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

Bloomberg Tradebook Launches Customizable Algorithm

Subscribe to our newsletter

Bloomberg Tradebook, the global agency brokerage business, has launched a Relative Benchmark Trading Algorithm on its PAIR cross-asset trading platform. The added algorithm gives Tradebook users the ability to customize how they trade securities relative to benchmarks they choose, according to Michael Baradas, cross-asset product manager at Bloomberg Tradebook.

“Active investors are trying to find assets that aren’t correlated to the market. In individual constituents of an index, correlation may be high at times, or there may be opportune times when it’s not correlated,” said Baradas. “That’s when active managers believe they can outperform. … The Relative Benchmark Trading Algorithm lets them do that. Given a benchmark like the S&P 500, it lets the trader or portfolio manager set certain parameters, so when a security is underperforming the index, they are buying, or when it’s outperforming, they’re selling.”

The PAIR platform, launched in 2009, allows simultaneous trading of multiple asset classes, and is integrated with the Bloomberg Professional service, thus leveraging Bloomberg’s data resources.

“Exchanges have different rules for price ticks, order sizes and messaging, and how many orders you can send,” said Baradas. Such rules may prevent algorithms from working. “Having the knowledge and access to all that data in real-time — and having the Bloomberg network to connect to all these exchanges and take in that data feed makes the algorithm more powerful,” he added.

PAIR’s Relative Benchmark Trading Algorithm can adjust itself depending on the rules in whichever market is the venue for a trade, explained Baradas. “The customer sees the same ticket,” he said. “They’re just buying one security and selling another one. They define that relationship and the algorithm on the back end understands those differences.”

The next capability Bloomberg may add to the algorithm is the ability to work with customized benchmarks and indices, added Baradas. “Fund managers and investors are trying to outperform their peers, so if they can find an edge with their own quants and their analysis is a better benchmark to track against, they can create custom indices on the Bloomberg terminal,” he said. “Tradebook would have a way to get that custom index to use to trade against.”

Subscribe to our newsletter

Related content

WEBINAR

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

Date: 20 May 2026 Time: 10:00am ET / 3:00pm London / 4:00pm CET Duration: 50 minutes 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...

BLOG

Infrastructure Modernisation, Intelligent Workflows, Data Strategy and More: A Preview of TradingTech Summit London 2026

The conversation around trading technology has become more exacting over the past year. AI is moving into production environments. Data estates are being rationalised and rebuilt. Infrastructure decisions are increasingly shaped by resilience, transparency and regulatory pressure. Against that backdrop, A-Team Group’s TradingTech Summit London 2026 takes place at a time when firms are reassessing...

EVENT

Eagle Alpha Alternative Data Conference, Fall, New York, hosted by A-Team Group

Now in its 8th year, the Eagle Alpha Alternative Data Conference managed by A-Team Group, is the premier content forum and networking event for investment firms and hedge funds.

GUIDE

FRTB Special Report

FRTB is one of the most sweeping and transformative pieces of regulation to hit the financial markets in the last two decades. With the deadline confirmed as January 2022, this Special Report provides a detailed insight into exactly what the data requirements are for FRTB in its latest (and final) incarnation, and explores what needs to be done in order to meet these needs on a cost-effective and company-wide basis.