Gather requirements
Determine required figures and information gaps together with traders
Operational real-time analytics system for a bond desk.
The system processes a gap-free Bloomberg market-data stream, runs optimised calculations with latency below one millisecond and delivers current figures directly to traders' screens.
The project began with figures that were too slow, stale or unavailable on the bond desk's screens. For each requirement, the team worked with the traders to determine what information was needed during live trading and how it should fit into the existing workflow. This led incrementally to a real-time analytics system covering the complete path from Bloomberg market data to the traders' screens.
For each figure, the required Bloomberg data was connected to the streaming platform, processed in the live stream and monitored for completeness; detected gaps were recovered. Calculation optimisation was a particular focus. Existing time-consuming calculations were analysed, restructured and implemented as efficient live-stream transformations to reduce latency to below one millisecond. The results were then published to the traders' systems and visualised for direct use in the workflow.
The result is an end-to-end, operational real-time analytics system extending from the Bloomberg feed to the trader's screen.
From an information need to a live figure
The visualisation shows a typical agile delivery process. Requirements are gathered together with the traders, implemented and refined over several iterations. The result is an operational solution for live trading.
Project profile
- Project context
- Before Nuitio
BloombergFront ArenaMarket dataData streamingELTLow-latency computing
Your point of contact
Talk to Tobias about your real-time analytics
Send Tobias a short note about what you have in mind. In an initial conversation, we discuss the project and possible next steps.
PhD, ETH Zürich · Financial Risk Manager · IMD Future Leaders