help manage the new on-demand business, we also deployed an administrative portal for on-going management of customer accounts.  At the same time, on the sales and marketing front, we worked together to find just the right usage-based pricing model to drive strong revenue growth for BGCantor while also delivering exceptional value for BGCantor’s customers.  Then we collaborated on developing marketing collateral and sales tools.

As for showing you blooper videos of our behind-the-scenes footage, I’m afraid I couldn’t quite convince Legal to sign off on that. Sorry. Maybe next time.