The post-crisis trading environment has industry pundits decrying many issues that have global implications, including cross-border risk management, ill-conceived approaches to market oversight and U.S. markets ceding valuable competitive ground. But at the heart of all the arguments swirling around Wall Street, Main Street and Pennsylvania Avenue is one irreducible point: time.
More so than at any other point in history, time is the friend and enemy of capital markets. And nowhere is the brute force of time playing out with more intensity than in the furious pursuit of quality real-time data in today's high-performance trading environments.
Managing the Data Deluge
Before organizations can fully address the performance challenges of real-time data access and analytics, they must address the quality and volume of the data to be analyzed. But the sheer volume and persistent incongruity of formats and sources severely complicate the task of aggregating and structuring that data.
Beyond the data deluge itself, a host of factors complicate the rush to greater feeds and higher speeds. The escalating hunt for quality real-time data is happening at the same time that other essential parts of the trading data/IT landscape are transforming themselves. Among the most important of these transformations:
- More Wall Street trading activity than ever is moving from public markets to private exchanges, where co-location and other factors fuel competi-tive access to real-time data. The NYSE currently handles roughly 25 percent of all trading on its own listed stocks, compared with 80 percent just six years ago. At least three dozen off-exchange venues have emerged in the last several years.
- Hardware acceleration and other technology advances, under way well before the financial crisis, are pushing feeds and associated analytics to the limits of physics, testing how much faster electrons--and therefore trading orders--can move through the wire.
- The evolution of complex event processing (CEP) over the last several years from nascent trend to a fact of life has had substantial implications not only for the trading life cycle, but for the vendor community as well.
- And there is the quest for smarter, faster, event-driven analytics through unlimited access to growing pools of structured and unstructured data.
The uniquely complex ecosystem of expanding capabilities and shifting alliances that define this arena is the focus of attention on the following pages. The authors of these articles look at several constituent parts of the real-time data ecosystem with a view to how these parts are shaping today's active capital markets world.
After decades of resistance, the silo's era seems to be entering the endgame. This places enormous attention on data extraction and execution from operational and outside sources not historically seen as integral to the front office P&L. The existence of unstructured or semistructured data calls for reimagining traditional relation-ships between formerly disparate parts of the enterprise.
This chapter also examines event data and its role in trading strategies. A complement to market data, event data provides a comprehensive view of current world events. Using the very latest computing technology to evaluate and trade upon event data has the potential to impact the capital markets in a material and time-saving way.
...and Putting It to Work in New Ways
The rapid ascent of high-frequency and electronic trading, as well as competition for alpha, continues to drive hedge funds, proprietary trading firms and other asset managers to identify new, differentiated data sets as core contributing factors in their real-time trading models. Firms hoping to prevail in today's markets are turning to new real-time content sets. These reside outside of classic market data paradigms, and firms are embracing them as sources of competitive differentiation.
Event data has crystallized as the leading real-time ingredient that firms are evaluating-- and increasingly adopting. The emergence of event-driven models and trading strategies is a particularly strong play for quant-focused firms, which tend to be well versed in rapidly absorbing and integrating data into their trading strategies in real or near real time.
The maturing of CEP, the topic of another article here, reflects the widely recognized importance of identifying event patterns and abstracting them in formalized ways--ways that can be consistently employed in real time. High- performance analytics databases will share an increasing amount of infrastructure with CEP technology. This chapter explores how such sharing increases efficiency by analyzing data as it streams and before it is stored.
From visualization tools to frameworks, new instruments are emerging to help both professional developers and end users save time by rapidly developing and deploying analytics applications. This chapter also discusses a new analytics programming language that does just that.
The imperatives of delivering and analyzing real-time data at unprecedented speeds and volumes drive much of today's capital markets agenda, in ways both manifest and as yet unrecognized. This is the time when the industry will determine just how quickly a trade can execute--and how best to harness that for competitive advantages.
Amid the many questions--and opportunities-- these new technologies raise, one thing is certain: Time will wait for no one.
About the Author: As executive vice president and chief marketing officer of Worldwide Marketing and Business Solutions Operations, Dr. Raj Nathan is responsible for all marketing initiatives for Sybase. Under his leadership, Sybase is recognized for visionary technologies that are helping to redefine the capabilities and profitability of the world's leading capital markets firms.