09.06.2018

In Fixed Income, Data Dominates

09.06.2018
Terry Flanagan

It’s easy enough to track trading in Apple stock, which consists of one security that trades electronically and pretty much continuously on one U.S. exchange. But what about a bond that’s one of a company’s 30 issues, which changes hands infrequently in a marketplace with numerous trading venues and protocols, including voice?

Pertinent trade info may be available, but it may be only partial, and/or not timely. And the lift of procuring reliable, high-quality data — much of it still resides on off-screen books — is heavy.  

However, the end result — better trade decisions — has made corralling and utilizing trade data in the expansive and decidedly non-homogeneous fixed income market a front-center pursuit for institutional managers.     

Gianluca Minieri, Amundi

“Data are becoming increasingly important not only for the more traditional liquid asset classes, such as large-cap equities, but also for bonds,” said Gianluca Minieri, Deputy Global Head of Trading at Amundi, Europe’s largest asset manager. “Data will be key not only to enhance even further the execution quality of liquid instruments, but also and in particular to support the long-awaited ‘equitization’ of fixed income markets.”

At the July 16 meeting of the Fixed Income Market Structure Advisory Committee, pre-trade transparency — i.e. having enough high-quality data to work with in order to make the best trade decisions — was a primary topic of discussion.

Thomas Urano, Portfolio Manager at boutique fixed income manager Sage Advisory, noted that data available to fixed income managers has evolved and expanded substantially over the past couple decades. Urano termed the present landscape, which includes information from dealers, electronic trading platforms, and the Trade Reporting and Compliance Engine (TRACE), as “unofficial pre-trade transparency.”

The conundrum is that fixed income data is generated from the most frequently transacted bonds — which aren’t the ones that most need data to guide a trade. “You’re trying to source data, information, determining where the market is…using liquid bonds because that’s where the data is available,” Urano said at the Fimsac meeting in Washington D.C. “But then the real challenge is how you transpose that information to illiquid securities.”

Urano added, “trying to source as much data, having it available, and having it immediate, from our
perspective, is key in handling pre-trade transparency.”

With risk-free yields still at low levels by historical standards, large fixed income managers that at one time might be able to skate by with less-sophisticated trading operations are feeling pressure to get up to speed on data management.    

“The search for yield has led to an increase in the sophistication of investment strategies across the board, including at traditionally more conservative investment firms, such as pension funds, long-only asset managers, and insurance companies,” Amundi’s Minieri told Markets Media. “Our role has dramatically changed and is posing increasingly more focus on data. In the current highly fragmented trading environment, data are key to successfully search for non-toxic liquidity and best prices.”

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HSBC AI Markets harnesses natural language processing to meet market participants’ trading and hedging needs, from pre-trade analysis, to execution, to post-trade. Markets Media caught up with Tom Croft to learn more about the platform.

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