About a-team Marketing Services
The knowledge platform for the financial technology industry
The knowledge platform for the financial technology industry

A-Team Insight Blogs

BMLL Offers Access to Normalised Level 3 Data and Advanced Analytics at Scale

Subscribe to our newsletter

BMLL Technologies, a cloud-based data-engineering-as-a-service company, has released a derived data service that provides access to normalised, highly granular Level 3 data and advanced analytics. Typically, the company’s derived data capability can process 225 billion messages in a matter of hours rather than days at a significantly reduced cost, allowing market participants to consume bespoke metrics derived from Level 3 message-by-message exchange data without the need to build and maintain internal infrastructure.

Designed in response to specific client requests, the BMLL derived data service provides a collaborative framework for customisable time series datasets and uses the most granular tick-by-tick data from primary equity and derivatives exchanges. This Level 3 data displays all the individual messages in the limit order book (LOB) and provides traders and researchers with extensive visibility into the workings of the market. Elliot Banks, chief product officer at BMLL, claims the service is unique in being able to combine public exchange data with a client’s private data to create bespoke derived data.

Offering point in time information at a very granular level, and analytics at speed and scale, the BMLL service is finding use cases including seeking alpha, working out transaction costs, spotting potential fraud, gaining visibility into order books, and understanding market quality in terms of behaviours, such as predatory trading, across exchanges and other trading venues.

The company says the service has already been adopted by eight Tier 1 organisations  including bulge bracket investment banks, asset managers, hedge funds, exchanges and academic research groups. Typical users are quants trading European equities and futures.

At the moment, users consume data from exchanges and venues across the US and Europe that has been normalised by BMLL in FTP files or on the company’s platform, where they can also access analytical tools. Looking forward, BMLL has plans to offer cloud-to-cloud data transfer and an application programming interface (API).

While BMLL takes the strain and clients can outsource processes of curation, normalisation, and data engineering for derived data, chief operating officer William L’Heveder says BMLL’s key deliverable is its ability to combine analytics with the market’s most granular datasets, do this at speed in the cloud, and deliver results of complex calculations quickly so that clients can make competitive decisions.

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: Re-architecting the trading platform for interoperability, resilience and profitability

Trading platforms have come a long way since the days of exchanging paper certificates and shouting across trading floors, pits and desks in the early 2000s, but there is progress still to be made as firms strive to reduce risk, increase profitability, and make their mark in digital assets trading. This webinar will review the...

BLOG

How Should Stock Analysts Use Prompts for ChatGPT?

Daniel Philps, Head of Rothko Investment Strategies and Co-Leader of Machine Learning at the Gillmore Centre for Financial Technology at Warwick Business School. 2023, termed Generative AI’s ‘breakout year,’ has seen generative AI techniques continually advancing, researchers are exploring new applications and pushing the boundaries of what can be generated. The latest annual McKinsey Global...

EVENT

AI in Capital Markets Summit London

The AI in Capital Markets Summit will explore current and emerging trends in AI, the potential of Generative AI and LLMs and how AI can be applied for efficiencies and business value across a number of use cases, in the front and back office of financial institutions. The agenda will explore the risks and challenges of adopting AI and the foundational technologies and data management capabilities that underpin successful deployment.

GUIDE

Institutional Digital Assets Handbook 2023

After initial hesitancy, interest in digital assets from institutional market participants has grown over the past three to four years. Early focus inevitably centred on the market opportunities presented by bitcoin and other cryptocurrencies. But this has evolved into a broad acceptance of a potentially meaningful role for digital assets in institutional markets. It’s now...