Grading the Claims
Attend any fixed income industry conference or subscribe to any industry newsletter and you are bound to come across the claim that fixed income markets are beginning to be, going to be, or already have been equitized. That is a true statement today, and it was a true statement a decade, or more, ago. And in that time there have been many attempts to make it so, some valiant, and some even successful. But what does it even mean to equitize?
The equity market has many conventions and many rules. Most of those conventions and rules have evolved over time, making the definition of equitized a moving target. A fair, albeit simple, description of the current equity market is a vast group of markets that are interconnected by rule and technology, some of which participate in price discovery (and pre-trade transparency) and some of which do not (dark pools), all of which are auto-executable, but only for the smallest incremental amount. Those equity market basic features have led to technology-enabled enhancements. Specifically, pre-trade transparency and actionable quotes of very small sizes led to the growth of portfolio trading which led to the growth of algorithmic trading.
So let’s take a look at how equitized the fixed income markets have become (or are likely to become) and assign some good old-fashioned letter grades.
Central Limit Order Book: D-
While a D- might seem a harsh way to start the grading, it is important to keep in mind that not even the equity market has a CLOB (unless you want to switch the C to stand for connected) hundreds of years after trading began under a tree. With the prevalence and strength of the existing electronic execution venues it seems the time for a central limit order book has come and gone.
Algorithmic Trading: C-
This one is tough. On the one hand I recently attended a conference where a representative of one of the largest algorithmic pricing firms asked, “do I manually TWAP this trade?” Sure, Time Weighted Average Price is an algorithm, but doing it by hand seems a violation of the spirit of algorithms. On the other hand, that is precisely what was happening in the equity markets two decades ago. In the early 2000’s when Credit Suisse was eating everyone’s lunch with their algorithms, every firm was claiming they had algorithms too, even if it was just their portfolio traders manually slicing orders. This is not unlike now when everyone feels compelled to state they use artificial intelligence even if it is just intelligence they are using (i.e. throwing bodies at the problem).
Pre-Trade Transparency: C+
Perhaps we need to consider partial credit for this grade as the range of possible grades is as wide as the range of fixed income asset classes. For US Treasury trading the availability of pre-trade transparency nearly rivals what is available in equity markets, though it does fall short for retail investors. Credit bids and offers have grown steadily with the entrance of new trading protocols and new, algorithmic pricing providers. And while municipals have participated in this growth, they start from a much smaller base. Meanwhile, asset classes like MBS and leveraged loans remain very much the province of professional, specialized traders with access to unique, expensive data sources.
Executable Prices: B-
One of the hallmarks of equity markets is that there is virtually always an executable price for every equity during market hours. This always available liquidity is typically available for very small trades. The most active participants in providing that stream of incremental liquidity have expanded their offerings to many corners of the fixed income markets. By building algorithmic pricing models they can stream liquidity to the marketplace. Firms like Brownstone, Citadel, Millenium Advisors, and Virtu have become regular conference participants as they seek to grow their algorithmic pricing businesses. And many of the incumbents in the business have built, or bought (Toronto-Dominion acquired Headlands), their own algorithmic pricing capabilities. There is even now at least one ATS (OpenYield) that advertises itself as algorithmic pricing friendly.
Portfolio Trading: A+
One of the most talked about trends in credit markets is the growth of portfolio trading, a feature previously unique to equity markets. From humble beginnings credit portfolio trading now accounts for almost 8% of customer trades and 14% of un-capped customer volume (6% of “capped” volume). But that is only part of the story. The earliest form of fixed income portfolio trading is, of course, ETF trading. And through ETFs portfolio trading extends beyond credit trading to encompass every form of fixed income investing.
Conclusion
One thing should be eminently clear by now, the fixed income market will never be exactly like the equity market. Even saying “the fixed income market” incorrectly categorizes it as monolithic. With the plethora of fixed income offerings, the best anyone can hope for is a spectrum of equitization. But innovation will continue to reign. Entrepreneurs will continue to experiment with equitization to find a better way. And many of the roadblocks of the past (diversity of instruments, specialization and compartmentalization of knowledge, processing power, technology capable of handling mass and disparate data) have been removed or are in the process of being removed. A little over a decade ago it would have been hard to imagine algorithmic pricing, but now it is here to stay. And with advancements in computing, from artificial intelligence to quantum computing, there is no reason to believe that equitization will stall at its present level.
