Thinking Out Cloud – The Market Data Sweet Spot
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
No commentsThinking Out Cloud – To Cloud or Not to Cloud in Financial Services?
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
No commentsBGCantor On-Demand: A “Behind the Scenes” Look
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.
No commentsRevenge of the Red-Headed Stepchild: Corporate Actions
Like the red-headed stepchild of reference data, corporate actions have been easy to neglect for many years, given the time, expense and difficulty of automation. That is, until the financial crisis combined with globalization to turn corporate actions into a high-priority risk factor. Like a red-headed stepchild turned Class A felon, corporate actions now threaten portfolios with greater risk than ever.
Before the crisis, globalization had already brought corporate actions to the breaking point. Portfolios filled with a wide array of securities from companies around the globe naturally required a way to handle corporate actions from a wider array of companies adhering to a wider array of standards and regulations. Let’s face it. It’s not easy to build automated systems to handle an increasingly diverse set of data delivered through an ever more diverse set of technology standards. So, it was easy for corporate action automation projects to fall off the bottom of the priority list.
But now, with the global financial crisis in full swing, the good old days of being able to neglect corporate actions appear to be over. As companies seek to respond to the crisis, they’re issuing a flood of new corporate actions to reorganize, inject new capital, retain cash and accomplish a host of other creative financial solutions. For investors and asset managers, it’s as if the red-headed stepchild is on a rampage, knocking over IT’s system building blocks, breaking analysts’ economic models for valuing securities, and generally making asset managers lose their hair.
I wish I could claim it was prophetic that we timed the release of XigniteCorporateActions to coincide with the up-surge in demand we’re seeing for automating corporate actions, but it was really more a matter of luck than foresight. Still, it’s hard to imagine a time when on-demand financial web services for corporate actions data was needed more than right now.
So, if your red-headed stepchild has been begging to go to juvie in recent months, here’s a little tough-love parenting tip: Don’t waste the next nine months trying to build your own data management prison to contain your corporate actions problems. Just dial the Xignite emergency number and ask for an on-demand web service that can lock up your corporate actions problems in a matter of weeks instead of months.
No commentsMarket Data Feeds vs. Web Services – Why buy the cow?
Many of the folks visiting our website looking for market data have previous experience with more traditional (or as we like to say legacy) data feed technology, but have not used Web services. Or, they are new to market data in general and have difficulty cutting through all the technical detail and marketing-speak to make an honest appraisal of what is best for their application. If this sounds like you, then take a look at this quick side-by-side comparison below.
To make a sound business decision, you need to ask yourself the practical question of “Why should I buy the cow, when I can get the milk through the fence?” In truth, there can be very good reasons for buying the cow. For example, you drink an awful lot of milk. Or, maybe you are also a really big meat eater. But, if your business isn’t dairy farming, then you are usually better off just buying the milk.
One often confusing element that is worth clarifying is that on-demand Web services are not only Web services, they are also on-demand. That is, many market data vendors bundle application programming interfaces (APIs) in wih their feed products (often as a free add-on). And, some of these APIs may support Web service standards or at least provide XML formatted output. However, this does not change the business economics of buying data in bulk and deploying and managing the infrastructure to host and distribute it yourself, versus accessing it one transaction at a time over the Internet.
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