News, Insight and Events

24 January, 2023

Going for growth to democratise Level 3 data

Best Execution caught up with Paul Humphrey, CEO of BMLL, which recently secured $26m of Series B investment to support the firm’s growth strategy.

9 January, 2023

Cboe Europe Equities Yearly Recap and Look Ahead

Using BMLL harmonised data Natan Tiefenbrun, President, Cboe Europe, compares time at EBBO, across the FTSE100, with Cboe's competitor venues.

22 December, 2022

The TRADE predictions series 2023: Data

Paul Humphrey, CEO, BMLL Technologies: 'Firms that realise the predictive power of Level 3 data will understand their markets better, derive more predictive analytics, and leave those still using lower-quality data behind.'

8 December, 2022

Tight NBBO Matter to Off-exchange Trades Too

Using BMLL Data, Phil Mackintosh, Chief Economist, Nasdaq, explore the differences in price between odd NBBO and the NBBO-midpoint for the same stock and highlights why the difference is importance for the end investor.

14 November, 2022

IEX ‘Boxes and Lines’ market structure podcast

IEX’s Ronan Ryan and John Ramsay talk with BMLL’s Paul Humphrey and Dr Elliot Banks in Ep. 72 ‘What’s historical data anyway?’.

11 October, 2022

BMLL Launches Data Visualisation Tool for Equities & ETFs

BMLL Vantage democratises access to Level 3 order book data and analytics through an intuitive visualisation tool, thereby removing the need to code in order to derive meaningful insights.

6 October, 2022

What Makes Other Countries’ Trading Tick?

Using BMLL Data, Phil Mackintosh, Chief Economist, Nasdaq, examines how the system of round lots and 1-cent ticks in the U.S. creates inefficiency as stock prices rise and fall.

15 September, 2022

Comparing AAPLs and Apples

Using BMLL Data, Phil Mackintosh, Chief Economist, Nasdaq, analyses 'Average Spread at Notional Depth' when comparing Nasdaq and NYSE market quality.

13 September, 2022

SIX Infosnack 11: Crumble in the Jungle

Using BMLL data, SIX highlights the trade-off between fill probability and adverse selection utilising Order Book Imbalance (OBI) state and a Crumbling Quote Signal (CQS).