Waters Wrap: Reading the fixed-income tea leaves

Some selected quotes from recent earnings calls:

“In 2023, as we’re entering 2024, there are still clients that pick up the phone and do trades like it’s 1994.”

—Billy Hult, CEO, Tradeweb

https://www.waterstechnology.com/trading-tech/7951394/tradeweb-turns-attention-to-automating-larger-trades-in-credit

“As we approach peak interest rates, we expect a resurgence in fixed-income flows, with clients capitalizing on higher yields.”

—Larry Fink, CEO, BlackRock

https://www.waterstechnology.com/trading-tech/7951361/blackrock-forecasts-return-to-fixed-income-amid-efforts-to-electronify-market

“[W]e do anticipate higher levels of demand for both automation and algo solutions in both credit and rates growing in the years ahead.”

—Chris Concannon, CEO, MarketAxess

https://www.waterstechnology.com/trading-tech/7951388/for-marketaxess-portfolio-trading-buoys-flat-revenue

The hype machine

I recently came across a story from 2007 on our website with this as the headline: “Hybrid Demand Continues to Dominate Fixed Income”. The story quotes a research paper, which estimated that “75% of overall fixed-income trading will be done electronically by 2011, up from the estimated 65% electronic adoption rate seen today [2007].”

Now, our CMS wasn’t quite as sophisticated back then, so there isn’t a link to the report, and I can’t find it online. Since I’m lacking the source material, I’ll give the benefit of the doubt that some context is missing. That said, earlier this year, the Securities Industry and Financial Markets Association put out a report, in conjunction with research firm Coalition Greenwich, which stated this:

“[T]he fixed-income market as a whole is undergoing a digital transformation that aligns with that of the broader global economy. But while the trading process has digitalized broadly and market transparency has grown, the exact scale and nature of this electronification varies considerably across the fixed-income product landscape. … [The] data shows that two-thirds of US Treasury trading (by notional) was traded electronically in 2022, making it the most electronically traded fixed-income market in the world.”

So it would seem to me that the estimate from that 2007 report was quite a bit off. And, if I’m being honest, I think I understand why. As an industry, we tend to get lost in that seemingly clean number of “percentage traded electronically”, and don’t focus enough on the reasons why electronic trading is growing.

This month marks my 14^th anniversary as a journalist at WatersTechnology (originally known as Waters…why we rebranded, I have no clue). Since I joined, I’ve been to numerous conferences and read likely hundreds of research reports talking up the electronification of the fixed-income markets. And the media—including WatersTechnology—has been guilty of feeding that hype machine.

Again, though, I think I understand why. In the world of capital markets technology, some of the most interesting advancements—in terms of new tools, new datasets and evolving market structure—are happening in fixed income when compared to equities, foreign exchange, and commodities. And while the CEOs of BlackRock, MarketAxess and Tradeweb certainly have their own horses in the fixed-income tech and analytics race, it’s also clear that there’s a lot of room for advancement in this arena as we head into 2024.

New toys

Let’s first take a look at some of the new tools that have hit the market this calendar year. And right now, the hottest topic in technology—finance or otherwise—is that of large language models (LLMs), and, by extension, generative AI.

GenAI isn’t a panacea—rather, when used correctly, it’s an efficiency play. One of the most interesting use cases is the very first GPT—or generative pre-trained transformer—to hit the capital markets: BloombergGPT. Back in March, Shawn Edwards, Bloomberg’s CTO, told WatersTechnology that the project aims to assist—and provide more depth to—the Terminal’s sentiment analysis, named-entity recognition, news classification, charting, and question-answering capabilities, among other functions.

“This is all very early days and we’re just scratching the surface—this is really Day One,” he said. “But the dream—and we’ve been working on this for years—has been for a user to walk up to the Terminal and ask any question and get an answer or lots of information; to get you to the starting point of your journey.”

It should be noted, though, that BloombergGPT is not aimed solely at fixed income. So let’s get even more niche.

As noted previously, fixed income is a space that still has a lot of manual workflows, especially when you get into markets like munis, mortgage-backed securities, or asset-backed securities—each of which, says that Sifma report, is less than 10% electronified.

That means chat is still a massively important component of trading in this asset class. Intercontinental Exchange’s ICE Chat is a desktop and mobile messaging platform. It includes a marketplace directory of market participants, and allows clients to message one another, participate in chat rooms, blast messages to multiple users for price discovery, and also uses quote and trade recognition logic and APIs to recognize and extract data from chats into actionable data for trading.

The exchange recently added an LLM component to ICE Chat. In August, Lynn Martin, president of the New York Stock Exchange and chair of ICE’s Fixed Income & Data Services business, said the exchange has seen a 60% increase in the number of transactions executed via the platform as a result of refining proprietary LLMs that help automate trading over the platform.

“We’re seeing good demand for adoption of our proprietary LLMs, and we are seeing the effect of that not just in our data services revenues,” she said.

But bleeding-edge technologies are not going to solve the manual woes that exist in fixed income. Rather, the simplification of workflows via interoperability is at the core of much tech development in the space. And sometimes that means competitors forming partnerships.

