Selling data these days is like selling ice to the Eskimos. Like arctic ice, data is everywhere. Market data not only comes from aggregators and exchanges; firms are becoming more active in the data market as they try to reduce latency and enhance their direct-to-customer technology offerings.
Market data velocity is exploding as decimalization and advanced execution (aggregation and algorithmic trading) have reduced the number of shares per trade and increased the number of data-generating events. Data sources are also increasing as firms move toward exchange feeds as even the slightest latency puts them at a disadvantage. Simultaneously, the amount firms are willing to pay for data is declining, as fewer traders means lower terminal revenues, and as institutions renegotiate contracts while commissions and trading profits fall.
Market data is not the only culprit in this data sprawl. Studies continue to show that reference data is one of the leading causes of trade failures. Reference data tends to challenge efficiency as the multitude of trading and processing systems and the complexity of the technology infrastructure make it difficult to have a consistent corporatewide data infrastructure.
On one hand, firms are awash with expensive, real-time, screen-based data that doesn't align with advanced execution. On the other hand, they have an infrastructure that demands clean and consistent reference data that they can't get. So what's a firm to do?
Firms need to look at their data infrastructures as processing workflows. They need to think about their data in a straight-through manner and create a market and reference data architecture. The data architecture is not just a collection of off-the-shelf and vendor technologies; it is a ground-up analysis of business requirements and the technology needed to satisfy those needs. It requires an understanding of need, use, latency, source and brand, married with technology, connectivity, bandwidth and cost. Data needs to be thought of as a precious commodity - and managed as such.
Not only do firms need to understand their data needs and architectures, but data vendors need to change their product sets as well. Vendors must rethink their offerings, looking at their product sets as industry offerings that link with other providers, other formats and other protocols. Just as openness has changed order-management systems as firms look to seamlessly integrate execution management systems into the order-management environment, market data platforms and vendors need to determine a lingua franca that enables the seamless interchange of market, customer and other reference data.
Pricing models also need to change, as real-time data, especially equity data, will need to be sold by the feed rather than by the terminal. Redistribution models need to be more easily negotiated as dealers and other service providers develop client-facing technologies, and closed platforms need to be opened so firms can more easily rationalize, harmonize and integrate data sources.
That is not to say that market and reference data is a free commodity - far from it. However, the way that vendors offer content, add value and set prices has to be more tightly aligned with usage requirements, needs and client-value propositions. The transition will be difficult, but so are the times. Just ask a NYSE specialist, a NASDAQ market maker or a software developer.
As these models settle down, however, the market for data will change, and new opportunities will present themselves and disappear - just like ice floes in the arctic. The key is to bring the floes together to create a larger whole that benefits all, rather than getting stranded on the isolated iceberg drifting out to sea.
Larry Tabb is founder and CEO of Westborough, Mass.-based The Tabb Group, a financial-markets strategic-advisory firm. firstname.lastname@example.orgLarry Tabb is the founder and CEO of TABB Group, the financial markets' research and strategic advisory firm focused exclusively on capital markets. Founded in 2003 and based on the interview-based research methodology of "first-person knowledge" he developed, TABB Group ... View Full Bio