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We are delighted to announce that BMLL has won “Best Data Science Solution” at the annual HedgeWeek European Awards 2024. These awards recognise excellence among fund managers and service providers in Europe across a wide range of categories.
BMLL was awarded “Best Data Science Solution” for providing Level 3 data and analytics to hedge funds, helping them improve predictability, quality and speed of alpha through a scalable, managed data and analytics service.
Specifically, BMLL helps quant teams deliver predictive alphas: using BMLL’s suite of predictive analytics and scalable research, they can unlock patterns in market behaviour, improve signal generation and optimise algorithm performance at a fraction of the cost of building the capabilities in-house.
The award recognises BMLL’s support for start-up hedge funds such as Magma Capital Funds, who leverage BMLL’s data science platform to reduce set-up costs and shorten time to market, as well as its capabilities for supporting large systematic hedge funds with alpha generation and operational needs.
BMLL’s ready-to-use, quant-built data science platform, provides hedge funds with the necessary research infrastructure to support their specific operation and growth from the outset, without the high upfront costs and lengthy timelines normally associated with launching a quantitative or systematic fund.
Paul Humphrey, CEO of BMLL, said: “We are very excited to win the ‘Best Data Science Solution’ category at the HedgeWeek European Awards 2024.
Historically, hedge funds have built the data science capabilities themselves. However, young funds want to focus on the value-add rather than the complexity and cost of the in-house processes associated with curating and cleansing data, or managing and storing multiple copies of historical market data. Their core competency is research and finding an angle to generate alpha, the effort needed for data curation and data engineering is not where they want to spend their time and resources. They turn to us to provide them with historical data packaged with an analytics library and the ability to query and analyse the data to generate trading signals.
My thanks go to our incredibly talented team for their continued dedication towards developing our unrivalled data science capabilities.”