S&P Global made waves with its 2020 acquisition of IHS Markit. Included in that deal was Ipreo, which IHS Markit bought in 2018. And with Ipreo came a product the company had built called InvestorAccess, which provides a technology platform for the sell side to communicate electronically about new opportunities and present them to the buy side. The platform then facilitates new issue allocations and full automation to order management systems used by firms on both the buy side and sell side. It currently supports primary issuance in US equities, US municipal bonds, and global fixed income.

In June, S&P announced the integration of InvestorAccess and Bloomberg’s TSOX execution management system to streamline the syndicated primary bond workflow. Mutual clients of both can stage orders from their order management system into TSOX, connecting to InvestorAccess and the syndicate book, which will send final allocations back to the OMS.

“What the buy side has been waiting for is for the market to deliver a solution that connects their OMS platform all the way through to the bank’s book-build platforms,” Nick Hall, head of fixed-income primary markets at Bloomberg, told WatersTechnology. “And the TSOX connection to S&P’s InvestorAccess is the first time anyone has ever done that in the primary market.”

Tradeweb, on the other hand, is leaning into its automated execution platform, AiEX, to drive usage. “Electronically, credit is a young market that is ripe for further innovation,” said Tradeweb president Tom Pluta on a recent earnings call. Results have been solid: for global credit, average daily trading on AiEX increased 95% year-over-year. The vendor is also using its unique proprietary API approach to drive adoption (and stickiness…and some controversy).

Data differentiates

New tools are pretty, but the simple reality is that if those systems aren’t interoperable, then they can’t provide what’s most important: context and analytics.

Earlier this year, MarketAxess made a big bet with its acquisition of Pragma, which specializes in algorithmic trading across asset classes, but with a sharper focus on equities and FX. Yet, as electronic trading grows, MarketAxess believes that the proliferation of data that comes with higher velocity markets will give algorithms a central role.

“There was much more interaction from every side on an automated basis, deployment of algos by dealers, opportunities to interact with other kinds of liquidity in the market. We felt like the best response was to partner with Pragma,” Gareth Coltman, global head of automation at MarketAxess, told WatersTechnology after the deal was announced. “…What we plan to do with Pragma is to build on what we’ve already started with Adaptive Auto-X, which is to develop more sophisticated, higher-velocity automation tools to our platform.”

And then, of course, there’s BlackRock and Aladdin, which has been on a big interoperability push in order to improve the platform’s analytics capabilities on one screen.

“So much of the strategy with respect to accounting and data is all about just solving for more of that surface area,” Sudhir Nair, global head of the Aladdin business, recently said. “And we see a world where having three books of record, three sources of truth, just isn’t going to work. It isn’t going to work in a world where everything is converging … [and] where markets are moving fast, and alpha is going to come by your ability to bring that data forward and put it in the hands of your investors.”

And in the “if you can’t build it, buy it” category, pricing and risk analytics vendor Numerix acquired Fincad earlier this year.

As a specialist in fixed income, Fincad fills a gap for Numerix. “When you think about the pricing layer of our product, one of the areas that we were weak up until Fincad was the fixed-income area,” said Steve O’Hanlon, who recently retired. (Click here if you want to hear Emanuele Conti, Numerix’s new CEO, discuss his vision for the vendor going forward.)

Also on the M&A front, in March, Bloomberg announced it had entered into an agreement to acquire fixed-income trading technology provider Broadway Technology in a move to provide customers with better access to the rates and credit markets.

“We were getting feedback from our clients that we really needed to service their rates business as well, so they wanted us to do that,” said Ben Macdonald, global head of enterprise products at Bloomberg.

At the same time, Chicago-based futures trading software provider Trading Technologies (TT), announced it was acquiring AxeTrading. Similar to Numerix-Fincad, it was all about asset class expansion to increase its data intake and analytics output so as to be more of a one-stop shop.

“This deal takes us into the much bigger, wider, and deeper corporate bond market, and the government bond market as well,” said TT’s executive vice president, Nick Garrow.

Evolution & everyday

Industry headwinds such as shrinking margins, regulatory pressures, and inflation and geopolitical fears are squeezing investment managers. We’ve written this before, but let me play the classics one more time:

Banks, asset managers, and exchanges are all expanding into the cloud. On top of that, end-users are becoming increasingly comfortable with the idea of not just taking from the open-source community, but contributing to it. End-users and vendors are also embracing APIs as the preferred way to connect to data sources. So it is that data is easier to acquire, store, and analyze. But providing actionable insights into that data—whether for trading, risk, settlement, or cyber—is of paramount importance. And it’s easier to provide context if systems are interoperable and if AI is used to help in these efforts, which, as noted before, can be seen by the rise of large language models and generative AI.

Even still, while new technologies present exciting opportunities for fixed income to evolve, the simple truth is that firms that are unable to create coherent and long-term strategies around data sourcing, mapping, lineage, and governance will ultimately stumble and fall. It starts with getting your data in order and then using new tools/platforms to present that data to users through customizable and easy-to-interpret user interfaces.

Electronification of fixed income both has been coming and is coming. Perhaps it’s best to not worry about what percentage of the market is electronified and instead focus on which targeted projects are working well, and which have been tossed into the bin of history to serve as learning lessons.

And I hope the many links above help in that endeavor. If not, let me know: anthony.malakian@infopro-digital.com.

The image accompanying this column is “Three Girls Having Tea” by Nishikawa Sukenobu courtesy of The Met’s open-access program.