BMLL, the leading, independent provider of harmonised, historical data and analytics, today announced a partnership with École Polytechnique to make its Data Lab available to their team of quantitative researchers. 

BMLL’s Data Lab is a data science platform that allows users to access over 5 years of Level-3 harmonised data, process it at scale, and find inferences by drilling down into every single message.  BMLL combines easy to use APIs and analytics libraries in a secure cloud environment, allowing scalable research without the burdens of data sourcing, curation or engineering. It seamlessly integrates with production tools and workflows, allowing researchers to efficiently unlock the predictive power of Level 3 data.

The École Polytechnique team is led by Senior Professor Mathieu Rosenbaum, a leading  quantitative analyst specialising in market microstructure modeling, who was named as a  “Quant of the Year” at the Risk Awards 2021. His most recent research is focused on high frequency markets, volatility modelling and financial regulation at the microstructure level. 

Paul Humphrey, CEO of BMLL, said: “We are delighted to partner with the École Polytechnique and support Professor Mathieu Rosenbaum and his colleagues in carrying out their research on market microstructure and specifically, the behaviour of limit order book data around specific events. This partnership is testament to the quality and depth of our Level 3 order book data, the ease of integration of our Data Lab with existing workflows and the ability to  turn the predictive power of data into actionable results.” 

Mathieu Rosenbaum, Senior Professor at École Polytechnique, said: “Marcos Carreira, PhD Candidate from the Quantitative Regulation chair at École Polytechnique, and I have worked with many different data providers, and the BMLL Data Lab is one of the cleanest historical data products we have seen.  It is very easy to use, and the documentation and support are superb.  The book reconstruction will be of great help, especially with all the interruptions to continuous trading that we have seen in the market.”   

Dr. Elliot Banks, Chief Product Officer at BMLL, said : “Researchers and quants are growing in influence in a world that is witnessing fast shifts in market regimes. Quant analysts understand the complex mathematical models relating to  price securities and are able to select the right data and parameters to generate profits and reduce risk.” 

Over the course of the project the team from École Polytechnique will have full access to the Data Lab, plus access to BMLL’s team of client facing data scientists.

Dr. Banks added: “We are proud to have created a tool that gives the world’s best researchers ways to collaborate and further explore the predictive power of historic data.  We look forward to the results of the research.” 

100 Heads of Data, Chief Data Officers, Data Scientists were recently surveyed to find out how buy-side participants use predictive data and analytics to improve alpha generation and mitigate risk in their daily trading decisions.  Over half (46%) of respondents said that the quant analyst was responsible for the integration and onboarding of new data sets and analytics within their organization. The full “Buy-side usage of Level 3 data analytics for algorithmic performance” survey is accessible here.