Kepler Cheuvreux this week confirmed a collaboration with data and analytics provider BMLL to boost its order book analytics and improve algo performance.
The agreement gives Kepler’s quant team access to the BMLL Data Lab and granular Level 3 data in order to carry out advanced order book analytics and improve algo performance. The Data Lab provides over six years of harmonised historical data from 65 venues, combining it with APIs and analytics libraries and hosted on the cloud.
“Financial institutions across the capital markets are increasingly data driven. In order to understand how markets behave and make more informed trading decisions that benefit their end clients, they are becoming more sophisticated in how they make use of the most granular data sets. Only the most granular Level 3 order book data provides market participants with the necessary actionable insight needed to outperform the competition,” said BMLL CEO Paul Humphrey and Jean François Perreton, head of algorithmic trading quant at Kepler Cheuvreux, speaking exclusively to The TRADE.
“Many market participants are evaluating whether to build a data science platform internally or look to partner with a specialist firm like BMLL, with key decisions driven by cloud adoption or on premise deployment. Being cloud native isn’t simply about storing data, but being able to run large scale compute that makes quants up to 8x more efficient than running on existing legacy infrastructure.
“Quant researchers typically spend 80% of their time engineering data to make it usable for quantitative analysis. BMLL is changing this ratio, allowing quants to spend 80% of their time on data science not on data engineering.”