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BMLL and Ultumus Partner to Enhance ETF Trading Analytics with Level 3 Data

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Market data and analytics provider BMLL has entered into a strategic partnership with Ultumus, a leading specialist in ETF and index data, to deliver a combined data offering aimed at improving trading efficiency and analytics for the global ETF community.

The collaboration integrates Ultumus’s widely used ETF reference and Portfolio Composition File (PCF) data with BMLL’s granular, historical Level 3 order book data. The move is designed to provide market participants – from asset managers to hedge funds and brokers – with a more powerful toolset to analyse ETF liquidity, pricing precision, and overall trading performance.

The partnership has already demonstrated tangible results. A leading European ETF issuer, using the combined datasets, was able to analyse and improve its spread performance, achieving a 16% reduction in spread threshold breaches and a 12% overall performance uplift.

This initiative represents a significant step in BMLL’s strategy to expand its asset class coverage, a plan bolstered by the $21 million strategic investment it secured last October. That funding round, led by major market maker Optiver, was earmarked for accelerating BMLL’s global expansion and product development.

For BMLL, the partnership is a strategic move to deepen its expertise in a crucial and rapidly expanding market segment. “In terms of ETFs as an asset class, we want experts like Ultumus to come and work with us because of our granularity and the quality of our data, where they can build then first-class insights on what is a massively growing asset class,” says Paul Humphrey, CEO of BMLL, in conversation with TradingTech Insight. “And that’s exactly where we want to be.”

The ability to prove a tangible return on data quality is the cornerstone of the partnership, explains Bernie Thurston, CEO of Ultumus. “Our PCFs are particularly data-rich, including holding, pricing, and settlement baskets. By working with BMLL, we can concretely demonstrate the value of this. We’ve proved that using a fully-featured, data-rich PCF like ours – compared to a more basic version from a custodian – can result in an average spread differential of about 16%, which we’re now able to show quite distinctly. And that obviously improves the relationship between the issuer and the market maker.”

Elliot Banks, Chief Product Officer at BMLL, explains what this means in practical terms for clients. “Users can finely slice and dice the data to understand how different segments are performing. It helps answer questions like: What does liquidity look like for active versus passive ETFs, or for UCITS versus other ETF types? Previously, you had to source and bundle different datasets to even begin answering that. What this partnership means is it becomes really seamless to do it.”

The explosive growth of active ETFs was a major catalyst for the collaboration, with providers needing to quantify the real-world impact of their data. “It’s all about timely, accurate data,” Thurston adds. “Once market participants know a rebalance for active ETFs is happening, they can widen spreads; when they get the new, accurate data, they can then tighten the spreads. That impact is what drives the market.”

By combining the ‘what’ of an ETF’s composition with the ‘how’ of its real-world trading behaviour at the most granular level, the partnership aims to equip firms with the insights needed to tighten spreads, improve pricing, and gain a competitive edge in the increasingly complex ETF ecosystem.

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