Delivering The Next-Generation of Real-Time Applications in Capital Markets

The Case for Complex Event Processing

As capital markets continue to be fueled by innovations in technology and the new business opportunities they present, market participants find themselves in a new type of arms race.

Not only do they need to respond to market activity with low latency but they need to be able to handle massive volumes of data, understand the complexities of new financial instruments and find new ways to make money.

Complex Event Processing (CEP) is the latest evolution in the technology domain that is enabling companies to handle their IT infrastructure and support business needs alike.

This series of podcasts will cover the trends in the marketplace, the challenges and opportunities facing market participants and the applications of technologies relating to CEP platforms.
 
1.       Market and Technology Trends in Capital Markets; moving from batch processing to event-driven architectures; integration of grid computing with dynamic business functionality; transparency and liquidity across the marketplace

2.       Use cases for Complex Event Processing in financial applications, including: Real-time processing (normalization, cleansing, enrichment) of vast quantities of market data; correlation analysis for algorithmic trading opportunities; low-latency order routing and execution; real-time pricing & risk management; fraud and compliance applications; service Level monitoring

3.       Challenges in using CEP technologies, and how to decide on a platform: What is needed to make CEP engines work in the enterprise ? What features should be considered in selecting a CEP platform ? What is coming down the road in the next 6-18months ?

4.       Building flexible, high performance applications: What are the core components in the next generation trading room architecture and how do the integrate with one another ? Where does really CEP fit into the high throughout, low latency picture – is CEP the solution to every problem ? How do you scale an application while retaining flexibility and responsiveness to changing business needs ?

5.       Data visualization and control of automated trading businesses: How do you control a fully automated trading environment ? What architectural and application controls are needed ? How do you deploy new or modified business logic ? How do you visualize the vast and complex data sets in real-time ?