London, 13 April 2021
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, who directs product development 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.
About BMLL Technologies
BMLL Technologies is the leading, independent provider of harmonised, Level 3 historical data and analytics to the world’s most sophisticated capital market participants.
BMLL offers banks, brokers, asset managers, hedge funds and global exchange groups immediate and flexible access to the most granular Level 3, T+1 order book data and advanced analytics, enabling them to accelerate research, optimise trading strategies and generate alpha at unparalleled speed and scale.
Founded in 2014 in the machine learning laboratories of the University of Cambridge, the platform enables researchers and quants across global financial services firms to apply complex statistical techniques to BMLL’s unique big-data sets with applications such as market impact, pre & post trade analytics, order book simulation and compliance. Users no longer need to buy, curate and harmonise data. With BMLL, they gain cost-effective, instant access to a cloud-native Data Science environment via a single web portal, with a long history of the most granular, full order book data across global equities, futures and ETFs for back-testing and simulation, delivered directly into their workflows.
About École Polytechnique
École Polytechnique, also known as L’X, is the leading French institution combining top-level research, academics, and innovation at the cutting-edge of science and technology. Its various undergraduate and graduate-level programs – Bachelor of Science, Ingénieur Polytechnicien (Master’s level program), Master’s, and PhD – are highly selective and promote a culture of excellence with a strong emphasis on science, anchored in humanist traditions. As a widely internationalized university, École Polytechnique offers a variety of international programs and attracts a growing number of foreign students and researchers from around the globe (currently 40% of students and 40% of faculty members).
École Polytechnique offers an exceptional education to prepare bright men and women to excel in top-level key positions and lead complex and innovative projects which meet the challenges of 21st century society, all while maintaining a keen sense of their civil and social responsibilities. With its 23 laboratories, 22 of which are joint research units with the French National Center for Scientific Research (CNRS), the École Polytechnique Research Center explores the frontiers of interdisciplinary knowledge to provide major contributions to science, technology, and society. École Polytechnique is a founding member of Institut Polytechnique de Paris.
Notes to Editors
About Mathieu Rosenbaum
Mathieu Rosenbaum is a full-time professor at École Polytechnique, where he holds the chair “Analytics and Models for Regulation”. He obtained his Ph.D from University Paris-Est in 2007. After being Assistant Professor at École Polytechnique, he became Professor at Sorbonne University.
Mathieu Rosenbaum’s research mainly focuses on statistical finance problems, such as market microstructure modeling or designing statistical procedures for high frequency data, volatility modelling and on quantitative regulatory issues, especially in the context of high frequency trading. In particular, he is one of the organizers of the conference “Market Microstructure, Confronting Many Viewpoints“, which takes place every two years in Paris.
Mathieu Rosenbaum has collaborated with various financial institutions, notably BNP-Paribas since 2004. He also has several editorial activities. He is one of the editors in chief of the journal “Market Microstructure and Liquidity“. Furthermore, he is managing editor for “Quantitative Finance” and associate editor for “Electronic Journal of Statistics”, “Journal of Applied Probability”, “Mathematical Finance”, “Mathematics and Financial Economics”, “Statistical Inference for Stochastic Processes”, “SIAM Journal in Financial Mathematics”, “Springer Briefs” and “Statistics and Risk Modeling”. He received the Europlace Award for Best Young Researcher in Finance in 2014 and the European Research Council Grant in 2015. He also received the 2020 Louis Bachelier Prize.
Mathieu Rosenbaum and Jim Gatheral won “Quant of the Year” at the 2021 Risk Awards.
A complete list of papers can be found at his page http://www.cmap.polytechnique.fr/~rosenbaum/