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AI News Chipmakers GPU-accelerated finance analytics

London Stock Exchange cuts market data analysis time with Nvidia tie-up

The deal will let financial institutions process decades of historical market data in seconds rather than hours, using GPU-accelerated computing.

by TechDefused Newsroom · Editor IL
The image shows a wall plaque displaying the name of the London Stock Exchange Group. The plaque features both the name and the emblem of the organization, set against a textured stone background. — Credit: Photo by David Vincent on Unsplash c Photo by David Vincent on Unsplash

London Stock Exchange Group (LSEG) has partnered with Nvidia to let financial institutions analyse huge volumes of historical market data at far greater speed using graphics processing unit (GPU) technology.

Benchmark testing found that years of LSEG's Tick History data can be processed in seconds using Nvidia's cuDF software library for GPU-accelerated computing, versus hours under conventional methods.

Tick History holds 110 trillion rows of data across 100 million instruments, spanning more than 30 years and more than 580 exchanges, trading venues and data contributors.

Historical data

The collaboration brings that historical data closer to the computing environments used for quantitative research and artificial intelligence, without firms needing to duplicate the full dataset, preserving the licences, permissions and access controls that govern its use.

The timing reflects a shift toward near-continuous, 24-hour equity trading that is pushing firms away from legacy models built around market-close data loading and overnight processing runs.

Traffic over LSEG's real-time network grew 29% in the first half of 2026 compared with a year earlier, hitting a peak of 26 million messages per second in June, while customer API requests for Tick History data rose 48%.

Detailed inspection

Ron Lefferts, co-head of data and analytics at LSEG, said the deal lets customers work with detailed historical data at speed "without the burden and risk of creating another full copy."

Nvidia's Ioana Boier said cuDF allows researchers to analyse Tick History at scale without discarding the granular detail that makes it valuable for advanced analytics.

Expected uses include quantitative strategy testing, order book reconstruction, liquidity analysis, risk scenario modelling and historical market replay.

by TechDefused Newsroom