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

A-Team Insight Briefs

Trading Technologies Launches TT Broker Scorecard to Enhance Trade Cost Analysis

Subscribe to our newsletter

Trading Technologies has introduced TT Broker Scorecard, a monthly report ranking global and regional equity brokers by liquidity and execution quality. The rankings are based on anonymised trade data from Abel Noser Solutions, which TT acquired in 2023. This new tool aims to provide buy-side market participants with insights into broker performance across various market segments, while enabling sell-side firms to identify their strengths and areas for improvement.

TT Broker Scorecard is accessible through Trade Zoom, Abel Noser Solutions’ transaction cost analysis (TCA) platform, allowing users to review historical trade data and drill down for more detailed insights. The new offering builds on TT’s expansion in TCA services, including the recent rollout of TT Futures TCA, providing granular trade data analysis for futures markets.

Peter Weiler, EVP Managing Director, Data & Analytics at TT, commented: “In today’s ultra-competitive environment, the buy side is increasingly trying to find liquidity in highly concentrated markets, while the sell side is seeking ways to protect and grow market share. TT Broker Scorecard will help firms on both sides uncover distinct business advantages by leveraging the massive universe of data that flows through our market-leading TCA platform. Our buy-side clients can find the counterparties that are most active in specific regions, countries, capitalizations, sectors and other segments. Sell-side brokers can identify and promote where they offer the most liquidity while establishing where they should focus on growing, leapfrogging competition or maintaining market share.”

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: Navigating the Build vs Buy Dilemma: Cloud Strategies for Accelerating Quantitative Research

For many quantitative trading firms and asset managers, building a self-provisioned historical market data environment remains one of the most time-consuming and resource-intensive steps in establishing a new research capability. Sourcing data, normalising symbologies, handling corporate actions and maintaining infrastructure can take months and absorb significant budget before a single model is tested. At the...

BLOG

Aeron and QuestDB: Building Open Infrastructure for Capital Markets Data

“Co-authored by Adaptive | Aeron and QuestDB” Authors: Ralph Swann, Strategy Group, Adaptive Nicolas Hourcard, CEO, QuestDB Three questions every trading-tech leader is being asked right now. When the matching engine fails over, can we prove every order was handled in the order it arrived, with no losses and no surprises for the regulator? And...

EVENT

TEST Event page 2

Now in its 15th year the TradingTech Summit London brings together the European trading technology capital markets industry and examines the latest changes and innovations in trading technology and explores how technology is being deployed to create an edge in sell side and buy side capital markets financial institutions.

GUIDE

AI in Capital Markets Handbook 2026

AI adoption in capital markets has moved into a more disciplined phase. The priority is now controlled deployment: where AI can be used safely, where it can deliver measurable value, and how outputs can be governed, monitored and evidenced. The 2026 edition of the AI in Capital Markets Handbook examines how AI is being applied...