Real-Time Analytics A Must-Have
Regulatory and customer demands for transparency drive technology adoption.
Capturing and making sense of real-time market conditions and event data are driving the adoption of technology for performing real-time analytics.
StreamBase, a provider of complex-event processing (CEP) technology, has launched StreamBase LiveView, which enables firms to address the challenges of managing high speed order flow and reacting in real-time.
Instead of processing trading data in batch mode either intra-day, or after market close, StreamBase LiveView is designed to constantly provide a real-time view of today’s highly automated and complex trading environment.
StreamBase LiveView is deployed globally at a top-tier investment bank to manage trading operations risk in real-time by creating a live, firm-wide warehouse of trading events.
“We’ve been working for the past nine months with a top-tier bank that wanted the capability to monitor their global trading activities ,” Justin Fry, senior vice president of marketing at StreamBase, told Markets Media. “We developed a solution that enables the bank to have a single unified view of the data, and be able to access it in real-time to perform stored and ad-hoc queries.”
StreamBase LiveView consumes data from streaming real-time data sources, creates an in-memory data warehouse, and provides push-based query results and alerts to end-users.
At the bank for which it was developed, StreamBase LiveView handles around 10 million trading events a day, streaming from 12 event-based systems within the firm, said Fry.
“The data is stored in an in-memory system and made available to users via a desktop client,” he said. “It’s as near real-time as you can get.”
Regulatory drivers and customer demands for greater transparency are leading banks to invest in real-time analytics.
“If an order is not being completed or showing signs of execution difficulties then the bank needs immediate insight into what happened,” said Fry. “With this sort of live capability, the trading operations group can track down and resolve order issues rapidly, improve customer service and help the bank to satisfy regulators and win order flow.”
Analytics providers have been packing more punch into their systems, including advanced statistical programming.
Sybase, for example, has embedded support for the R statistical programming language within Sybase RAP—The Trading Edition, an analytics server for financial services.
Fincad earlier this year launched F3 Toolbox for use with MATLAB, which gives MATLAB users access to Fincad’s F3 analytics library; MATLAB is a mathematical programming language that’s used by 2,300 financial firms to develop quantitative trading strategies.
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